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CSIROHEALTH&BIOSECURITY TelehealthPilotsProgram DepartmentofHealth FinalProjectReport Organisation: Australiane-HealthResearchCentre(AEHRC),CSIRO DateSubmitted: May2016 Authors: FINALREPORT May2016 Prof.BrankoCeller,Dr.MarlienVarnfield,Dr.RossSparks,Dr.JaneLi,Dr.SuryaNepal, Dr.JulianJang-Jaccard,Mr.SimonMcBride,andDr.RajivJayasena Copyrightanddisclaimer ©2016CSIROTotheextentpermittedbylaw,allrightsarereservedandnopartofthispublication coveredbycopyrightmaybereproducedorcopiedinanyformorbyanymeansexceptwiththewritten permissionofCSIRO. Importantdisclaimer CSIROadvisesthattheinformationcontainedinthispublicationcomprisesgeneralstatementsbasedon scientificresearch.Thereaderisadvisedandneedstobeawarethatsuchinformationmaybeincomplete orunabletobeusedinanyspecificsituation.Norelianceoractionsmustthereforebemadeonthat informationwithoutseekingpriorexpertprofessional,scientificandtechnicaladvice.Totheextent permittedbylaw,CSIRO(includingitsemployeesandconsultants)excludesallliabilitytoanypersonfor anyconsequences,includingbutnotlimitedtoalllosses,damages,costs,expensesandanyother compensation,arisingdirectlyorindirectlyfromusingthispublication(inpartorinwhole)andany informationormaterialcontainedinit. ii I. Contents I. CONTENTS...................................................................................................................................................3 II. REVISIONHISTORY......................................................................................................................................7 III. ACKNOWLEDGEMENTS............................................................................................................................8 IV. LISTOFFIGURES.......................................................................................................................................9 V. LISTOFTABLES.......................................................................................................................................12 VI. LISTOFABBREVIATIONS.........................................................................................................................15 1. EXECUTIVESUMMARY...............................................................................................................................17 2. INTRODUCTIONANDBACKGROUND..........................................................................................................19 2.1 EVIDENCEOFUNSUSTAINABLEINCREASESINHEALTHCARECOSTSANDINTHEDEMANDFORHEALTHWORKFORCE............20 2.2 EVIDENCEFORAGEINGDEMOGRAPHICSANDTHEINCREASINGBURDENOFCHRONICDISEASE........................................20 2.3 EVIDENCEFORTELEHEALTHSERVICESFORTHEMANAGEMENTOFCHRONICDISEASE....................................................21 2.4 HIGHLEVELPROJECTTIMELINE.........................................................................................................................24 3. AIMSANDOBJECTIVES..............................................................................................................................25 4. METHODS..................................................................................................................................................27 4.1 ORGANISATIONCHARTS...................................................................................................................................27 4.2 OPERATIONALRESPONSIBILITIES........................................................................................................................28 4.3 SELECTIONOFTELEMONITORINGSERVICE............................................................................................................29 4.4 CLINICALTRIALPROTOCOL................................................................................................................................31 4.5 SELECTIONOFPARTICIPANTS.............................................................................................................................32 4.6 QUESTIONNAIREINSTRUMENTS.........................................................................................................................34 4.7 ADDITIONALINFORMATIONONENTRYANDEXITQUESTIONNAIREINSTRUMENTS.......................................................35 4.8 USEOFFOCUSGROUPS,STRUCTUREDINTERVIEWSANDQUESTIONNAIRES...............................................................37 4.9 DATAMODELS................................................................................................................................................38 4.10 METHODOLOGYFORDATAANALYSIS..............................................................................................................41 Questionnairedata..............................................................................................................................41 PBS,MBSandHospitaldata................................................................................................................42 5. RESULTS....................................................................................................................................................44 5.1 5.2 PATIENTRECRUITMENTOFTESTANDCONTROLPATIENTS......................................................................................44 Reasonsfordecliningorwithdrawingfromthestudy.........................................................................46 Demographicsofstudygroupsatbaseline..........................................................................................48 BaselinehealthcharacteristicsofTestandControlpatientsatpointofentry....................................50 USABILITYANDACCEPTABILITYOFTELEMONITORINGTOPATIENTS,CLINICIANSANDCARERS.......................................51 CSIROTelehealthTrialFinalReportMay2016 Page3of187 5.3 5.4 5.5 Patientexperiencewiththetelemonitoringtechnology......................................................................51 Patientcompliancewithmonitoringschedules...................................................................................53 UsageofTMCClinicianPortalandCSIROPortalbyCareCoordinators...............................................55 Clinicians’perceptionsoftelemonitoringbenefittopatients..............................................................56 Carers’perceptionsoftelemonitoringbenefittopatients...................................................................57 IMPACTOFTELEMONITORINGONPATIENTEXPENDITUREONMBSANDPBSITEMS....................................................58 DescriptivestatisticsformatchedTestandControlpatients..............................................................60 LinearregressionanalysisofimpactoftelemonitoringinterventionontotalMBSexpenditure.........61 ImpactoftelemonitoringonMBSexpenditure....................................................................................65 AnnualsavingsinMBSexpenditure.....................................................................................................66 AnalysisofDifferences(Control–Test)forMBSexpenditure..............................................................71 LinearregressionanalysisofimpactoftelemonitoringinterventionontotalPBSexpenditure.........72 ImpactoftelemonitoringonPBSexpenditure.....................................................................................75 AnnualsavingsinPBSexpenditure......................................................................................................77 AnalysisofDifferences(Control–Test)forPBSexpenditure...............................................................81 ANALYSISOFHOSPITALDATA–NUMBEROFADMISSIONSANDLENGTHOFSTAY........................................................83 Linearregressionanalysisofnumberofadmissions............................................................................83 Impactoftelemonitoringonnumberofadmissions............................................................................85 Analysisofdifferences(Control–Test)fornumberofadmissions......................................................86 LinearregressionanalysisofLengthofStay(LOS)..............................................................................87 ImpactofinterventiononLengthofStay(LOS)...................................................................................88 Analysisofdifferences(Control–Test)forLengthofStay..................................................................89 EFFECTOFTELEMONITORINGINTERVENTIONONMORTALITY..................................................................................90 Mortalitycalculationsbasedoncomparativecrudedeathrates........................................................91 AgespecificDeathRatesofTestpatientsrelativetotheBDMdatabase............................................92 5.6 TESTPATIENTSELF-REPORTEDMEASURESATFOLLOW-UP.......................................................................................93 5.7 IMPLEMENTINGAHIGHDEFINITIONWEBRTCTELECONFERENCINGSYSTEM...............................................................95 5.8 DEMONSTRATIONOFTELEHEALTHREPORTUPLOADTOPCEHR...............................................................................98 5.9 DEVELOPMENTOFARISKSTRATIFICATIONSYSTEMFORTELEHEALTH.........................................................................98 5.10 DISCUSSIONOFRESULTS...............................................................................................................................99 6. CONCLUSIONS..........................................................................................................................................103 6.1 COSTOFDELIVERINGTELEHEALTHSERVICES......................................................................................................105 6.2 HEALTHECONOMICSOFTELEMONITORING.........................................................................................................106 6.3 ORGANISATIONALCHANGEMANAGEMENTANDIMPACTONWORKPLACECULTURE.................................................107 6.4 BENEFITSFORPATIENTSANDCLINICIANS............................................................................................................108 CSIROTelehealthTrialFinalReportMay2016 Page4of187 6.5 INTEGRATIONOFTELEMONITORINGSERVICESINTOTHEHEALTHCARESECTOR..........................................................109 6.6 SUSTAINABILITYOFTELEHEALTHENABLEDHEALTHCARESERVICES...........................................................................110 Factorsinhibitingsustainabilityoftelehealthservices......................................................................110 IncentivesforprivatesectorinvestmentintoTelehealth...................................................................111 InternationalevidenceforwideradoptionofTelemonitoringservices.............................................111 7. FINANCIAL................................................................................................................................................113 8. APPENDIX.................................................................................................................................................115 8.1DATAARCHITECTURE..........................................................................................................................................115 8.2 8.3 8.4 8.5 8.6 DATAINTEGRATION.......................................................................................................................................117 DHSPBS/MBSDataformat................................................................................................................118 HealthRoundtableFormat................................................................................................................119 METHOD2:DETAILEDSTATISTICALANALYSISUSINGBACIANDLMEMODELS...........................................................126 BACIdesignandlinearmixedeffectsmodels....................................................................................126 Powercalculations.............................................................................................................................129 FinalLinearMixedEffectsModelsforMBS.......................................................................................130 FinalLinearMixedEffectsModelsforPBS.........................................................................................137 METHOD3:MONITORINGCUMULATIVESUMOFDIFFERENCESINCOSTSOVERTIME.................................................144 CumulativesumofdifferencesininGPCostsovertime....................................................................144 Cumulativesumofdifferencesinspecialistcostsovertime..............................................................146 Cumulativesumofdifferencesinlaboratorycostsovertime............................................................147 Cumulativesumofdifferencesofprocedurecosts............................................................................148 CumulativesumofdifferencesofnumberofGPvisits.......................................................................149 Cumulativesumofdifferencesofnumberofspecialistconsultations...............................................150 Cumulativesumofdifferencesofnumberoflaboratorytests...........................................................151 Cumulativesumofdifferencesofnumberofprocedures..................................................................152 DEVELOPMENTOFAWEBRTCVIDEOCONFERENCINGSERVICE.............................................................................153 TelemedcareVideoConferencing......................................................................................................153 WebRTCPrototypeImplementation..................................................................................................155 LaboratoryTestofWebRTCVideoConferencingSystem...................................................................160 IMPLEMENTATIONOFTELEHEALTHREPORTUPLOADTOPCEHR.............................................................................161 ProjectPCEHRIntegration.................................................................................................................162 ExampleofautomaticallygeneratedtelehealthReportsuitableforuploadingtoPCEHR................163 8.7 RISKSTRATIFICATIONSYSTEM–PROTOTYPEDEVELOPMENT.................................................................................165 8.8 REFLECTIONSOFAPROJECTOFFICER................................................................................................................182 9. PUBLICATIONS..........................................................................................................................................183 CSIROTelehealthTrialFinalReportMay2016 Page5of187 9.1 REFEREEDJOURNALPUBLICATIONS...................................................................................................................183 9.2 CONFERENCEPROCEEDINGS............................................................................................................................183 9.3 CONFERENCEPRESENTATIONS.........................................................................................................................184 10. REFERENCES..........................................................................................................................................185 CSIROTelehealthTrialFinalReportMay2016 Page6of187 II. RevisionHistory Date Version ReasonforChange Changedby 25thMay2014 1.0 Developtemplateandinitialdraft RajivJayasena 16th,18th&June2014 1.1,1.2, 1.3 Majorworkingdrafts BrankoCeller 22ndJune2014 1.4 IncludeFinancialsandupdate RajivJayasena 23rdJune2014 1.5 FinalupdateforsubmissiontoDept ofHealth RajivJayasena 15thAugust2014 2.0 MajorUpdatesbasedoncomments receivedfromDeptofHealthand reformat BrankoCeller 20thAugust2014 2.1 Reviewandupdatesinpreparation forresubmission RajivJayasena 21stAugust2014 2.2 FinaliseDocumentforresubmission BrankoCeller& RajivJayasena September2014 3.0–3.3 FinalReportdraftversions BrankoCeller& RajivJayasena 30thSeptember2014 4.0 FinalReportSubmissiontoDOHA BrankoCeller& RajivJayasena 13thMay2016 5.0 UpdatedFinalReport BrankoCeller,Rajiv Jayasena&Marlien Varnfield CSIROTelehealthTrialFinalReportMay2016 Page7of187 III. Acknowledgements ConductingastudyaslargeandascomplexastheDepartmentofHealthTelehealthPilotsProgram“Home MonitoringofChronicDiseaseforAgedCare”requiredthesupportofnumerouspeopleandgroups. Assponsorsofthestudywouldliketoexpressoursincereappreciationtothefollowinggroupsandindividualsfor theircommitment,dedicationandsupport: TheCommonwealthDepartmentofHealth TheDepartmentofHumanServices TheCommonwealthScientificandIndustrialResearchOrganisation(CSIRO) TheCSIRODigitalProductivityandServicesFlagship TasmaniaNorthHealthDistrictandLauncestonHospital GrampiansRuralHealthAlliance DjerriwarrhHealthServices ACTHealthandCanberraHospital NepeanBlueMountainsLocalHealthDistrict NepeanBlueMountainsMedicareLocal AnglicanRetirementVillages–Penrith TownsvilleMackayMedicareLocal ParticipatingGeneralPractitioners TestandControlPatients TelemedcarePtyLtd iiNET CSIROSTAFF ProfessorBrankoCeller Dr.RajivJayasena Dr.MarlienVarnfield Dr.RossSparks Dr.SuryaNepal Dr.LeilaAlem Dr.JaneLi Dr.JulianJang-Jaccard Mr.SimonMcBride Mr.AlexanderPonomarev Mr.JohnO’Dwyer CSIROTelehealthTrialFinalReportMay2016 Page8of187 IV. ListofFigures Figure1GrowthinConsumerPriceIndex(CPI)forHospitalandotherhealthservices[16]..........................20 Figure2Separationsper1,000populationbysexandagegroup,allhospitals,2012–13[15].........................21 Figure3Projectorganisationchart.................................................................................................................27 Figure4OperationalresponsibilitiesandworkflowsforProjectstaff............................................................28 Figure5TelemedcareClinicalMonitoringUnit(CMU)...................................................................................30 Figure6TrialsitesalongeasternseaboardofAustraliaandTasmania..........................................................31 Figure7Schematicdiagramofdifferentdatasourcesandtheirsecureintegration......................................42 Figure8FinalcohortofTestandControlpatients..........................................................................................44 Figure9Timecourseof(a)connecting114Testpatients,and(b)consenting173ControlPatients............45 Figure10(a)PrimaryDiagnosis (b)DistributionofSEIFAindexacrosssites............................................49 Figure11Distributionofcommencementdatesformonitoringofvitalsigns...............................................49 Figure12DistributionofnumberofdaysofmonitoringofTestPatients(N=100).........................................49 Figure13UseoftheTMCClinicianWebportalbyClinicalCareCoordinators...............................................55 Figure14RecordofaveragedailyloginstotheCSIROPortal/clinician.........................................................56 Figure15Beforeandaftermeansmayappearidenticalwhendataisnonstationary..................................61 Figure16sqrt(MBSCosts)plottedfor(a)Testpatientsand(b)Controlpatientsat30dayintervals............62 Figure17PlotofDifferences(Control-Test)forMBSexpenditureagainst30dayintervals.........................62 Figure18Linearregressionandanocovacomparisonofregressionlinebeforeintervention(redtrace)and regressionlinefullyextendedfortimeperiodsafterinterventionforALLMBSControls(bluetrace)...........65 Figure19EstimateofimpactoftelemonitoringonMBSexpenditure...........................................................67 Figure20EstimatesofannualMBSexpenditureforTESTpatients(red)andCONTROLpatients(blue),before (solid)andafter(dottedlines)intervention....................................................................................................68 Figure21sqrt(MBSCosts)plottedfor(a)Testpatientsand(b)Controlpatientsat30dayintervals.Linear regressionlinesarecalculatedafterremovalofoutliers,whicharemarkedinred.......................................72 Figure22PlotofDifferences(Control-Test)forPBSexpenditureagainst30dayintervals..........................73 Figure23Ancovaanalysisofdifferencesinslopeofbeforedatasegmenttocombinedbefore+afterdatafor thecompletepatientcohort(N=100).AsP>0.05theslopeswerenotdifferent.........................................76 Figure24EstimationofsavingsonPBSExpenditurecurveprojectedforwardoneyear...............................77 Figure25EstimatesofannualPBSexpenditureforPBSTestpatients(red)andControlpatients(blue),before (solidlines)andafter(dottedlines)intervention...........................................................................................79 Figure26sqrt(30dayPBSExpenditure)for(A)FemalePatients(N=33)and(B)DiabeticPatients(N=20)..81 Figure27FitoflinearregressionlinesforNumberofHospitaladmissionsover100dayintervalsbeforeand afterintervention............................................................................................................................................84 Figure28Estimateofimpactofinterventiononnumberofadmissionsperannum.....................................85 Figure29LinearregressionofdifferencesforNumberofadmissions/annum...............................................86 CSIROTelehealthTrialFinalReportMay2016 Page9of187 Figure30FitoflinearregressionlinesforLengthofStay(LOS)over100dayintervalsbeforeandafter intervention.....................................................................................................................................................87 Figure31EstimateofimpactofinterventiononLOSperannum.................................................................89 Figure32LinearregressionofdifferencesforLOS/annum.............................................................................90 Figure33AgedistributioninMasterRegistry.................................................................................................92 Figure34AgeadjusteddeathratesinMasterRegistry..................................................................................92 Figure35CSIROPortalshowingbasicfunctionalityandaccesstomultipleservices....................................116 Figure36DataIntegrationschemadevelopedbytheCSIROforthetrial....................................................117 Figure37TimecourseofMBScostsforTASpatients...................................................................................132 Figure38TimecourseofMBScostsforTASpatientswithstartmonthsynchronised.................................132 Figure39TimecourseofMBScostsforVICpatients....................................................................................133 Figure40TimecourseofMBScostsforVICpatientswithstartmonthsynchronised.................................133 Figure41:PredictedMBScostsforQLDpatients..........................................................................................134 Figure42TimecourseofMBScostsforQLDpatientswithstartmonthsynchronised................................134 Figure43PredictedMBScostsforNSWpatients.........................................................................................135 Figure44TimecourseofMBScostsforNSWpatientswithstartmonthsynchronised...............................135 Figure45Figure10:PredictedMBScostsforACTpatients..........................................................................136 Figure46TimecourseofMBScostsforACTpatientswithstartmonthsynchronised................................136 Figure47PredictedPBScostsforTasmanianpatients.................................................................................139 Figure48TimecourseofMBScostsforTASpatientswithstartmonthsynchronised.................................139 Figure49PredictedPBScostsforVICpatients.............................................................................................140 Figure50TimecourseofMBScostsforVICpatientswithstartmonthsynchronised.................................140 Figure51PBSPredictedcostsforpatientsinQLD........................................................................................141 Figure52TimecourseofMBScostsforQLDpatientswithstartmonthsynchronised................................141 Figure53PBSPredictedcostsforpatientsinACT........................................................................................142 Figure54TimecourseofMBScostsforACTpatientswithstartmonthsynchronised................................142 Figure55PredictedPBScostsforNSWpatients...........................................................................................143 Figure56TimecourseofMBScostsforNSWpatientswithstartmonthsynchronised...............................143 Figure57CUSUMdifferencesinmatchedtestandcontrolpatients’GPcosts............................................144 Figure58TheEWMAofthematcheddifferencesin(average)30daycostsbetweenthetestandcontrol patients.........................................................................................................................................................145 Figure59CUSUMdifferencesinmatchedtestandcontrolpatients’specialistcosts..................................146 Figure60TheEWMAofthematcheddifferencesin(average)30dayspecialistcostsbetweenthetestand controlpatients.............................................................................................................................................146 Figure61CUSUMdifferencesinmatchedtestandcontrolpatients’laboratorycosts................................147 Figure62ThetimeseriestrendinEWMAsmoothedmatcheddifferencesin(average)30daylaboratorycosts betweenthetestandcontrolpatients.........................................................................................................147 CSIROTelehealthTrialFinalReportMay2016 Page10of187 Figure63CUSUMdifferencesinmatchedtestandcontrolpatients’procedurecosts................................148 Figure64TheEWMAofthematcheddifferencesin(average)30dayprocedurecostsbetweenthetestand controlpatients.............................................................................................................................................148 Figure65CUSUMdifferencesinmatchedtestandcontrolpatients’numberofGPvisits...........................149 Figure66TheEWMAofthematcheddifferencesin(average)30daynumberofGPvisitsbetweenthetestand controlpatients.............................................................................................................................................149 Figure67CUSUMdifferencesinmatchedtestandcontrolpatients’specialistconsultations.....................150 Figure68TheEWMAofthematcheddifferencesin(average)30dayspecialistconsultationsbetweenthetest andcontrolpatients......................................................................................................................................150 Figure69CUSUMdifferencesinmatchedtestandcontrolpatients’numberoflaboratorytests...............151 Figure70TheEWMAofthematcheddifferencesin(average)30daynumberoflaboratorytestsbetweenthe testandcontrolpatients...............................................................................................................................151 Figure71CUSUMdifferencesinmatchedtestandcontrolpatients’numberofprocedures......................152 Figure72TheEWMAofthematcheddifferencesin(average)30daynumberofproceduresbetweenthetest andcontrolpatients......................................................................................................................................152 Figure73SelectingpatientsfromtheTMCClinicianinterface.....................................................................153 Figure74Browserasksforapermissiontoaccessthelocalcameraandmicrophone................................155 Figure75SignallingandInteractions............................................................................................................157 Figure76Signallingandinteractiondata......................................................................................................160 Figure77Demonstrationoftwowayhighdefinition720pvideoconferencing...........................................161 Figure78VitalSignsMonitoringReportPCEHRUploadDemonstration......................................................161 Figure79OverviewofPCEHRintegration.....................................................................................................162 Figure80AnexampleofanoverviewplotforTasmanianpatients..............................................................168 Figure81Parallelcoordinateplotsindicatingmultivariatetrendsinapatient’smeasurement..................169 Figure82Anexampleofthetrendplotforpatient2fromTasmania..........................................................170 Figure83Anexampleofstepchangeinthetrend.......................................................................................171 Figure84Anexampleofachangepoint&magnitudeforscaleplot...........................................................171 Figure85Anexampleofmeasuresthathavenotchangedsignificantlyfromthebaseline.........................172 Figure86Bodytemperaturevaluesforpatient1.........................................................................................173 Figure87SpO2valuesforpatient6..............................................................................................................174 Figure88SBPvaluesforpatient6.................................................................................................................175 Figure89Bodyweightvaluesforpatient9...................................................................................................176 Figure90Bodyweightvaluesforpatient28.................................................................................................177 Figure91BodytemperatureofPatient2untiltheendofMarch2014........................................................178 Figure92BodyweightofPatient2untiltheendofMarch2014.................................................................179 Figure93HeartrateofPatient2untiltheendofMarch2014.....................................................................179 Figure94Systolicbloodpressure(SBP)ofPatient2untiltheendofMarch2014.......................................180 CSIROTelehealthTrialFinalReportMay2016 Page11of187 V. ListofTables Table1TelemonitoringServiceSelectionCriteria..........................................................................................29 Table2EthicsCommitteeApprovals...............................................................................................................32 Table3Clinicalcriteriaforeligibility...............................................................................................................33 Table4ExampleofcasematchingofControlpatientswithTestpatients.....................................................34 Table5KeyelementsoftheEntryandExitQuestionnaires...........................................................................35 Table6QuestionnaireInstrumentsandtheirschedule..................................................................................35 Table7EntryQuestionnaireinstrumentsandtheirinterpretation................................................................36 Table8Researchmethodsforevaluatinguseabilityandacceptabilityoftelehealthservices.......................37 Table9DataModelforevaluatingoutcomesandobjectives.........................................................................38 Table10Patientdemographicsandrecruitmentateachsite........................................................................45 Table11Reasonsgivenbypatientsfordecliningtoparticipateinthetrial...................................................46 Table12MainreasonsforconsentedTestpatientsnotcommencingmonitoring........................................47 Table13Reasonsgivenbypatientsforwithdrawingfromthetrial...............................................................47 Table14BasicdemographicsofTestandControlparticipantsatbaseline....................................................48 Table15AgeofTestandControlpatientsatstartoftelemonitoring............................................................50 Table16Self-Reportingmeasures,forTestandControlpatientsatEntry.....................................................50 Table17PatientresponsestoUserandSatisfactionSurvey-Telemonitoringequipment............................51 Table18PatientresponsestoUserSatisfactionSurvey–Telemonitoringservice.........................................52 Table19Patientcompliancewithmeasurementandquestionnaireschedules(ALLTestpatients)..............53 Table20Patientcompliancewithmeasurementschedules(TAS+ACTpatients)..........................................54 Table21Patientcompliancewithmeasurementschedules(NSW+VIC+QLD)...............................................54 Table22ProjectOfficersandCareCoordinatorsperceptionofbenefitstopatients.....................................56 Table23BaselinecomparisonbetweenTestandmatchedControlpatientsbeforeandafterintervention.60 Table24MBSItemNumbersincludedinanalysis..........................................................................................61 Table25Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–Allpatients...........................63 Table26Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–MALEpatientsonly...............63 Table27Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–FEMALEpatientsonly..........63 Table28Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–CARDIACpatientsonly.........64 Table29Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–RESPIRATORYpatientsonly.64 Table30Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–DIABETICpatientsonly........64 Table31Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–COMMUNITYmonitoredpatients .........................................................................................................................................................................64 Table32Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–HOSPITALmonitoredpatients65 Table33EstimateofannualexpenditureonMBSItemsforallpatientcohorts............................................66 CSIROTelehealthTrialFinalReportMay2016 Page12of187 Table34EstimatesofMBScostsandsavingsofTestpatientsoneyearbeforeandoneyearafterthe intervention.....................................................................................................................................................70 Table35EstimatesofMBSsavingsofTestPatientsrelativetoControlpatientsoneyearaftertheintervention, usingdifferences(Control–Test)...................................................................................................................71 Table36ComparisonofMBSsavingscalculatedfromTestpatientsaloneandfromDifferences(Control-Test) .........................................................................................................................................................................72 Table37Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–Allpatients............................73 Table38Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–MALEpatientsonly................74 Table39Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–FEMALEpatientsonly...........74 Table40Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–CARDIACpatientsonly..........74 Table41Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–RESPIRATORYpatientsonly..74 Table42Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–DIABETICpatientsonly.........75 Table43Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–COMMUNITYmonitoredpatients .........................................................................................................................................................................75 Table44Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–HOSPITALmonitoredpatients75 Table45EstimateofannualexpenditureonPBSItemsforallpatientcohorts..............................................77 Table46EstimatesofPBScostsandsavingsforTestpatientsoneyearaftertheintervention.....................80 Table47EstimatesofPBSsavingsoneyearaftertheintervention,usingdifferences(Control-Test)...........81 Table48ComparisonofPBSsavingscalculatedfromTestpatientsaloneandfromDifferences(Control-Test) Savingsareshownaspositivevaluesandincreasesareshownasnegativevalues.......................................82 Table49SelectionofTestandControlpatientsforanalysisofhospitaladmissionsandLOS........................83 Table50ResultsofregressionanalysisofNumberofHospitalAdmissionsforBeforeandAfternumberof admissions.......................................................................................................................................................84 Table51Resultsofinterventiononnumberandrateofhospitaladmissionsperannumusingsimplifying assumptions....................................................................................................................................................85 Table52EstimatedimpactofInterventiononnumberofadmissionsperannum.........................................86 Table53EstimatesofNumberofadmissionsoneyearaftertheintervention,usingdifferences(Control-Test) .........................................................................................................................................................................87 Table54ResultsofregressionanalysisofLengthofStay(LOS)forBeforeandAfterintervention................88 Table55Resultsofinterventiononlengthofstay(LOS)perannumusingsimplifyingassumptions.............88 Table56Resultsofinterventiononlengthofstay(LOS)perannum..............................................................89 Table57EstimatesofNumberofadmissionsoneyearaftertheintervention,usingdifferences(Control-Test) .........................................................................................................................................................................90 Table58ComparativeMortalitydatausingdifferentdatasources................................................................91 Table59AgeDistributioninMasterRegistry..................................................................................................92 Table60AgeadjusteddistributionofDeathsovertheperiodofthetrial.....................................................92 Table61AgeadjusteddeathsofTestpatientsrelativetoBDMmaster.........................................................92 Table62Kessler10resultsatbaselineandfollow-up....................................................................................93 CSIROTelehealthTrialFinalReportMay2016 Page13of187 Table63EQ5Dresultsonbaselineandfollow-up(proportionoflevels1,2and3answers)..........................94 Table64HeiQresultsatbaselineandfollow-up.............................................................................................94 Table65MoriskyMedicationAdherenceresultsatbaselineandfollow-up..................................................95 Table66Patients’responsestothevideoconferencingquestionnaire.........................................................96 Table67CostofClinicalCareCoordination..................................................................................................105 Table68PowerCalculations.........................................................................................................................129 CSIROTelehealthTrialFinalReportMay2016 Page14of187 VI. ListofAbbreviations AB Asthmaticbronchitis ACT AustralianCapitalTerritories ADSL AsymmetricDigitalSubscriberLine ADSL2 AsymmetricDigitalSubscriberLine-2ndspecification AF AtrialFibrillation AHD Atheroscleroticheartdisease AMI AcuteMyocardialInfarction AP AnginaPectoris ART Arthritis ARV AnglicanRetirementVillages AST Asthma BT Bronchiectasis CAD CoronaryArteryDisease CCC ClinicalCareCoordinator CHD Coronaryheartdisease CHF CongestiveHeartFailure CM Cardiomyopathy CMU ClinicalMonitoringUnit COPD Chronicobstructivepulmonarydisease CSIRO CommonwealthScientificandIndustrialResearchOrganisation CVD Cardiovasculardisease DHS DepartmentofHumanServices DM DiabetesMellitus FTTP Fibretothepremises HREC HumanResearchEthicsCommittee HT Hypertension IHD IschaemicHeartDisease LHD LocalHealthDistrict MBS MedicalBenefitsScheme NBN NationalBroadbandNetwork NGO Non-GovernmentOrganisation NIBP Non-invasivebloodpressure NSTEMI Non-STelevationmyocardialinfarction CSIROTelehealthTrialFinalReportMay2016 Page15of187 PAS Patientadministrationsystem PBS PharmaceuticalBenefitsScheme PCEHR PersonallyControlledElectronicPatientRecord PHN PrimaryHealthNetworks PO ProjectOfficer QLD Queensland ROI ReturnonInvestment SEIFA Socio-EconomicIndexesforAreas STEMI STsegmentelevationmyocardialinfarction TAS Tasmania TMC Telemedcaretelemonitoringdevices/services T2DM Type2DiabetesMellitus VDSL Very-high-bit-rateDigitalSubscriberLine VIC Victoria CSIROTelehealthTrialFinalReportMay2016 Page16of187 1. ExecutiveSummary Thisprojectanalysesanddocumentstheeffectsofintroducingathometelemonitoringofvitalsignsforthe managementofaheterogeneousgroupofchronicallyillpatients.Patientssufferingfromawiderangeofchronic conditionswhowerefrequentlyadmittedtohospital,wereselectedfromnominatedhospitallists.Theimpactof telemonitoringwasanalysedusingawiderangeofhealthandwellbeingoutcomesaswellasnumeroushealth economicmetricsderivedfromMBSandPBSdataandhospitaldatausingtheHealthRoundtableformat.Data wasalsorecordedfromthetelemonitoringsystemusedinthetrial,andquestionnaires.Theimpactofthis interventiononthepatients,carersandcliniciansinvolvedintheircarewasquantitativelyandqualitatively analysedanddocumented. Inaddition,thisprojectreportsontheeffectofworkplacecultureandcapacityforinnovationandorganisational changemanagementinsuccessfullyintegratinganewmodelofcarewithlongestablishedservicemodels.We haveclearlydemonstratedthatthesuccessmetricsforthedeploymentoftelehealthservicesrelatemoretoonsiteclinicalleadership,capacitytoaccommodatechangeandtheflexibilityofexistingprocessesandsystemsthan anytechnicalissuesassociatedwiththetelehealthmonitoringequipmentorpatientadherencetomeasurement schedules. ThetelemonitoringsystemdeployedinthisstudywasdevelopedinAustralia,registeredwithTGA(Therapeutic GoodsAdministration)andhasbeenextensivelyusedandtestedinprevioustrials.Patientshadnodifficultyusing thetelehealthequipment,incorporatediteasilyintotheirdailylivesandtendedtomonitortheirvitalsignsand respondtoquestionnairesonaverageeverytwodays.Thisgeneratedauniquelongitudinalrecordofthepatient’s healthstatus,whichwiththeapplicationofsimplepredictiveanalyticscouldresultinthebettercoordinationof care,thereductionofunnecessaryhealthcarecosts,reducedhospitalisationandreducedlengthofstay. Highlightsoftheresultsobtainedinthispilotprogram,followingoneyearoftelemonitoringinclude; • • • • • • • 46.3%reductionsinrateofMBSexpenditure(savings$611-$657) 25.5%reductioninrateofPBSexpenditure(savings$44-$354) 53.2%reductionintherateofadmissiontohospital(reductionof0.22–1.0hospitaladmissions) 75.7%reductionintherateoflengthofstay(reductioninLOSof7.3–9.3days) >40%reductioninmortality >83%useracceptanceanduseoftelemonitoringtechnology >89%ofclinicianswouldrecommendtelemonitoringservicestootherpatients Theseresultsarebroadlyinagreementwithinternationaldata,buttheimpactonMBSandPBSexpenditurehas neverbeenreportedbefore. Aneconomicanalysisoftheimpactoftelehealthwasundertakenbasedontheresultsofthistrialandthe experienceofestablishingtelehealthservicesinsixdiversesitesinAustralia.Anoperationalmodelbasedona singleClinicalCareCoordinatormanaging100patientsisproposedinfuturelargescaledeploymentsof telehealth. Analysisofthismodelsuggeststhatforchronicallyillpatients,anannualexpenditureof$2,760couldgeneratea savingofbetween$16,383and$19,263pa,representingaReturnonInvestment(ROI)ofbetween4.9and6.0. ThenecessitytoalignthosewhopaywiththosewhobenefitinachievingashighaROIaspossiblesuggeststhat LocalHealthDistricts(LHDs)andthenewlyestablishedPrimaryHealthNetworks(PHNs)arewellpositionedto implementandmanagetelemonitoringservicesandclinicaltriagecallcentres.Clinicaltriageandmonitoring servicescouldthenbemadeavailableforallchronicallyillpatientsirrespectivewhethertheyareunderthecare ofaGP,acommunitynurseemployedbytheLHD,oracommunitynurseemployedbyaNon-Government Organisation(NGO). CSIROTelehealthTrialFinalReportMay2016 Page17of187 Fromasimpleanalysisofpopulationhealthdataweconcludethatapproximately750,000peopleagedover65[1] withcomplexchronicconditionsandmultipleco-morbiditieswhoareadmittedtohospitalatleastonceeachyear wouldbenefitfromathometelemonitoringoftheirvitalsignsandfromon-goingclinicalmonitoringandtriageof theirhealthstatus. CSIROTelehealthTrialFinalReportMay2016 Page18of187 2. IntroductionandBackground Inindustrializednationsapproximately70-78%ofhealthcarebudgetsarespentonthemanagementofchronic diseaseoritsexacerbation[1-3]andasthepopulationagestheburdenofchronicdiseasewillincreaseandplace healthcarebudgetsunderincreasingstrain.Asaconsequencepolicymakersandhealthservicemanagersseek innovationsthatdeliverthesameorimprovedhealthservicesusingproportionatelyfewerresources. Telehealthserviceshavebeendemonstratedtobeonesuchinnovationininternationalcontexts,butthereare lowlevelsofevidencefromAustralianstudies.Thisstudyevaluatedwhethertheintroductionofin-home telemonitoringservicestothemanagementofchronicdiseaseinthecommunitycouldreducepatientuseofthe healthsystemandimprovehealthcareoutcomesandtheirqualityoflife.Wealsoexploredtheextenttowhich real-timeriskstratificationofthesepatientswasofvaluetohealthprofessionalsandtheissuesandchallengesin deployingtelemonitoringservicesinthecommunity. Astrongprimaryhealthcaresystemhasbeenacknowledgedascriticaltothesustainabilityofhealthcaresystems bothindevelopingandindustrialisednationsandithasemergedasarecurrentthemeinAustraliainrecent years[4-6].Themanagementofchronicdisease,muchofwhichcouldoccurinhomeandcommunitysettings, unnecessarilyburdensAustralia’shospital-centricpublichealthsystem. Telehealthandtelecaretechnologiesandservicesforthemanagementofchronicdiseaseathomeandinthe communityhavebeenofintenseinterestindevelopedwesterneconomiesbecauseofunprecedentedgrowth ratesoftheagedpopulationandincreasingmorbidityaspopulationages.Thesefactorsplaceunsustainablestress onestablishedhealthcareservices,andwillresultinincreasingdeficitsinclinicalhumanresources,expanding diseasemanagementprogramsandpatientdemandforgreaterself-management. Telehealthservices,deliveredthroughhometelemonitoring,havebeendemonstratedtodelivercosteffective, timelyandimprovedaccesstoqualitycare[17-25].Theseservicesalsoreducesocialdislocationandenhancethe qualityoflifewithinandthesustainabilityofthesecommunitiesbyallowingchronicallyillandagedmembersto stayintheirhomesandcommunitieslonger. HoweverexperienceinAustraliawiththedeploymentoftelehealthservicesisextremelylimited,withmost deploymentsonsmallscaleandlackingdetailedanalysisofkeysuccessfactorssuchas: • • • • • • Healthcareoutcomes Healtheconomicbenefits Impactonclinicalworkforceavailabilityanddeployment Humanfactors(acceptability,usabilitybypatients,carers,nurses,GPsandadministrators) Workplaceculture Organisationalchangemanagementandbusinessprocesses Thedevelopmentofarobustbusinesscaseandbusinessmodelsforlargescalecommercialdeploymentof telehealthservices,basedonreliablesocio-economicevidence,isthereforeessentialiftheseservicesaretobe deployednationallytomitigatetheescalatingcostsofhealthservicedeliveryandtheincreasingdeficitinclinical workforce. Thistrialendeavouredtocreatearobustevidencebaseforthesekeysuccessfactorsanddemonstratean effectiveandscalablemodelforinternet-enabledtelehealthservicesinAustralia.Armedwiththeinsights providedbythisevidencebase,policymakersmayhavemuchofthedatatheyrequiretoimplementfunding modelsandcreateasustainabletelehealthservicessectorinAustralia. DespitelargenationalinvestmentsinhealthIT,verylittlepolicyworkhasbeenundertakeninAustraliain deployingtelehealthinthehomeasasolutiontotheincreasingdemandsandcostsofmanagingchronicdisease. IncontrastintheUK,thefirstreportfromtheDepartmentofHealth(DH)onthissubjectwaspublishedin2000[7] andmanyothershavefollowedsince[8-10]. CSIROTelehealthTrialFinalReportMay2016 Page19of187 TheDH’sPreventativeTechnologyGrant(PTG)from2006-08provided£80Mtolocalauthoritiesandtheir partnersforinvestmentinassistivetechnology[10]andmostrecently£31moffundingforaWholeSystem Demonstrator(WSD)programhadtelehealthasanintegralpartforthemanagementoflong-termconditions[1112] . 2.1 Evidenceofunsustainableincreasesinhealthcarecostsandinthedemandforhealthworkforce • • • • • HealthisnowthesecondlargestareaofgovernmentexpenditureandthelargestemployerinAustralia (ABS.2011CensusData). TotalHealthexpenditurehastrebledinthelast25yearsandin2011-2012was$140.241bpa,9.5%of GDP.Increasedspendingonpublichospitalservicesinrealtermswasthelargestcomponentofthe overallincreaseinspending,accountingforapproximatelyone-third(32.9%)oftheincreaseinthatyear [1]. FederalGovernmentaccountsfor42.4%ofallhealthcareexpenditurewith27.3%fromstateandlocal Governmentsand17.3%paidforbyindividuals.Healthinsurerscontributeapproximately8%[1]. Hospitals,doctorsandmedicinesdominateournationalhealthspendingprofile(2011-2012)data[1]. Pricesfordental,hospitalandmedicalserviceshaverisenmorestronglythanallconsumerpriceindex (CPI)thisdecade[16]asseeninFigure1. Figure1GrowthinConsumerPriceIndex(CPI)forHospitalandotherhealthservices[16] 2.2 Evidenceforageingdemographicsandtheincreasingburdenofchronicdisease InAustralia,theproportionofthoseagedover65willincreaseby68%,andthatofthoseover85willalmosttriple inthenext40years.Asthepopulationagestheburdenofchronicdiseaseincreases[13]. • • • • • • • Around80%ofGPconsultationsrelatetochronicdisease Patientswithachronicdiseaseorcomplicationsuseover60%ofhospitalbeddays Twothirdsofpatientsadmittedasmedicalemergencieshaveexacerbationofchronicdiseaseorhave chronicdisease Forpatientswithmorethanonecondition,costsaresixtimeshigherthanthosewithonlyone Somepeoplearehighlyintensiveusersofservices(10%ofinpatientsaccountfor55%ofinpatientdays) orveryintensiveusers(5%ofinpatientsaccountfor40%ofbeddays) HospitaladmissionsincreasewithageasshowninFigure2andlengthofstaylengthens,particularlyfor thosewithchronicconditionsandmultipleco-morbidities[13,15] Thebiggestandfastest-growingspendingcategoryinhealthishospitals-theygetalmost$18billionin realtermsmorethanin2002-03,anincreaseofover95%[15]. CSIROTelehealthTrialFinalReportMay2016 Page20of187 • • • • In2011–12,therewasa1.6%increaseinAustralianGovernmentfundingforpublichospitalservices comparedtoan8.0%growthinstateandterritorygovernmentfunding[1]. TreasuryprojectionsbasedondatafromtheAustralianInstituteofHealthandWelfare,withtaxheld constantasshareofGDPandbasedoncurrentarrangementsinplaceatthetimeofthe2010 Intergenerationalreport[p53of14],showthatstateandlocalexpenditureonhealthwillrepresent100% ofbudgetswithin30years[17]. Thereisanincreasingdemandfromthe“babyboomer”generationfortheexpansionofdisease managementprogramsandgreaterself-management. Thereareincreasingdeficitsinclinicalhumanresourcesparticularlyinruralandremotelocations. Figure2Separationsper1,000populationbysexandagegroup,allhospitals,2012–13 2.3 [15] Evidencefortelehealthservicesforthemanagementofchronicdisease TheWholeSystemDemonstrator(WSD)[11,12]intheUK,isthelargestrandomisedcontroltrialoftelehealthand telecareintheworld,involving6191patientsand238GPpracticesacrossthreesites-Newham,Kentand Cornwall.Threethousandandthirtypeoplewithoneofthreeconditions(diabetes,heartfailureandchronic obstructivepulmonarydisease(COPD))wereincludedintheTelehealthTrial. HeadlineFindingsreleasedbytheUKDepartmentofHealthinDecember2011,demonstrated; • 15%reductioninA&EVisits • 20%reductioninemergencyadmissions • 14%reductioninelectiveadmissions • 14%reductioninbeddays • 8%reductionintariffcostsand • 45%reductioninmortalityrates ThelargestexampleoftelehealthuseishoweverintheUS,wheretheVeteransHealthAdministration(VHA)has mainstreamedroutineuseoftelehealthforclinicalcarewithinitsCoordinatedCareandHomeTelehealth(CCHT) project[17].Analysisofdataobtainedforqualityandperformancepurposesfromacohortof17,025CCHTpatients showsthebenefitsofa25%reductioninnumbersofbeddaysofcare,19%reductioninnumbersofhospital admissions,andmeansatisfactionscoreratingof86%afterenrolmentintotheprogram.VHA’sexperienceisthat anenterprise-widehometelehealthisappropriateandcost-effectiveinthemanagementofchroniccarepatients inbothurbanandruralsettings.Morerecently,theUSDepartmentofVeteransAffairsannouncedthat690,000 CSIROTelehealthTrialFinalReportMay2016 Page21of187 USveteransreceivedcareinthe2014fiscalyearviatelehealth,with2milliontelehealthvisitsscheduled.That meansthat12percentofallveteransenrolledinVAprogramsreceivedtelehealthcareofsomekindin20141. Therearemanyclinicalbenefitsassociatedwithremotepatientmonitoringwithalargerangeofchronic conditions[16].SomeoftheevidenceforthiswassummarizedinarecentwhitepaperbytheMedicalTechnology AssociationofAustralia[18]andincludes(i)anincreaseinmeansurvivaltimeinasampleof387diabeticpatients whoundertookdailymonitoringofvitalsigns[19],(ii)asignificantimprovementinglycaemiccontrolindiabetic patientswhotransmittedbloodglucoseandbloodpressuredatatoatelehealthnurse[20],(iii)a71%reductionin EmergencyRoom(ER)admissionsinrespiratorypatientswhohadoxygensaturationmeasuredbypulseoximetry andmonitoreddaily[21],(iv)areductioninthenumberofhospitalreadmissionsinpatientswithangina[22],(v) significantimprovementsinhealthrelatedqualityoflifeandadecreaseinmortalityinCOPDpatientsusinghome monitoring[23],(vi)a43%reductioninhospitalizationsanda68%reductioninbeddaysofcareincardiacpatients whotransmitteddailyECGandbloodpressuredata[24]and(vii)a50%reductionintheriskofheartfailurerelated readmissionand55%reductionincardiovascularmortalityinchronicheartfailurepatientsmonitoredathome[25]. Theevidencethereforeappearsoverwhelmingthatathometelemonitoringcandeliversignificantpatienthealth benefitsatlowercostandwithahighlevelofacceptancebypatientsandtheircarers.Deploymentoftelehealth serviceshoweverisfarfromwidespread.Broadlyspeakingtelehealthserviceshasbeenembracedmost enthusiasticallyintheUSwithuptakeinAustraliaandtherestoftheWesternindustrialisednationspatchy, tentativeandonasmallscalerarelyproceedingpastthetrialstage. OutsideoftheUSA,theUnitedKingdomhasthemostevolvedinfrastructureandgovernmentpolicyframework forsupportingathometelemonitoring,andisnowpromotingaPublic-PrivatePartnershiptodeploytelehealth servicestothreemillionchronicallyillpatients.InAustralia,Governmenthasbeenpreoccupiedwiththefunding ofnationaleHealthinfrastructurethroughtheNationaleHealthTransitionAuthority(NeHTA)2,andwiththe developmentofthenationalPersonallyControlledElectronicHealthRecord(PCEHR)3whichisnowbeingslowly deployedandisreceivinglimitedacceptancefromclinicians. TelehealthvideoconsultationsbetweenspecialistsandpatientsinResidentialCareFacilitiesorremotearea communityhealthservicesarenowbeingfundedthroughtheMedicaresystem 4andatlastcounttheDepartment ofHumanServiceshadprocessedover169,000telehealthservicesprovidedtoover62,000patientsbyover9,700 practitioners. TheConsumerDirectedCareProgramwhichisreplacingtheexistingFederallyfundedcarepackagesknownas HomeandCommunityCarePackages(HACC),CommunityAgedCarePackages(CACP)andExtendedAgedCarein theHome(EACH),alsohasprovisionforthesupplyofathometelemonitoringservices. 1 http://mobihealthnews.com/37325/telehealth-served-12-percent-of-va-covered-veterans-in-2014 2 http://www.nehta.gov.au/our-work 3 http://www.health.gov.au/internet/main/publishing.nsf/Content/PCEHR-Review 4 http://www.mbsonline.gov.au/internet/mbsonline/publishing.nsf/Content/connectinghealthservices-factsheet-stats CSIROTelehealthTrialFinalReportMay2016 Page22of187 Withtheseinitiativesinplace,itisprobablethatAustraliawillbegintoimplementlargescaleathome telemonitoringservicesoverthenextfewyears.However,therearesignificantuncertaintiesandimpediments thatneedtoberesolvedbeforelargescaledeploymentoftelehealthserviceswillbecomeroutine.Theseinclude thefollowing: • • • • • • Concernoverfundingmodels.TheNationalHealthInsurancesystemhashistoricallyfundedprovider– patientclinicalconsultations.Thereareconcernsthattelehealthservicesmayleadtocostblowoutsin essentiallyuncappedfederalandstatehealthcarebudgets. StateandFederalGovernmentcostshifting.InAustraliatheFederalGovernmentfundsprimarycareand agedcareandtheStateGovernmentsfundhospitalservices.IftheFederalGovernmentfundstelehealth toreduceunnecessaryhospitalisationofthosewithchronicconditions,theprimarybeneficiarieswillbe thestategovernments.Hence,thereisapotentialmisalignmentofthosethatpayandthosethatbenefit! Limitedawarenessandsupportfortelehealthservicesbothamongclinicians,serviceprovidersand patients. VaryinglevelsoforganisationalreadinesswithinStateGovernments,localhealthdistrictsandnotfor profithealthserviceprovidersforthedeploymentoftelehealthservices. Alackofdataonhowtoidentifythosepatientsthatwouldbenefitmostfromathometelemonitoringfor theirchronicconditions,andarobustprocessforallocatingtelemonitoringresourcesthroughoutthe diseaselifecyclefromearlyinterventionforearlystagediseaseconditionssuchasType2diabetes, throughtocomplexchronicconditionswithmultipleco-morbiditiessuchascongestiveheartfailure(CHF) patientswithCOPDandcoronaryheartdisease(CHD). Arobustprocessforselectingcompetitiveathometelemonitoringservicesthatprovidethebestquality patientdataandopportunityforclinicaldiagnosis.Ensuringthatsystemsareinteroperableandstandards basedandcanautomaticallytransferdatasecurelytoeitherprovidercontrolledornationalelectronic healthrecords. Therefore,thisTelehealthTrialwasdesignedtoprovidearobustevidencebasewithwhichpolicymakersand healthservicemanagerscouldmakewellinformeddecisionsregardingthedeploymentoftelehealthservicesin anAustraliansetting. CSIROTelehealthTrialFinalReportMay2016 Page23of187 2.4 HighLevelProjectTimeLine FundingProposalsubmittedtoNBNEnabledTelehealthPilotsProgram(ITA274/1112) 16/05/2012 Title:HomeMonitoringofChronicDiseaseforAgedCare AnnouncementofsuccessfulapplicantsunderITA274/1112 15/12/2012 ContractssignedbetweenCSIROandCommonwealthDepartmentofHealth 18/02/2013 EthicsApprovalreceivedfromCSIROHREC 25/03/2013 RemovalofNBNrestrictionforpatientselectionandconnection 31/10/2013 Finalisationofcontractswitheachofsixtrialsites 01/03/2013to 22/05/2014 FirstTestpatientconsentedandmonitoringcommenced 29/05/2013 LastTestpatientconsentedandmonitoredcommenced 04/08/2014 DraftFinalReportsubmittedtoDepartmentofHealth 24/06/2014 DecommissioningofNepeanBlueMountainsMedicareLocalSite 01/07/2014 DraftReportsubmittedtoDepartmentofHealth 24/06/2014 FinalReporttobesubmittedtoDepartmentofHealth 27/09/2014 CompletionofmonitoringofTestPatients 31/12/2014 26/04/2016 DataanalysisandsubmissionofupdatedreporttoDepartmentofHealth CSIROTelehealthTrialFinalReportMay2016 Page24of187 3. AimsandObjectives Thisstudywasdesignedwiththeaimofdemonstratinghowtelehealthservicesforchronicdiseasemanagement inthecommunitycanbedeployednationallyinAustraliainarangeofhospitalandcommunitysettingsandto developadvancedmodellinganddataanalyticstoolstoriskstratifypatientsonadailybasistoautomatically identifyexacerbationsoftheirchronicconditions. TheanticipatedProjectOutcomesincluded: - Patientsdonotneedtotravelasregularlytoseehealthprofessionals Throughtimelyandbettercoordinatedcare,participantshavefewervisitstoemergencydepartments, reducedratesofhospitalisationsandotherclinicalevents Increasedcapabilityforpatientstomonitorandmanagetheircondition/sfromhome Healthprovidersdeliveringservicesmoreefficientlytoalargernumberofchronicallyillpatients ClinicalandhealtheconomicevidenceonhowNBN-enabledtelehealthservicescanbescaledup nationallytoprovideanalternativecosteffectivehealthserviceforthemanagementofchronicdisease inthecommunity Tomeasuretheoutcomesthefollowingresearchquestionswereaddressed; • • • • • • Effectoftelemonitoringonhealthserviceutilisation − Unscheduledvisitstohospital,visitstoGPsandNursevisits − Costandfrequencyoflaboratorytestsandotherclinicalprocedures Effectoftelemonitoringonpatientsoutcomes − Qualityoflife,progressionofchroniccondition,wellbeing,medicationadherence Serviceimplementationanddeployment − Existingmodelofcare,servicedesign,adoptionandappropriation Userexperienceandserviceimplementation − Satisfaction,useability,acceptance,workload,anxietyandstrainamongstudyparticipants includinghealthprofessionals,administrators,patientsandcarers Serviceimplementationissues − Howthenewhomemonitoringservicewasimplementedateachsite Whatimpacthasthishadontheprocessandoutcomesofnormalcaredelivery? − Howareexistingservicepracticesevolvingasaresultofthenewservice − Whatcanbelearntfromdifferentimplementationapproaches? Costeffectivenessanalysis − Analysisofreductions/increasesincostsbornebypatientsasaresultoftelehealth − Analysisofreductions/increasesincostsbornebythecommonwealthandonthegroundservice providersandpatientsasaresultofthedeploymentoftelehealthservices TheProjectObjectiveswereto: • DemonstrateanddocumenthowtelehealthservicescouldbesuccessfullydeployedacrossAustralia,by pilotingservicesinfivedifferentsettingsacrossfivestateswitharangeofhealthserviceprovider’s, includingLocalHealthDistricts,MedicareLocalsandnotforprofitcommunityorganisations. CSIROTelehealthTrialFinalReportMay2016 Page25of187 • • • • • • • • • • • Thiswasdemonstratedbydeployinganddemonstratingtheoperationoftelehealthmonitoringinamultisitemulti-statecasematchedcontroltrial(Before-After-Control-Impact(BACI)design)ofchronicallyill patientslivingintheirownhomesinthecommunity.Thishasneverpreviouslybeenattemptedin Australia. Demonstratetheclinicalandhealtheconomicevidenceonhowtelehealthservicescouldbescaledup nationallytoprovideanalternativecosteffectivehealthserviceforthemanagementofchronicdiseasein thecommunity. Patientselectionwasbasedonfrequencyofadmissiontohospitalforarangeofchronicconditions.This betterreflectsthepopulationhealthrealitiesofthehealthcaresystem. Provideevidencethatathometelemonitoringhasthepotentialtoreduceunscheduledadmissionsto AccidentandEmergency(A&E)comparedtothecontrolgroup. Provideevidenceforanimpactonhospitaladmissions,mortality,clinicaleventsandsymptomsand improvementsinfunctionalmeasuresandpatients'andcarers’experienceswithcare. Evaluatehealtheconomicbenefits Evaluateimpactonclinicalworkforceavailabilityanddeployment Evaluateimpactofhumanfactors(acceptability,usabilitybypatients,carers,nurses,GPsand administrators,impactonworkplaceculture) Evaluateimpactofworkplaceculture Evaluateimpactoforganisationalchangemanagementandbusinessprocesses Developanewevidencebaseddataanalyticaltechniquefortheriskstratificationofpatients’health statusdailyanddemonstratethatthisfacilitatesthemanagementoflargenumbersofpatientsby orchestratinganoptimalandtimelyallocationofresourcestoavoidunnecessaryhospitalisation DemonstrateconnectivitytoPCEHRdevelopmentsboththroughtheuseofMBSandPBSdatatotrack changesinTestandControlpatientoutcomesandbydemonstratinghowclinicalreportscanbe generatedfromathometelemonitoringdataandautomaticallyloadedtotheindividualpatient’sPCEHR record. Foreachoftheaboveobjectives,operationofthetrialatfivedifferentsitesrepresentingtwodifferentmodels, oneHospitalBasedandtheotherCommunitybased,forthemanagementofchronicdiseaseinthecommunity allowedtheidentificationandanalysisofsitespecificdifferencesinworkplaceculture,organisationalchange managementandstaffandmanagementcapabilitiesthatcontributetodifferencesinmeasuredhealth,social andeconomicoutcomes. Trialscope Casematchedcontrol(BACI)trialoffivesites(twositesintheNepeanBlueMountainsareawereultimately mergedintoasinglesiteforlogisticalreasons)infivestatesandTerritorieseachwith25testpatientsand50 controlpatientsinbothpublicandprivatehealthcaresettings. • • Deploymentandevaluationofstateofthearttelehealthtechnologyinthehomeforthemonitoringof vitalsigns,deliveryofclinicalquestionnairesandmessagingbetweenpatientsandcarers. Development,deploymentandpreliminarytestingofanewriskstratificationschematosupportnurse coordinatorsinorchestratingandoptimisingthedeliveryofcareonlyandwhenrequired,toachievethe besthealthcareoutcome. CSIROTelehealthTrialFinalReportMay2016 Page26of187 4. Methods 4.1 OrganisationCharts EstablishinganappropriateGovernancemodelformanagingsuchacomplexprojectiscriticalinordertocomply withtherequirementsoftheNationalStatementonEthicalConductinHumanResearch(2007)-UpdatedMarch 20145,thespecificrequirementsofmultipleHumanResearchEthicsCommitteesandthestatutoryrequirements oftheTherapeuticGoodsAdministrationregardingtheuseofmedicaldevicesformonitoringhealthstatus. TheOrganisationalstructureshownbelowinFigure3wasestablishedinApril2014.Clinicalgroupsmetona weeklybasisandwerechairedbytheProjectManagerortheClinicalTrialCoordinator.Thefourresearchteams alsometweeklytomonitorprogressagainstprojectmilestones.TheProjectManagementCommitteemet monthlytomonitorandreviewprogressoftheprojectagainstitsstatedaimsandobjectives.ThisManagement CommitteewasChairedbytheProjectDirectorandincludedrepresentativesfromeachsiteaswellastwo clinicians,onerepresentingtheinterestsofGeneralPracticeandtheother,ChairingtheAdverseEventsand DeathReviewcommitteewhichmetwhenevernecessary. Project Management Committee Project Management & Financial Control Project Director Project Manager Adverse Events & Death Review Committee Technical Project Committee CTC Site 1: Canberra ACT Site 2: Townsville QLD Site 3: Grampians VIC Site 4: Launceston TAS Site 5: ARV Penrith NSW Site 6: NBMML Penrith NSW Research Group 2 Data Architecture PO CCC PO Clinical Trial Information System CCC PO CCC PO Research Group 1 Clinical Trial Analysis Ethics, Security & Privacy Research Group 3 Data Analytics CCC PO CCC PO Research Group 4 Human Factors CCC Trial Sites Figure3Projectorganisationchart Notes: • • • • InAugust2014,NBMMLwasdecommissionedandpatientsfromthatsiteweretransferredtoARVin Penrithforongoingmonitoringandmanagement.Resultsforonlyfivesitesarethereforereportedinthis document. PO–ProjectOfficer,responsibleforpatientrecruitmentandallresearchrelatedtasksfortheproject CCC–ClinicalCareCoordinator,responsibleforclinicalmonitoringandmanagementofTestpatients CTC–ClinicalTrialCoordinator,responsibleforoverallmanagementofin-fieldactivities. 5 https://www.nhmrc.gov.au/guidelines/publications/e72 CSIROTelehealthTrialFinalReportMay2016 Page27of187 4.2 OperationalResponsibilities InAustraliahealthservicesaredeliveredthrougharangeofsectors,includingpublicsector(federal,state), privateforprofitornot-for-profitorganisationsandsometimesamixofthesesectors.Chronicdiseaseservices usuallyinvolvemultipleserviceproviders(e.g.,GPs,specialists,communitynursing,alliedhealthetc.)andrequire coordinationbetweenthesestakeholders.Coordinatedcareprogramshavebeenintroducedbyusingacentral worker(nursecoordinator)whocoordinateswithserviceproviderstodevelopacareplandedicatedtoindividual patientsandprovidesongoingfollow-uptothepatients.Patientswithchronicconditionsareusuallytriagedby assessmentcentresandassignedtodifferentlevelsofcareprogramsaccordingtotheirdiseaseseverities.These programscanrangefromhospital-basedtocommunity-basedandfromfederallyfundedtostatefunded. Partofthisstudy’sinterventioninvolvedtheintroductionofthenewroleoftelehealthnurseasaClinicalCare Coordinator(CCC)ateachsite.TheroleoftheCCCwastomonitoreachparticipant’svitalsignsandliaisewith GPs,specialists,andcommunitynurseswhomaybecaringfortheparticipant. AProjectOfficer(PO)wasalsoallocatedtoeachsiteandfullyfundedbytheprojecttomanageoperational activitiesforthestudyandtherebyseparatingpatientcarefromstudyoperations. ProjectOfficersandCCCateachsitehadthefollowingoperationalresponsibilitiesunderthecoordinationofthe CCC.Figure4showsdetailedoperationalresponsibilitiesandworkflowforprojectstaff. Figure4OperationalresponsibilitiesandworkflowsforProjectstaff CSIROTelehealthTrialFinalReportMay2016 Page28of187 4.3 SelectionofTelemonitoringService TheCSIROconductedacomprehensivetechnologyassessmentatarm’slengthfromthestudyteamtoselecta telehealthserviceproviderforthestudy.ParticipantsintheselectionpanelincludedseniorCSIROresearchand managementstaffandrepresentativesfrompartnerorganisations. TheTable1Table1belowliststheselectioncriteriaconsideredduringtheassessment. Table1TelemonitoringServiceSelectionCriteria # CRITERION DESCRIPTIONAND/ORSPECIFICREQUIREMENTS 1 Vitalsignmonitoring Mandatoryfeatures:ECG,heartrate,spirometry,non-invasive bloodpressure,oxygensaturation,bodyweightandbody temperature. Optional:Glucometry(integratedormanualentry) 2 Interactivefeatures Participant/clinicianvideoconferencingandmessagingfeatures. Supportforschedulinganddeliveryofclinicalandstudyspecific questionnairestoparticipants. Quality/easeofusebyparticipantsandclinicians. Multi-languagesupport. 3 Standardsandregulatory Approvalfromrelevantregulatorybodies,specificallyAustralia’s compliance TGAandpreferablyalsoEuropeanCEMarkandUSFDA. CompliantwithHealthInformationExchange(HIE)andHL7 standardsandService-orientedarchitecture(SOA)forWeb Services. 4 Clinicaldecisionsupport capabilities Abilitytoexportde-identifiedrawdatasignalsfromthesystemfor researchandanalysis. Expertsystemfordailypatientriskprofiling 5 Abilitytosupportthe study Demonstratedexperienceandparticipationintelehealthclinical trialsandresearchprojectsinAustralia AustralianbasedsoftwareandhardwareR&Dcapabilityand capacitytosupporttheresearchrequirementsoftheCSIRO. Combinedin-personandremotecustomersupportfortheonthe groundpatientsandclinicalteams Patient,clinicianandstudyteamtrainingcapability. Totalcostofequipment/servicesoverthelifetimeofthestudy. ThetechnologyselectionpanelselectedtheTeleMedCare6SystemsClinicalMonitoringUnit(CMU),depictedin Figure5onthenextpage,andassociatedclinicalwebservices,notingthatnotallfeaturesofferedbythedevice wereutilizedinthisstudy.Theselectionofthistelehealthsystemwasbasedonthefactorsbelow: 6 http://www.telemedcare.com/ CSIROTelehealthTrialFinalReportMay2016 Page29of187 • • • • • • Allvitalsignmeasuringdevicesarepartofthesystemminimisingissuesthatcanhappenbyhaving separatedevicesconnectingtoacentralunit TheentiretelehealthsystemtogetherwithmeasuringdevicesandsoftwareareTGAapproved Telehealthsystemhasnobatteryrequirementsastheunitismainspowered Noincompatibilityandcalibrationissuesgiventheunitisdesignedtoworktogetherwithallitsdevices Newversionwasassessedasbeingveryuserfriendlytooperate Allthesefactorsincludingthecostsfitwithinthetimeandbudgetofthetrial ThesitePOsandCCCsconfiguredthetelemonitoringsystemtoreflectclinicalbestpracticeforthepatient’s clinicalcondition.Typicallypatientswouldhavesomeorallofthefollowingvitalsignsmeasurementsscheduled ataconvenienttime,typicallyinthemorning; • • • • • • • NonInvasiveBloodPressure(NIBP)usingcombinedoscillometricandauscultatorytechniques Pulseoximetrytomeasurearterialbloodoxygensaturation SinglechannelECG,usingeitherthebuildinsurfaceelectrodesoracustomcableandclamps Spirometry,includingmeasurementsof; o VC–Vitalcapacity o PEF–PeakExpiratoryFlowRate o FEV1–Volumeexpiredinfirstsecond BodyTemperature Bodyweight(±100gmaccuracy) Glucometer–BGLbloodglucoseconcentration Inadditiontoscheduledtimes,patientscouldtaketheirvitalsignsatanytime.Afullsuiteofclinical questionnaireswasalsoavailable.ThesewerescheduledandadministeredbytheCCCs.TheTMCclinical monitoringunitalsopermitssecuremessagingandvideoconferencingbetweenpatientsandtheircare coordinators. Figure5TelemedcareClinicalMonitoringUnit(CMU) CSIROTelehealthTrialFinalReportMay2016 Page30of187 4.4 ClinicalTrialProtocol TheClinicalTrialProtocolreceivedclearancefrommultipleHumanResearchEthicsCommittees(Table2)andwas registeredwiththeANZClinicalTrialRegister7(ID364030). Thisstudywasdesignedasadichotomous,prospective,casematchedbefore-after-control-impact(BACI)trial with25interventionand50controlpatientsateachofsixsites.Thesiteswerewidelydistributedalongthe AustralianEasternseaboardasshownbelowinFigure6.TheInterventionwastheprovisionoftelemonitoring equipmentforthecollectionofvitalsignsandtheadministrationofquestionnaires.Controlpatientsreceived normalcare. Trialsiteswereoriginallyselectedonthefollowingcriteria: • • • earlyparticipationintherolloutofthefibre-to-the-premises(FTTP)NationalBroadbandNetwork(NBN); geographicallocationanddemographicprofile; variationsinmodelsofcareusedtomanagechronicdiseasetobegenerallyrepresentativeofthevariety ofmodelsofcareforthemanagementofchronicdiseaseexistinginAustralia. Criterion(i)wassubsequentlymodifiedtorelaxtheNBN-suppliedFTTPrequirementasaconsequenceofthe electionofanewCommonwealthgovernmentinSeptember2013. • • • • • • Site1:ACT-CanberraHospitaland ACTHealth Site2:QLD-TownsvilleandMackay MedicareLocal(TMML) Site3:VIC-BallaratandGrampians Site4:TAS-LauncestonHospitaland TNO Site5:NSW-ARVPenrith Site6:NSW-NepeanBlue MountainsMedicareLocal(NBMML) Figure6TrialsitesalongeasternseaboardofAustraliaandTasmania 7 http://www.anzctr.org.au/ CSIROTelehealthTrialFinalReportMay2016 Page31of187 InJuly2014,NBMMLwasmergedwithARVthusleavingfiveremainingsites.Ofthese,twoinTASandACT,were hospitalbasedwithaccesstospecialistnursesandmedicalregistrarsandtheremainingthreewerecommunity basedwithnormalcarebeingdeliveredprimarilybyGPsand/orcommunitynurses. Thehealthcaresettingsforthefivelocalorganizationsrangedfromhospital-based(ACT,TAS),MedicareLocal (QLD),andcommunity-basedatLocalHealthDistrict(VIC)toaprivateaged-careandhomecareorganization (ARV).Mostofthesiteshadexistingchronicdiseasemanagementprogramsofsomeform.TheACTteamhad workedonahometelemonitoringprogramforanumberofyearsbeforethistrial.Othersites(VIC,QLD)had somepriorexperiencewithothertelehealthapplications.ClinicalCareCoordinatorsatTASandACTwere physicallybasedathospitalsandworkedcloselywithmultidisciplinaryteamsconsistingofspecialistnurses, medicalregistrarsandstaffspecialists. Inthisstudyweanalysedandcomparedtheperformance,subjecttotheavailabilityofdata,acrossthreedistinct groupswithTASandACTashospitalbasedservices,QLD,VICandNSWascommunitybasedservices,compared tothetotalcohortofpatientsacrossallsites. EthicalapprovalwasobtainedfromtheCommonwealthScienceandIndustrialResearchOrganisation(CSIRO) Animal,FoodandHealthSciencesHumanResearchEthicsCommittee(ref#13/04,approvedMarch2013), AdelaideAustralia,andtheethicscommitteeforeachsite.ApprovaltoaccessMBSandPBSdatawasalso obtainedfromtheCommonwealthDepartmentofHealthandAgeingandtheDepartmentofHumanServices, CanberraAustraliaasshowninTable2below. Table2EthicsCommitteeApprovals ETHICSCOMMITTEE APPROVAL#,DATE. CommonwealthScience&IndustrialResearch Organisation(CSIRO) 13/04,25March2013. DepartmentofHealth&Ageing 25/2013,7August2013. NepeanBlueMountainsLHD LNR/13/NEPEAN/79,1July2013. TownsvilleMacKayLHD HREC/13/QTHS/56,7June2013. BallaratLHD HREC/13/BHSSJOG/29,27May2013. CanberraHospitalandACTHealth ETHLR.13.122,29May2013. TasmaniaNorthHealthService(LauncestonHospital) AcceptedCSIROHRECApproval 4.5 SelectionofParticipants Sincerandomselectionofpatientswasnotpossiblebecauseofsmallsamplesizesandtheinitialrequirementthat TestpatientsbeselectedfromareasconnectedtotheNBN,aBeforeAfterControlIntervention(BACI)designwas adoptedthatforegoesassumptionsofnormality.TheBACIpairedsamplesdesignprovidesgreatercontrolover confoundingvariables,increasesthepowerofthestudyandimprovesthechancesoffindingasignificantresult withasmallernumberofsamplesiftheimpactisrelativelysmall. Theresearchprotocolrequiredtherecruitmentof75participantsateachofthesixsitestoachieveatotalsample sizeof450.Ofthese150weretoberecruitedasTestpatientsand300Controlpatients.Ateachsite25 participantsweretobeallocatedtotheintervention,with50remainingcontrolparticipantsreceivingnormalcare aspertheirsite’sexistingmodelofcare. Eligiblecandidateswereidentifiedprimarilybysearchingthehospitalpatientadministrationsystem(PAS)for patientswhosatisfiedtheeligibilitycriteriadescribedinTable3.Somecandidateswerealsoidentifiedbysite clinicalstafffamiliarwiththeirmedicalhistory.Atotalof1430eligiblepatientswereidentifiedfromhospitallists providedbyACT(520),NSW(230),QLD(187),TAS(210)andVIC(282).PatientlistswereobtainedfromTownsville Hospital,CanberraHospital,NepeanBlueMountainsHospital,BallaratHospitalandLauncestonHospital. CSIROTelehealthTrialFinalReportMay2016 Page32of187 Candidateswereeligibletoparticipateinthestudyiftheymetallinclusionandnoneoftheexclusioncriteria listedinTable3andbecameparticipantsonthesigningofinformedconsentinthepresenceofanindependent witness. Table3Clinicalcriteriaforeligibility Criteria Type Description Age Inclusion 50yearsoldandoveratconsent. Cognitivecapacity Inclusion AbbreviatedMentalTest(AMT)[27]score>7. Unplannedacute admissions Inclusion Arateofunplannedacuteadmissionwiththerequiredprincipal diagnosiscode(s)indicatedbelow: a) >2inthelast12months,or b) >4intheprevious5years. ICD-10-AMprincipal Inclusion diagnosiscode(s)for eachunplanned acuteadmission Code(s)foreachunplannedacuteadmissionindicateadiagnosisfor oneormoreofthefollowingchronicconditions: Unsuitableconditions Exclusion Thestudyteamconsideredthepresenceofthefollowingconditions tobeunsuitableforparticipationinthestudy: a) ChronicObstructivePulmonaryDisease(J41–J44,J47andJ20, withsecondarydiagnosisofJ41-J44,J47), b) CoronaryArteryDisease(I20–I25), c) HypertensiveDiseases(I10–I15,I11.9.Note:Hypertensive HeartFailure(I11.0)isincludedinCongestiveHeartFailure), d) CongestiveHeartFailure(I11.0,I50,J81), e) Diabetes(E10-E14), f) Asthma(J45). a) Anyformofcancer, b) Anyneuromusculardisease c) Anypsychiatricconditions. Careteam Inclusion Theeligiblepatientsweretobeunderthecareofanyofthe following: a) Communitynurseand/or b) GeneralPractitioner Careprograms Inclusion Participationinoneofthefollowinggovernmentcareprograms: a) CommonwealthChronicDiseaseManagement b) CommonwealthCoordinatedVeterans’CareProgram c) NSWConnectedCareProgram Unsuitablecare programs Exclusion Participationinoneofthefollowinggovernmentcareprograms: a) CommonwealthExtendedAgedCareintheHome CSIROTelehealthTrialFinalReportMay2016 Page33of187 Forthepurposesofourstudyunplannedadmissionswerealladmissionsotherthan: 1. Admissionsfromthewaitinglist(includingboththesurgicallistandthemedicalwaitinglist); 2. Admissionslistedas"regularsamedayplannedadmissions"whichwereadmissionsthatwereintended regularandplannedsame-dayadmissionsforanon-goingphaseoftreatment,suchasrenaldialysisor chemotherapy. FollowingthesigningofaconsentformandcompletionoftheEntryQuestionnaire(see4.5below),Testpatients wereconnectedtotheinternetandsuppliedwiththeTMCtelemonitoringsystemandtrainedonitsusebythe PO.Theirvitalsignsweremonitoreddailyexceptonweekendsandquestionnaireresponses,recordedviathe TelemedcareCMU,weremonitoredasperscheduleinTable6bytheCCC.Onsitevisitsandtechnicalsupportas wellastheobtainingofConsentandtheadministrationofExitquestionnairesweretheresponsibilityofthePO. ControlpatientsalsocompletedtheEntryquestionnairebutotherwisecontinuedtoreceivenormalcare.Foreach interventionparticipant,sixcontrolcandidateswereautomaticallycasematchedongender,age,chronic conditionandSocio-EconomicIndexesforAreas(SEIFA)8.Ontheirconsentthetwoclosestmatchingcontrol candidatescommencedasparticipantsinthestudy.Theremainingfourcandidateswereheldinreserve.Table4 belowdemonstratesthecasematchingprocess. Generally,thecloserthematchthegreaterthelikelihoodoffindingasignificantresultwithasmallernumberof samplesiftheimpactisrelativelysmall. Table4ExampleofcasematchingofControlpatientswithTestpatients 1 TEST/CONTROL AGE GENDER MAJOR SEIFA DIAGNOSIS INDEXFOR POSTCODE STRENGTHOFMATCH PerfectMatch=0 TEST 54 M COPD 1023 CONTROL1 56 M COPD 1025 1.68 CONTROL2 54 F HD 1022 2.16 WEIGHTS 0.2 1 1 0.16 2 3 1 SEIFA2011Socio-EconomicIndexesforAreas. SEIFAprovidesmeasuresofsocio-economicconditionsbygeographicarea[25] 2 |54-56|x0.2+1x0+1x0+|1023-1015|x0.16=1.68 3 |54-54|x0.2+1x1+1x1+|1023-1022|x0.16=2.16 Ideally,asmanyasfourmatchesweresoughtforeachTestpatient,andtheclosestmatchwasthenselectedas thecasematchedcontrolforthatTestpatient.Inmanycasesonlyoneacceptablematchwasavailable. 4.6 QuestionnaireInstruments Anumberofquestionnaireinstrumentsweredevelopedoradaptedfromtheliteratureforuseinthetrial.All patientsenrolledinthestudywererequiredtotakeanEntryandExitQuestionnaire.Thisquestionnaire instrumentwasdevelopedfromabaseCSIROCAFHSHumanResearchEthicsStandardScreeningMedical Questionnaire9withtheadditionofotherquestionnaireinstrumentseitherwhollyorinpart,measuring demographic,lifestyle,healthanddiseasecharacteristics.KeyelementsoftheEntryandExitQuestionnairesare describedinTable5below. 8 http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa http://my.csiro.au/Support-Services/Human-Research-Ethics-in-CSIRO/Health-and-Medical-Research-Ethics/Human-Research-Ethics-Committee.aspx 9 CSIROTelehealthTrialFinalReportMay2016 Page34of187 Table5KeyelementsoftheEntryandExitQuestionnaires Section 1-3 Source/Questionnaire CSIROStandardScreeningMedicalQuestionnaire7+additionaltrialspecific questions ‡SelectedquestionsfromLivingwithDiabetesStudy[28] ‡SelectedquestionsfromFatandFibreBarometer[29] 4 ActiveAustralia[30] 5 Kessler10[31] 6 DimensionsfromHeiQ(Livingwithandmanagingmedicalconditions)[32] 7 EQ-5D[33] 8 DimensionsfromHeiQ(SocialIsolation)[32] 9 MoriskyMedicationAdherence[34] InadditiontothePointofEntryandExitquestionnaire,anumberofquestionnaireswerescheduledand administeredtoTestpatients(andcaregiverswhenapplicable)duringthetrialwithvaryingfrequency.Theseare describedinTable6below.Auserquestionnairewasalsoadministeredtocliniciansattheendofthestudy. Table6QuestionnaireInstrumentsandtheirschedule QUESTIONNAIRE COPD(DevelopedbytheAustinHospital) CHF(DevelopedbytheAustinHospital) *EQ-5D(Qualityoflife)] *Kessler10(Mentalhealth) *heiQ–selecteddomains(Self-monitoring,Healthservices navigationandSocialisolation) *MoriskyMedicineAdherenceScale CaregiverStrainIndex[35](administeredtopatient caregiver) AbbreviatedMentalTest[27] UseracceptanceandSatisfaction(topatient)[36] UseracceptanceandSatisfaction(toclinicians)[36] ADMINISTERINGSCHEDULE Daily Daily Weekly Monthly Entry,6months,Exit Entry,6months,Exit Entry,6months,Exit Atconsent 6monthsandatexitofstudy Atendofthestudy *ThequestionsfromthesequestionnaireswerealsoincludedintheParticipantPointofentryand-Exit QuestionnaireswhichwereadministeredatentryandexitbythePOandthroughtheTMCmonitoringdeviceat6 months.InsomecasestheExitquestionnairewasadministeredtoTestpatientsthroughtheTMCdevice. TheschedulingforthesequestionnaireswassetintheTMCsystembythePO,afterliaisingwiththeCCCon diseasespecificquestionnaires(COPDandCHF).Allfrequentlyadministeredquestionnaires,suchastheCOPD andCHF,EQ5DandK10questionnaireswerescheduledandadministeredtoTestpatientsthroughtheTMC monitoringdevice. 4.7 AdditionalInformationonEntryandExitQuestionnaireInstruments Asmentionedin4.6,theinstrumentslistedinTable7belowwereusedintheEntryQuestionnaireadministered toallTestandControlpatients.Table7providesadditionalinformationonthemeasuresandscoresusedinthe trial.TheEntryQuestionnairewasadministeredtoTestparticipantsatthetimeofdeploymentoftheirTMC telemonitoringdevice.InmostcasesdatawereentereddirectlyintotheOpenClinicaportal,anopensource clinicaltrialsoftwareforelectronicdatacaptureandclinicaldatamanagement. CSIROTelehealthTrialFinalReportMay2016 Page35of187 Howeverinsomecasestheresponseswerecollectedonpaperandthenenteredinthedatabaseatalatermore convenienttime.Thiswasmainlyduetotimelimitationsatthepatients’homesespeciallywhenthe telemonitoringdeviceinstallationtookabitlongerthanusual(configurationissuesorothertechnicalissues). Table7EntryQuestionnaireinstrumentsandtheirinterpretation Domain Demographic information Behaviour information Physical Activity Psychosocial functioning Questionnaire CSIRO Demographics Questionnaire+ additionaltrial specificquestions Measure Gender,Age,weightand height(BMI),occupation, maritalstatus,income, computerskills,social mediaandNBN connectivity Selectedquestions 12questionsrelatingto fromLivingwith alcoholintake,tobacco DiabetesStudyand smoking,fruitand FatandFibre vegetableconsumption, Barometer meatandfish,fibre,fat andsaltintake ActiveAustralia ParticipationinleisureSurvey timephysicalactivity Kessler10(K10) Livingwith Dimensionsfrom andManaging HeiQ Medical Conditions; SocialIsolation MeaningofScore Individualandcodedscores Individualandcodedscores <150min/week: insufficientlyactive ≥150min/week:sufficiently active 10questionsassessinghow Score10-50;10defines apatienthasbeenfeeling patientnotexperiencing inthelastfourweeks feelingsofdistressand50 beingseverelevelof distress • Score<20arelikelyto bewell • Score20-24arelikely tohaveamildmental disorder • Score25-29arelikely tohavemoderate mentaldisorder • Score30andoverare likelytohaveasevere mentaldisorder 16questionsrelatingto Equally-weightedtotal livingwithandmanaging scoresonallheiQsubmedicalconditionsand5 domainsarecalculatedand questionsrelatingtosocial re-scaled(totalscoresof isolation thequestionsdividedby theNoofthequestions)to rangefrom1.0to4.0. Higherscoresrefertoselfreportsofmorepositive effectofaselfmanagementprogram CSIROTelehealthTrialFinalReportMay2016 Page36of187 Domain QualityofLife Questionnaire EQ5D †Medication adherence Morisky Medication AdherenceScale Measure Scoresderivedfrom responsestofivegeneric questionsonhealthstatus • mobility • self-care • usualactivities • pain/discomfort anxiety/depression VASrecordsrespondent’s self-ratedhealthona vertical,visualanalogue scale(0-100)wherethe endpointsarelabelled ‘Bestimaginablehealth state’and“Worst imaginablehealthstate Eightitemself-reportscale onmedicationadherence MeaningofScore ResultspresentedasIndex (Australian)VASpresented asnumberfrom0-100with 0theworstand100the bestimaginablehealth state Lowadherence(<6), Mediumadherence(6to <8),Highadherence(=8) ForControlparticipants,theEntryQuestionnairewasadministeredafterwrittenconsenttoparticipateinthetrial wasobtainedduringafacetofacemeetingwiththePO. 4.8 UseofFocusGroups,StructuredinterviewsandQuestionnaires Amulti-methodapproachwasadoptedforthestudyofimplementation,useracceptabilityanduseability.Table8 summarizesstudymethods,participantsanddatacollectedandincludedinthisreport. Table8Researchmethodsforevaluatinguseabilityandacceptabilityoftelehealthservices METHODS STUDYPARTICIPANTS Questionnaire Patient satisfaction and Alltestpatients acceptance (at six-month and twelve-month time points) Clinician satisfaction and AllCCCsandPOs acceptance(endofthetrial) Patient declining withdrawing Semistructured interview DATACOLLECTED Questionnaire at six-month and at exitofthestudy Endoftrial or Patientswhodonotcommence At point of refusal orcompletethetrial orwithdrawal Duringthefirstphaseofthe CCCs and POs of 6 sites Interview trial(Aug-Sep2013) (including managers at some transcriptions sites) Ongoing implementation CCCs and POs of 6 sites (Dec2013) (including managers at some sites) During field studies (Oct Study participants of “Field 2013, Mar-Apr 2014, Aug study” 2014) CSIROTelehealthTrialFinalReportMay2016 Page37of187 METHODS Fieldstudy and interviews STUDYPARTICIPANTS Around six-month time point of telemonitoring at foursites: TAS(Oct2013) VIC, ACT, Old (Mar-Apr 2014) NBM,ARV(Aug2014) POsandCCC’s Recordedsuccessstories notes andissuesas“Observation andStory”inCSIROportal DATACOLLECTED CCCs and POs of 6 sites (including managers at some sites); TwoGPsandoneGPgroup(one GP per site at VIC and Qld; a groupofeightGPsatTAS) 2patientsandapatientgroup(1 patient and 1 carer per site at VIC, Qld, ACT; a group of 8 patientsandtheircarersatVIC) Notes;Reports; andInterview transcriptions; POsandCCCsof6sites Descriptionsof observationsand issues 4.9 DataModels Asdescribedearlier,patientdatawereobtainedfrommultiplesourcesandintegratedintoasingleunified databaselinkedviatheuniqueOpenClinicaID(OCID).ADataModelwasdevelopedwhichprovidedthetemplate fordataanalysisbylinkingoutcomesandobjectivestospecificdatavariablesandidentifyingthedatasources. Thisdatamodelunderpinnednearlyallquantitativeanalysispresentedinthisreport.Thedatamodelispresented belowinTable9. Table9DataModelforevaluatingoutcomesandobjectives OUTCOME/OBJECTIVE DATAVARIABLE DATASOURCE CONFIRMATIONOF SELECTIONCRITERA Admittedtohospitalfortheir conditionatleasttwiceinthe previousyear,or>4timesin previousfiveyears HospitaldatainHealthRoundtable format-obtainedfromlocal hospitalforpreviousfiveyears. • Dateadmitted • Datedischarged • Reasonforadmission (ICD9/10Codes) • Procedurescarriedout REDUCEDHOSPITALISATION NumberofUnscheduled admissionstohospitalfortheir condition MBSFlag(InHospital)datain HealthRoundtableformat • Dateadmitted • Datedischarged • Reasonforadmission (ICD9/10Classification) • Medicationadministered • Procedurescarriedout REDUCEDUSEOFCLINICAL SERVICES MBSrecords MBSrecords Numberofvisitsto/byGP Numberofvisitsto/byspecialists CSIROTelehealthTrialFinalReportMay2016 Page38of187 OUTCOME/OBJECTIVE DATAVARIABLE DATASOURCE (ImpactonClinical Workforceavailabilityand deployment) Numberofvisitsbycommunity nurse Numberofvisitsto/byallied health (ieoccupationaltherapist) Changesinprescriptionhistory CommunicationwithCCC MBSrecords MBSrecords (IfreimbursablefromMedicare) PBS CCCLogsfromCSIROPortal ORGANISATIONALCHANGE MANAGEMENTAND IMPACTONWORKPLACE CULTURE Administrative/operational changesimplemented/requiredin ordertoimplementthetelehealth service. Questionnairesandstructured interviews. • Withinfirstthreemonths • Everysixmonthsthereafter USEABILITYOF MONITORINGEQUIPMENT Compliancewithmonitoring schedule,recordeddaily. Extrameasurementstakenby patient(When?Which?) Compliancewithquestionnaire administration(When?Which?) UseofVideoconferencing Overalldatausage TMCLogs TMCLogs TMCLogs TMCLogs iiNETprovidedlogs USEABILITY/ACCEPTABILITY FORPATIENTSOF MONITORINGEQUIPMENT EaseofUse QuestionnairesdeliveredviaTMC Qualityoftrainingreceived • Midpointoftrial Patientembarrassmentifvisitors • Atendoftrial knowtheyarebeingmonitored Acceptabilityasanitemof furniture Easyorhardtotakemeasurement Important/NotImportantin patients'self-management ResponsivenessofClinicalCare Coordinatorinrespondingto changes CARERSEXPERIENCEWITH TELEHEALTH (CommunityNurse/Carer) Easeofuseof(i)equipmentand (ii)Clinicianwebsite Changestopreviousclinical modelsofcare Effectivenessinimprovingability todelivercare Impactonworkload Questionnairesandstructured interviewsofCommunityNurses • Atendoftrial EffectonCarerstress Effectoncarerworkload Effectivenessinimprovingability todelivercare Questionnairesandstructured interviews • Midpointoftrial • Atendoftrial CARER'SEXPERIENCEWITH TELEHEALTH (Relativeorothercarer) CSIROTelehealthTrialFinalReportMay2016 Page39of187 OUTCOME/OBJECTIVE DATAVARIABLE DATASOURCE GPEXPERIENCEWITH TELEHEALTH Easeofuse Changestoclinicalmodelsofcare Effectivenessinimprovingability todelivercare Impactonworkload Questionnairesandstructured interviewsofPatients'GP • Within3monthsoffirst deployment • Midpointoftrial • Atendoftrial USEABILITY,ACCEPTABILITY OFCLINICIANWEB INTERFACE EaseofUse Qualityoftrainingreceived Howmanyhoursrequired ValueandeaseofuseofVideo conferencing QuestionnairesdeliveredviaTMC • Onemonthafterfirst deployment • Midpointoftrial • Atendoftrial HEALTHECONOMIC OUTCOMES Dailycostofhospitalisation Costofprocedurescarriedout whilstinhospital Costofvisitsto/byGP Costofvisitsto/byAlliedHealth (ieChiropodistorOT) CostofvisitsbyCommunityNurse /Carer CostoftraveltoGP Lossofearningsifpatientwasstill employed,fromdaystakenofffor illnessorvisitstohealth professionals HospitaldatainHealthRoundtable format HospitaldatainHealthRoundtable format MBSData MBSData MBSData MBSData UseGoogleMapstodetermine distancetravelledfromhome addresstoaddressofservice location,thenapplystandard costingmodel.Ieflagfall+km charge Estimatefrompatientsalaryand timespentoneachvisit COSTOFDELIVERING TELEHEALTHSERVICES CostofClinicalCareCoordinator(s) CostofClinicalNurses/Carers Costofprovidingnetworkservices Costofprovidingtelehealth monitoringservices Depreciatedcostsofcapital equipment Estimateofcostofspacefor monitoringcentreateachsite Healthserviceproviderandlogs recorded Healthserviceproviderandlogs recorded iiNETbillingatcommercialrates TMCcommercialdailysubscription costs Ourownprojectrecords EstimatesfromHealthservice Provider CSIROTelehealthTrialFinalReportMay2016 Page40of187 4.10 MethodologyforDataAnalysis Thisprojectwasdesignedtointegratedatavitalsignsandquestionnaireresponsesfromthetelemonitoring devicesdeployedtoTestpatientswithquestionnairedataadministeredtoTestandControlpatientsaswellas PBS,MBSandhospitaldataobtainedforbothTestandControlpatients.Detaileddataanalysiswascarriedout primarilyonthe100Testand137Controlpatients(ReferSection5.1.2forfinalpatientnumbersincludedinthis analysis),butthisgroupwasalsobesubdividedaccordingto(i)primarydiagnosis(Cardiac,Respiratoryor Diabetes)(ii)whethermonitoringwascarriedoutinhospitalorcommunitysettingsor(iii)bysite(QLD,NSW,ACT, VICandTAS).Considerationwasgiventothesizeoftheresultingcohortandthereliabilityandpublichealthvalue oftheresultinganalysis. PrimaryanalysiswascarriedoutontheimpactoftelemonitoringontotalMBSandPBSexpenditureaswellason numberofadmissionsandlengthofstay.InAppendix8.3,theseanalysesareextendedusinganumberof methodstoindividualparameterssuchasnumberandcostofGPvisits,numberandcostofvisitstospecialists andnumberandcostoftestsandproceduresprescribed. Itwasquicklydeterminedthatmostdatawastimevarying,asonewouldexpect,giventhatmanyhealthrelated eventsandcostsincreaseaspatientsage.Theimpactoftelemonitoringonthetrajectoryoftheseincreasesis thereforeofparticularinterest,anditbecameessentialtomodelthesechangesusingavarietyofBeforeand AfterControlIntervention(BACI)timevaryinganalysismethodssuchaslinearregressionsagainsttime,linear mixedeffectsmodellingandcumulativesumsofdifferences. Baselinecharacteristicsaredescribedfortimeintervalsasmean±SDsforcontinuoussymmetricalvariablesand meansand95%ConfidenceIntervals(CI)forskeweddata.Confidencelimitswerecalculatedaccordingtothe methodofZou,TalebanandHuo[41].Allstatisticaltestsaretwo-tailedmatchedpairt-Tests,andapvalueof< 0.05wasusedtoindicatestatisticalsignificance.StatisticalanalysisisperformedusingStataReleaseV.12(TX: StataCorpLP),SPSS17,MATLABandMicrosoftExcel. TheresultsoftheseanalysesonprimaryparameterssuchasQuestionnaireData,MBSandPBScosts,aswellas numberofhospitaladmissionsandlengthofstayarepresentedinChapter5withamorefinegrainedanalysis undertakenonindividualsitesandspecificsecondorderparameters,presentedinAppendix1. Questionnairedata Baselinecharacteristicsaredescribedforbothgroupsusingmean±SDsforcontinuoussymmetricalvariablesand mediansand95%CIforskeweddata.Categoricalvariablesarepresentedascountsandpercentages. Comparisonsismadebetweenthetwogroupsatbaselineusingthecasesavailable.Theχ2test(orFisher’sexact test)isusedforcategoricalvariables,thetwo-samplet-testforcontinuousvariablesandtheWilcoxonrank-sum testforskewedvariables.Within-groupdifferencesfrombaselinetolastpointareexaminedusingthepairedttestforsymmetricaldataandtheWilcoxonsigned-ranktestforskeweddata. Allstatisticaltestsweretwo-tailed,andapvalueof<0.05wasusedtoindicatestatisticalsignificance.Statistical analysiswasperformedusingStataReleaseV.12(TX:StataCorpLP),SPSSv17andMicrosoftExcel. CSIROTelehealthTrialFinalReportMay2016 Page41of187 PBS,MBSandHospitaldata RawdatawerereceivedfromnumeroussourcesasshowninFigure7,typicallyasEXCELspreadsheets. EntryandExit Questionnaires Questionnaires OpenClinica DataBase MBSData Daily&Weekly Questionnaires TMCServer DataBase PBSData DataBase HIEandBusiness ProcessData Telemonitoring VitalSignsData HealthRoundTable HospitalRecords TMCServer Data Base Data Base RecordedEvents inPortal DATAINTEGRATIONENGINE SECURECLOUDSERVER AUTHORISEDRESEARCHERS Figure7Schematicdiagramofdifferentdatasourcesandtheirsecureintegration Onreceiptofrawdata,thefileextensionwascheckedandifinEXCELformat,thefilewasconvertedtoCSV (Comma-SeparatedVersion)format.TheconversionwasdonebyopeningtheexcelfileinMSExcelxxx.xlsxand savingitasxxx.cvs.OncethedatafilewasintheCVSformat,thenextstepwastoinsertitintoarelational database.Todothis,atablestructurewithitsattributeswasdefined.Theattributeswerebasedonthecolumns intheCSVfile.Onceatablestructurewasdefined,itwascreatedinsidetheMySQLdatabaseusingthesql command. Oncethetablewascreated,theCSVdatawasportedintothedatabasetable,usingtheMySQLloadinfilefunction whichallowedthedatatobepopulatedinsidethedatabasetablewithouthavingtowriteasinglelineof programmingcodebutsimplyusingascript. Oncedatawasinthedatabase,variousSQLquerycommands(e.g.,select,update,delete)wereusedtoproduce variousresultsrequiredforreports.Tofacilitatethis,theMySQLworkbench,aclientapplicationthatconnectsthe backenddatabaseandretrievesthedatafromthedatabasetableaccordingtoSQLquerieswasused.Theresults weresavedasCSVfileswhichcouldbeopenedinMSExcel. Togeneratevariousgraphsaccordingtothequeryresults,eitherbuilt-inExcelgraphfunctionwereusedorVisual Basicprogrammingwasusedifthegraphwascomplex.StatisticalanalysiswasperformedusingStataRelease V.12(TX:StataCorpLP),SPSS,R,MATLABandMicrosoftExcel. CSIROTelehealthTrialFinalReportMay2016 Page42of187 PBS,MBSandHospitaldatawereallsynchronisedtothedatewhenthetelemonitoringcommenced.AsTest patientswereconnectedtotelemonitoringequipmentoveraperiodofmonths,synchronisingtothedate monitoringbeginshadtheaddedadvantagethatseasonaleffectswereaveragedout.PBS,MBScostsforevery patientwereaveragedover30dayperiods,typicallyfor36x30dayperiodsbackfromdateofconnectionand12 x30daysforward.Thisapproximatedtoanalysingdataoverthreeyearsbeforeandoneyearafterthe intervention.InAppendix8.3,wepresentBACIlmemodellinganalysiswhereseasonalvariationswerespecifically considered. Hospitaladmissionsdataandlengthofstayweresimilarlytreated,exceptthatthetimeintervalchosenwas100 days.Thiswasapreferredintervalashospitaladmissionsweremuchlessfrequentandwouldgeneratedatawith alargenumberofzeroentries.Similarly,12x100dayperiodsbackfromthetimeofconnectionand4x100day forwardswereanalysed. PBS,MBSandHospitaldatawereanalysedastimeseries,wheredataacrossalltestpatientswereaveragedover eachtimeperiodandplottedbeforeandafterthetimeofintervention.Normalityofdatawastestedineachcase andwherenecessarysqrtorLogNormaltransformswereapplied.Thetimeseriesbeforeandafterintervention weretheninvestigatedusinglinearregressionandAnalysisofCovariancemethods.Beforeandafterdatawere analysedbothasbeingseparatelineswithdifferentslopesorthesamelinehavingthesameslope.ANCOVAwas thenappliedtotestwhethertheslopesaresignificantlydifferentatthe95%confidencelevel. Thisanalysiswasappliedto(i)Testpatientdata(ii)Controlpatientdataand(ii)Difference(Control-Test)data. ThesetimeseriesanalysespermittedthedeterminationofhowwellTestpatientsandControlpatientswere indeedmatched,controlledforpossibleeffectsoftheinterventiononControlpatientsandbyanalysing differences,eliminatedpossibleseasonalandotherpossibletimevaryinginfluences. CSIROTelehealthTrialFinalReportMay2016 Page43of187 5. Results Thiscomplexandambitiousprojectenvisagedtherecruitmentof25Testpatientsateachofsixsites,consented andmonitoredforaperiodofoneyear,withanother50casematchedcontrolpatientstrackedoverthesame period.Onegroupwasdecommissioned,whichresultedinatargetcohortof125Testpatientsand250Controls Attheend,notingthecomplexityofmountingaclinicaltrialacrosssixsitesandfivestatesandTerritories,with differentworkplaceculturesanddifferentcapacityfororganisationalchangemanagement,wewereableto achievethefollowingresults; Total enrolled n=287 Test Group n=114 Control Group n=173 Figure8FinalcohortofTestandControlpatients 5.1 PatientrecruitmentofTestandControlPatients Thetrialdesignrequiredthatpatientsateachsitebeselectedfromalistofeligiblepatientsprovidedbythe majorpublichospitalatthatsite.CanberraHospitalandACTHealth,NepeanBlueMountainsLHD,Townsville MackayLHD,LauncestonHospitalandBallaratHospitalallprovidedlistsfromwhichTestandControlpatients couldbeselected. Ourtargetnumbersweretorecruit25Testpatientsandtheir50matchedControlpatientsateachofthesixsites selected.Asonesitewasdecommissionedduetoslowenrolment,andmergedwithanother,ourfinaltargetwas torecruit125Testpatientsand250ControlPatients.Ultimatelywerecruitedandconsented114TestPatients and173ControlpatientsasshowninFigure8,butoftheseonly71Testpatientsand110Controlpatientswere fromthehospitallistsprovided. ThemajorityofpatientsNOTonthehospitallists,wereeitherfromVICorNSW.InVictoriapatientsfromthe DjerriwarrhHealthServices,wouldprimarilybeadmittedtoBacchusMarsh&MeltonRegionalHospitalrather thanBallaratHospital.IntheNepeanBlueMountainsarea,mostpatientswereconsentedbyARVandwerenot necessarilyontheNepeanBlueMountainsLHDlist.Ineverycasehowever,localPO’swouldensurethatpatients recruitedintotheprojectwereeligibleforinclusion Theresultsofrecruitmentof114Testpatientsandconsenting173ControlpatientsisdescribedinTable10 below. CSIROTelehealthTrialFinalReportMay2016 Page44of187 Table10Patientdemographicsandrecruitmentateachsite Eligiblepatientsfrom Hospitallistsprovided Patientsconsented Patientsconsented,didnot commence PatientsConsentedfrom Hospitallists Patientsconsentedfrom outsideHospitallist AllPatientsConsented Age (SD) NumberofMalepatients Age (SD) NumberofFemalepatients Age (SD) TAS ACT HospitalBased VIC NSW CommunityBased QLD TOTAL 210 282 230 187 1429 520 T C T C T C T C T C T C 5 5 10*(4) 5 3(1) 23 29 56 16 22 0 1 7 4 19 27 71 110 - 4 - 1 26 48 10 8 7 2 43 63 29 69.4 (9.0) 18 69.5 (10.1) 11 69.2 (7.3) 60 72.8 (9.7) 35 73.3 (9.7) 25 71.9 (9.8) 16 70.7 (8.2) 11 70.5 (7.6) 5 71.0 (10.2) 23 73.7 (8.6) 14 72.6 (7.2) 9 75.4 (10.7) 26 69.7 (7.6) 19 70.3 (7.8) 7 68.0 (7.5) 49 68.9 (8.8) 24 70.2 (8.4) 25 67.5 (9.2) 17 77.3 (9.1) 9 76.0 (7.3) 8 78.7 (11.1) 12 71.0 (12.9) 7 66.4 (12.8) 5 77.4 (11.2) 26 70.5 (10.7) 16 69.9 (8.9) 10 71.5 (13.7) 29 114 173 74.1 71.1 71.9 (8.5) (9.3) (9.4) 17 73 97 74.3 70.8 72.1 (8.6) (8.6) (9.2) 12 41 76 73.9 71.6 71.7 (8.6) (10.4) (9.9) *agreedtobecontrols MatchedControlpatientsweretobeideallyrecruitedandconsentedassoonaspossibleafterTestpatientswere recruited,butasControlpatientsdidnotreceiveanyintervention,theirhealthstatuscouldberetrospectively trackedfromMBSandPBSDataandhospitaldataoverthesametimeperiodastheTestpatientswere monitored. 60 120% 70 120% 50 100% 60 100% 80% 50 40 30 60% Frequency Frequency Thetimecourseofrecruitingandconnecting114Testpatientstothetelemonitoringequipmentandof consenting173ControlpatientsareshowninFigure9below. 80% 40 60% 30 20 40% 10 20% 10 20% 0 0% 0 0% 40% 20 CommencementofMonitoring Figure9Timecourseof(a)connecting114Testpatients,and(b)consenting173ControlPatients CSIROTelehealthTrialFinalReportMay2016 Page45of187 Reasonsfordecliningorwithdrawingfromthestudy AsdescribedinSection4.4,potentialeligiblecandidateswereidentifiedprimarilybysearchingthehospital patientadministrationsystem(PAS)forpatientswhosatisfiedtheeligibilitycriteriaasdescribedinTable3.Some candidateswerealsoidentifiedbysiteclinicalstafffamiliarwiththeirmedicalhistory. ItwastheroleofthePOtocontactparticipants,confirmeligibility,provideinformationandtoenquirewhether eligibleindividualswereinterestedandwillingtoconsentto,andparticipateinthetrial.Outcomesofthe recruitmentprocessarereportedasfollows: Individualsexcludedfromtrial(subsequenttoinitialscreening) Whencontacted,atotalof41individualswerefoundnoteligible,andthereforenotaskedtoconsent(Testn=26; Controln=15).Themainreasonswere:number/diagnosesofhospitalisationsnotmeetinginclusioncriteria, resident/movingtoAgedCarefacility,diseasesofthenervoussystemsuchasParkinson’sdisease,disorderof cognitiveprocesses(dementia),severevisualimpairment,notspeakingEnglishandcancerdiagnoses. Individualsdecliningparticipation Dataforindividualsdecliningthetrial(Testn=95;Controln=33)arepresentedinTable11.Therewaslittle differenceingenderwith52%maleand48%femalesnotwantingtoparticipate.Table11describesthereasons statedbyindividualswiththenumbersrepresentingthecountsperreason,assomeparticipantsstatedmore thanonereason. Thenumberspresentedthereforeexcludepotentialparticipantswhowerefoundnoteligible(andthereforenot askedtoconsent)whencontacted. Table11Reasonsgivenbypatientsfordecliningtoparticipateinthetrial REASONFORDECLININGTHETRIAL Notinterested/lackofmotivationorcommitment Perceivesparticipationinthetrialtobetoomuchofaneffort Competinglifedemands PerceivestheTMCdevicetoodifficulttouse Donotfeeltheywouldbenefitfromtheintervention Deteriorationinhealthand/ormedicalcareneeds Logisticalreasons Concernsregardingprivacy StudyDesign Other Numberoftimes cited(%) 71(55%) 39(30%) 21(16%) 15(12%) 12(9.4%) 10(7.8%) 10(7.8%) 7(5.5%) 1(0.8%) 12(9.4%) Themainreasonreportedfordecliningtoparticipateinthetrialwasalackofinterest(55%)followedby participationinthetrialbeingperceivedastoomucheffort(30%).Mostoftheindividuals,whodidnotfeelthat theywouldbenefitfromtheintervention,indicatedthattheyhadplentyofcareinplaceandfeltwellsupported byfamily/friendsand/orGP.Althoughtheageofthosewhodeclinedwasnotalwaysavailable,theaverageageof thecohortofpatientswhodeclinedwasquitehigh(77.8±10).Thereasongivenfordeclining,thattheyperceived theTMCtoodifficulttouse,wascitedbyonly12%andonly6%hadconcernsaboutprivacy.Competinglife demandsweremainlycitedasbeingtoobusywithworkorcaringforapartner,toomuchgoingonand travel/goingawayforalongperiodoftime,whereaslogisticalreasonsincludednotwantingtheinternet,and relocation.The‘Other’reasonsreportedwerenotionofownnon-compliance,fearofoutofpocketcostfor internet,recoveredenoughfromcondition,notintherightstateofmindandnotwantingadailyreminderof sicknessandpoorhealth. CSIROTelehealthTrialFinalReportMay2016 Page46of187 Withdrawalfromtrialafterconsentbutpriortodeploymentofmonitoringequipment(Testparticipantsonly) Anumberofindividualswhoundertook(signedconsent)totakepartinthetrialasTestparticipants(n=27)were notabletocommenceduetothereasonsprovidedinTable12: Table12MainreasonsforconsentedTestpatientsnotcommencingmonitoring REASONFORNOTCOMMENCINGMONITORING(TESTPARTICIPANTS) GP/Specialistrefusedconsent ParticipantnotcontactabletoarrangeTMCdeployment CouldnotsuccessfullybeconnectedtoInternet(NBNorADSL) LivingenvironmentnotsuitableforTMCdeployment Changeinpersonalcircumstances N 2 5 8 4 8 AccordingtoCSIROEthicsApproval(ref#13/04),involvementinthetrialasTestparticipantrequiredtheapproval fromtheirtreatingpractitioner.Twooftheconsentedparticipantshadtobewithdrawnfromthetrialafterthey consented,duetorefusalbytheirGPandCardiologist,respectively,toconsent. Therequirementatthestartofthetrialforhighspeedbroadbandconnectivityleadtosignificantdelaysformany participantsfromdateofconsenttodeploymentofthetelemonitoringdevice.Thiswasduetopoorinternet connectionavailability,arisingfromsignificantdelaysinbroadbandnetworkroll-out.Asaresult,anumberof participants(n=5)werenotcontactablebythetimeroll-outprogressedtotheirarea.Eightdwellingscould ultimatelynotbeconnectedtotheinternetwhichledtotheinabilitytoconnectthetelemonitoringdevice. OtherproblematiccircumstancesincludethelivingenvironmentsofparticipantsfoundtobenotsuitableforTMC deploymentduetolimitedspaceorinappropriatelivingconditions.Finally,changesinpersonalcircumstances wereresponsibleforthewithdrawalof8potentialTestparticipantsandtheseincludeddeteriorationinhealth, familycareresponsibilitiesandlossofinterestduetounforeseenlongwaitingtimes. WithdrawalfromtrialpostTMCdeployment(Testparticipantsonly) ReasonforTestparticipantsnotremaininginthestudy(n=18)arereportedinTable13.Theseparticipants discontinuedmonitoringandrequestedtheTMCdevicetoberemovedbeforetheycompletedthetrial.The averagetimefromTMCdeploymenttothelastmeasurementsreceivedfromthewithdrawnparticipantswas7 months(range1-14months)with10participantsmonitoringforatleast6months.Theaverageageof participantswhodidnotcompletethetrialwas71years(range54-87years)andaSpearman’scorrelationwas runtoassessanyrelationshipbetweenageandnumberofmonthsmonitoringbeforewithdrawal.Therewasno significantcorrelationbetweenparticipantageandthenumberofmonthsspentmonitoringpriortowithdrawal (P=0.7).Thenumbersreportedarecountsperreason,assomeparticipantsstatedmorethanonereason. Table13Reasonsgivenbypatientsforwithdrawingfromthetrial REASONFORWITHDRAWINGFROMTRIAL Nolongerinterested/lackofmotivationorcommitment Donotfeelbenefitsfromtheintervention Changesincircumstances(nolongermeetinginclusioncriteria, deteriorationofhealth,difficultyusingTMC) Competinglifedemands(work,family,stress) Logisticalreasons Numberof timescited 4 6 10 4 5 Themainreasonleadingtocessationofmonitoringandultimatelywithdrawalbeforecompletionofthetrialwas deteriorationinhealth(n=10)andoneoftheseparticipantsmovedtoanAgedCareFacilityafter10monthsof monitoring.Twoparticipantswhobothhadbeenmonitoringforlessthantwomonthswithdrewbecausetheyfelt theycouldnotcope,onecitedstressandtheotherfeltthereweretoomanymeasurementsandquestionnaires CSIROTelehealthTrialFinalReportMay2016 Page47of187 andfoundlanguageabarrier.Twooftheparticipantswhoindicatedthattheydidnotfeeltheywerebenefiting fromtheinterventionsufferedfromdeterioratinghealthbutlackoftimetododailychecksandgettingtiredofthe internetdroppinginandoutwerealsocitedasreasonsfornotbenefitingfromtheintervention. Onepatientwaswithdrawnafter3monthsofmonitoringduetotremor,poorcompliancewiththemeasurement scheduleandunwillingnesstobemonitoredbytheassignednurse. Demographicsofstudygroupsatbaseline AllpatientsfromtheMasterlistof114Testpatientsand173potentialControlpatients,hadPBSandMBSdata availablefortheperiod1stJuly2010to31stDec2014.Howeveroncarefulanalysisitwasobservedthatsome patientshadmissingdata,insomecasesforperiodsaslongas3-6months.Allthesepatientshadmultiplechronic conditionsandwerehospitalisedatleasttwiceinthepreviousyear,andinmostcasesweretakingbetween6-10 medicationsaday.ItwasthereforecompletelyunexpectedandinexplicablethatDHSPBSandMBSrecordswere missingdataforsuchprotractedperiodsoftime. Despitedetailedanalysisofthesedataanomalies,theDHSwasunabletoprovideanexplanation,andasaresult, datafromanumberofTestpatientsandControlpatientswererejectedforfurtheranalysis.Thematchingprocess describedinTable4ledtoafinalmatchedcohortof100Testpatientsand137ControlpatientsasshowninTable 14below. Table14BasicdemographicsofTestandControlparticipantsatbaseline. Demographics (Number/Age/Gender) Numberofpatients Age (SD) NumberofMalepatients Age (SD) NumberofFemalepatients Age (SD) TAS ACT HospitalBased T C T C 25 55 13 19 70.2 72.9 71.0 74.1 (9.0) 9.0) (7.7) (8.1) 16 31 10 11 70.4 73.2 70.4 74.2 (10.3) (8.8) (8.0) (6.4) 9 24 3 8 69.9 72.5 73.1 74.0 (6.6) (9.5) (7.5) (10.6) VIC T 25 69.8 (7.6) 19 70.4 (7.6) 6 67.9 (8.2) NSW QLD CommunityBased C T C T 35 14 8 23 69.6 76.25 69.6 70.7 (7.7) (7.4) (14.2) (10.2) 17 8 6 14 71 77.5 65.2 68.7 (5.3) (6.2) (13.6) (8.5) 18 6 2 9 68.2 74.6 83 73.8 (9.4) (9.2) (2.3) (12.4) TOTAL C T C 20 100 137 73.9 71.2 72.2 (8.6) (8.7) (8.9) 11 67 76 73.0 70.9 72.2 (9.0) (8.6) (8.4) 9 33 61 74.9 71.7 72.1 (8.5) (9.1) (9.7) Therewerenosignificantdifferencesbetweenage,genderorBMIofTestandControlpatientsatbaseline.Sixty sevenpercentofTestpatientsweremaleand33%female,withthesefiguresalmostreversedfortheControl patientgroup. Theprimarydiagnosisforeachpatientwasrecordedduringtheinitialquestionnaireandwasthenconfirmedboth fromtheDHSdatabaseandwhenavailable,thehospitaldatabase. Mostpatientshadmorethanoneconditionlistedasaprimarydiagnosis.Forsimplicityprimarydiseaseconditions weregroupedinthebroadcategoriesofCardiacDisease,RespiratoryDisease,DiabetesandOther.Figure10(a) plotsthedistributionofdiseaseconditionsforTestandControlpatientsasa%ofeachgroup.Sincepatientsoften hadmorethanoneprimarydiagnosis,percentagevaluescouldaddtomorethan100%. ThebroadcategoryofCardiacdiseaseincludedAF,AHD,AMI,Aorticvalvestenosis,AP,CAD,CHD,CHF,CM,CVD, HT,IHD,NSTEMIandSTEMI.RespiratorydiseaseincludesAB,AST,BTandCOPD.TheDiabetesCategoryincluded DMandT2DM,andtheOtherdiseasecategoryincludedART,BowelCondition,Cellulitis,ProstateCancer,Renal DiseaseandRenalfailure. CSIROTelehealthTrialFinalReportMay2016 Page48of187 80% 70% 1200 Test Control 1000 60% 800 50% SEIFAIndex %oftotalcohort 40% 30% 400 20% 10% 0% 600 200 Cardiac Diabetes Respiratory Figure10(a)PrimaryDiagnosis 0 Other ACT 16 23 NSW 17 12 QLD 27 30 VIC 27 49 TAS 29 60 (b)DistributionofSEIFAindexacrosssites Insubsequentanalysis,patientswerecharacterisedashavingaprimarydiagnosisofCardiovasculardisease(50), Respiratorydisease(30)orDiabetes(20).AsillustratedinFigure10(b)therewerenostatisticaldifferences observedbetweenTestandControlpatientseitherwithrespecttotheSEIFAstatusortheirprimarydisease diagnosis. Figure11showsthewidedistributionofcommencementdatesforthetelemonitoringofvitalsigns. 120% 30 100% 25 Frequency 35 20 15 80% 60% 40% 10 5 20% 0 0% Figure11Distributionofcommencementdatesformonitoringofvitalsigns Testpatientsweremonitoredonaveragefor276days,(Figure12)withnosignificantdifferencebetweenaverage monitoringdurationsforfemalepatients(266days)andmalepatients(281days).SeventyfivepercentofallTest patientsweremonitoredforperiodsexceeding6months. 20 Frequency 15 10 5 0 Figure12DistributionofnumberofdaysofmonitoringofTestPatients(N=100) CSIROTelehealthTrialFinalReportMay2016 Page49of187 TheaverageageofpatientsatthecommencementofmonitoringofTestpatientsisshowninTable15. Table15AgeofTestandControlpatientsatstartoftelemonitoring ALLPatients MalePatients FemalePatients N TEST N CONTROL 100 67 33 71.1±8.7 70.8±8.6 71.7±9.1 137 76 61 71.7±9.0 71.2±9.1 72.3±8.9 TheageofeachTestpatientatcommencementofmonitoringwascomparedtotheageoftheirrespective controlsatthattime.Controlpatientswereonaverage0.46yearsolderthatTestpatients.Thisdifferencewasnot statisticallysignificantforeithermaleorfemalepatients. Theresultsthatfollowrelateexclusivelytothiscohortof100TestPatientsand137matchedControlpatients. BaselinehealthcharacteristicsofTestandControlpatientsatpointofentry AsexplainedinSection5.1.2,acohortof100Testand137matchedControlpatientswereincludedinabaseline analysistoevaluatehealthcharacteristicsbetweenthetwogroupsaftermatching.Intheanalysis,whentwo matchedControlpatientswereavailableperTestpatient,theirdatawereaveraged.Baselinecharacteristicsare describedforbothgroupsusingmean±SDsforcontinuoussymmetricalvariablesandmediansandIQRfor skeweddata.Comparisonsismadebetweenthetwogroupsatbaselineusingthecasesavailableandthenumber ofparticipantswhocompletedthespecificEntryQuestionnaireitemsareindicatedinTable16.Thetwo-samplettestwasusedforcontinuousvariablesandtheWilcoxonrank-sumtestforskewedvariables. Allstatisticaltestsweretwo-tailed,andapvalueof<0.05wasusedtoindicatestatisticalsignificant.Statistical analysiswasperformedusingStataReleaseV.12(TX:StataCorpLP). Table16Self-Reportingmeasures,forTestandControlpatientsatEntry QUESTIONNAIRE KesslerK10 (Median,IQR) Morisky (Median,IQR) EQ5DIndex Mean±SD(95%CI) heiQ Self-monitoringscore Mean±SD(95%CI) Healthservice navigation Mean±SD(95%CI) Socialisolation Mean±SD(95%CI) TEST N CONTROL N Pvalue 18.5 (14.0–26.0) 94 18.0 (13.5–23.0) 97 0.25 7.0 (6.75-7.75) 97 7.0 (6.13–8.0) 97 0.76 0.62±0.25 (0.57–0.67) 98 0.64±0.23 (0.59-0.68) 96 0.55 3.1±0.33 (3.0-3.17) 98 3.07±0.33 (3.01-3.15) 97 0.66 3.23±0.45 (3.2-3.3) 98 3.24±0.42 (3.15-3.32) 96 0.99 3.06±0.52 (2.96-3.16) 97 3.02±0.54 (2.91-3.13) 97 0.62 TherewerenosignificantdifferencesbetweentheTestandControlparticipantsatbaselineintermsofhealth characteristics.TheKessler10scores(measurementofdepression)wereinthenormalrangeforbothgroups.The EQ-5Dindex,whichrecordstheparticipants’self-ratedqualityoflife,showedbothgroupstobebelow0.7,an indicationoffairself-ratedhealth.SelectedconstructsfromtheheiQquestionnairewereincludedintheEntry Questionnaireandcompriseself-monitoring,healthservicenavigationandsocialisolation. Nosignificantdifferenceswereobservedinanyofthesescores,however,bothgroupsshowedrelativelyhigh scoresforSelf-monitoring(comparablewithbenchmarkstatisticsatbaselinefortheAustralianpopulation(3.03) whichreferstoself-reportsofmorepositiveeffect). CSIROTelehealthTrialFinalReportMay2016 Page50of187 Healthservicenavigationandsocialisolationscoreswerealsorelativelyhigh,comparablewiththeAustralian population(3.1and2.91respectively),andweresimilarinboththestudygroups. 5.2 UsabilityandAcceptabilityofTelemonitoringtoPatients,CliniciansandCarers Patientexperiencewiththetelemonitoringtechnology TestpatientsansweredtheUserSatisfactionQuestionnaireattheendoftheproject.Thequestionsabout telemonitoringtechnologyincludedparticipants’perceptionsoftechnologycomplexityandcompatibility. Wereceivedresponsesfrom56participants.Alltestpatientswereoverallsatisfiedwithusingthemonitoring device(Table17).TheyfoundtheinstructiononusingtheTMCdeviceeasytounderstand.Responsesindicate thatfewparticipantsfoundthedevicecumbersome,unnecessarilycomplex,orthoughtthattheywouldneeda technicalperson’ssupportinusingthedevice.MajorityofparticipantsfoundtheTMCeasytouse(87.5%)andfelt confidentinusingit(85.7%)despite32.1%ofthemreportingthattherewereoccasionsoffrustration.Intermsof compatibility,majorityofparticipantsfoundthatusingthemonitoringdevicecouldbeincorporatedintheirdaily routine(80.4%),fitsinwiththeirdailylife(71.4%)andthewaytheywouldliketomanagetheirhealth(76.8%). Table17PatientresponsestoUserandSatisfactionSurvey-Telemonitoringequipment ITEM %Agreedor stronglyagreed N=56 COMPLEXITY • TMC*easytouse • IsometimesfindtheTMCsystemfrustratingtouse • InstructionsontheTMCareeasytounderstandandfollow • UsingtheTMCsystemiscumbersome • IneededtolearnalotofthingsbeforeIcouldgetgoingwith theTMC • IfoundtheTMCunnecessarilycomplex • IthinkthatIwouldneedthesupportofatechnicalpersonto beabletousetheTMC • IfeelveryconfidentusingtheTMC • IfindthevariousfunctionsintheTMCarewellintegrated COMPATIBILITY • TMCisatoolthatwouldbeeasytoincorporateintomy dailyroutine 87.5 32.1 83.9 19.6 23.2 7.1 12.5 85.7 83.9 80.4 • TheTMCfitsrightintothewayIliketomanagemyhealth 76.8 • UsingtheTMCfitswellwithmylifestyle 71.4 *TMCsystemistheTelemedcaretelemonitoringsystemsuppliedtoTestpatients. Wealsoaskedquestionsaboutthepatients’experienceofempowerment,experiencewithtelehealthnurse, serviceobservabilityandoverallsatisfactioninaUserSatisfactionquestionnaireattheendofthetrial. Wereceivedresponsesfrom49participants.Themajorityofpatients(73.5%)weresatisfiedwiththeirinternet connectionsandmost(89.6%)reportedthattheyweresatisfiedwiththetelemonitoringservice(Table18).Their overallexperiencewiththetelehealthnurseswaspositiveintermsofthetimeanddiscussionstheyreceivedfrom thenurses.Howeveronly12.2%ofpatients’reportedthattheirGPsreviewedthetelemonitoringresultsduring patients’visitsandonly34.7%patientsagreedthattelemonitoringimprovedtheircommunicationswithGPs CSIROTelehealthTrialFinalReportMay2016 Page51of187 AsshowninTable18,testpatientsfoundthattelemonitoringimprovedtheirknowledgeabouttheirconditions (69.4%)andsymptomstowatchfor(77.6%).Theyreportedthattheyhadbecomemoreinvolvedinmonitoring theirhealthconditions(79.6%)andimprovedtheirself-care(71.4%)asaresultoftelemonitoring.Asmallnumber feltthatseeingtheirvitalsignseverydayandtalkingtotelehealthnursesmadethemanxiousorworried.Alarge majority(89.8%)ofthemrespondedthattheywouldrecommendtelemonitoringservicetootherpeople. Table18PatientresponsestoUserSatisfactionSurvey–Telemonitoringservice %positive ITEM (e.g.agree/satisfied andstrongly agreed/verysatisfied) N=49 EMPOWERMENTEXPERIENCE Dailymonitoringofmyvitalsignshasimprovedmyknowledgeaboutthenatureofmyhealth condition DailymonitoringofmyvitalsignshasimprovedmyknowledgeaboutthesymptomsIshould watchfor DailymonitoringofmyvitalsignshasimprovedmyknowledgeaboutthewayIcanbetter managemyhealthcondition Asaresultofusingthetelemonitoringservice,Ihaveinvolvedmoreinmonitoringmyhealth condition Asaresultofusingthetelemonitoringservice,Ihavebeenabletobettermanagemyhealth condition Asaresultofusingthetelemonitoringservice,Ifeelmoresecureaboutmyhealthcondition Asaresultofusingthetelemonitoringservice,Ihaveimprovedmyself-care EXPERIENCEWITHTELEHEALTHNURSE Howdoyoufeelabouttheserviceprovidedbythetelemonitoringnurseintermsofthetime giventoyoubythetelemonitoringnurse Howdoyoufeelabouttheserviceprovidedbythetelemonitoringnurseintermsofcontacting youwhenthereisaneedtodiscussyourmeasurement Howdoyoufeelabouttheserviceprovidedbythetelemonitoringnurseintermsofhelping youtounderstandyourconditions Inanoverallandgeneralsense,howsatisfiedareyouwiththetelemonitoring serviceyoureceivedfromthetelemonitoringnurse? OBSERVABILITY 69.4 77.6 59.2 79.6 61.2 69.4 71.4 87.8 79.2 77.1 75.0 Theeffectsofmonitoringmyhealthusingthetelemonitoringserviceareapparenttoothers 38.8 Iwouldrecommendusingthetelemonitoringservicetootherpeople 89.8 OVERALLSATISFACTION Overallhowsatisfiedareyouwiththetelemonitoringservice? 89.6 Wouldyouliketocontinueusingthetelemonitoringserviceafterthetrial? 57.1 OTHEREXPERIENCE Talkingtotelemonitoringnurseoverthephonemakesmeworryaboutmycondition 4.1 Seeingmyvitalsignseverydayhasmademeanxiousaboutmychroniccondition 12.2 HowoftenhasyourGPreferredtoyourmeasurementsduringyourvisits? 12.2 TelemonitoringhasimprovedmycommunicationwithmyGPs 34.7 Howsatisfiedareyouwithyourinternetconnection? 73.5 CSIROTelehealthTrialFinalReportMay2016 Page52of187 AlltheTestpatientsinterviewedwerekeentousehometelemonitoringandpositiveaboutitsvalue.They appreciatedthattheirmeasurementswerebeingmonitoredandthefeelingofbeinglookedafterbynurses.A patientfromQueenslandcommented: “Thisgivesmegreatpieceofmind.Iamgettingtoknowthevariations,andwhenIhaveabadreadingItakeit easy.WithoutthisthingIwouldjustgoaboutlikenormalandgetmyselfintrouble.” “Iknowtheladiesbehindareseeingmydataandwillcallmeifneedbe,itislikeseeingmyGP.” “IhavealotoffaithinitandIshowittomymates,itislikehavingadoctorathome.” Patientcompliancewithmonitoringschedules Generallytherewasahighlevelofsatisfactionwiththetelehealthserviceandtheeaseofuseofthe telemonitoringtechnology.Compliancewiththemeasurementprotocolsscheduledforeachpatientwas generallyhighwithpatientscarryingouttheirscheduledmeasurementsandquestionnairesatleastonceevery twodays.Giventhedemandingscheduleofmeasurementsandquestionnaires,thisisconsideredaconsiderable achievementandmorethansufficienttodevelopacomprehensivelongitudinalpatientrecordinthehome. AstrongcorrelationwasfoundbetweenthelevelofinvolvementoftheCCCsandpatientcompliance.Thehigher theCCCengagementwiththepatientandthemonitoringofpatientdata,thehigherwasthelevelofcompliance fromthepatient.ClinicalCareCoordinatorsgenerallyviewedeverypatient’srecorddailyandtrackedtimespent oneachpatientusingtheCSIROWEBportal. Patientcompliancewiththeirscheduleddailymeasurementswerecalculatedbytrackingthetotalnumberof scheduledeventsandthencountingtheactualnumberofmeasurementactivitiescompleted.Theratioofthese providedarobustmeasureofcompliance.OverallpatientcompliancedataisshowninTable19.Testpatients successfullycompleted177,416measurementsofvitalsignsandrespondedto26,649questionnairesoverthe periodof16months.Patientcompliancewiththeirscheduleddailymeasurementswerecalculatedbytracking thetotalnumberofitemscompletedandcomparingtonumberofitemsscheduledoverthesameperiodoftime. Table19Patientcompliancewithmeasurementandquestionnaireschedules(ALLTestpatients) ItemofActivity Location:(Allsites) Numberof Numberof Scheduled Items Items Completed VITALSIGNSMEASUREMENT BloodPressure 30,679 20,551 ECG 30,327 19,817 PulseOximetry 30,834 20,216 BloodGlucose 12,464 8,739 Spirometry 20,692 10,876 BodyTemperature 27,297 17,143 BodyWeight 25,122 14,124 AverageCompliance(Measurements) 177,416 111,466 CLINICALQUESTIONNAIRES CHF(Daily) 12,139 6,179 COPD(Daily) 8,679 4,335 QualityofLifeEQ5D(Weekly) 3,761 2,235 MentalHealthK10(Monthly) 943 534 LivingWithandManaging 919 621 MedicalConditions(HeiQ) MedicationsAdherence 208 93 AverageCompliance(Questionnaires) 26,649 13,997 % Compliance 66.99% 65.34% 65.56% 70.11% 52.56% 62.80% 56.22% 62.83% 50.90% 49.95% 59.43% 56.63% 67.57% 44.71% 52.52% CSIROTelehealthTrialFinalReportMay2016 Page53of187 Thesedatashowthatonaverage,patientswererecordingtheirvitalsignsalittlebetterthaneverytwodays, representingacompliancerateofapproximately62.8%,andtheyweretakingquestionnairesatapproximately 52.5%ofthescheduledrate. Similarly,forQuestionnairestheHeiQ(LivingWithandManagingMedicalConditions)werecompleted67.6%of thetimewhilsttheMedicationsAdherencequestionnairewasonaveragecompletedonly44.7%ofthetime. Table20Patientcompliancewithmeasurementschedules(TAS+ACTpatients) ItemofActivity Location:(TAS+ACT) VITALSIGNSMEASUREMENT BloodPressure ECG PulseOximetry BloodGlucose Spirometry BodyTemperature BodyWeight AverageCompliance(Measurements) Numberof Scheduled Items Numberof Items Completed % Compliance 13,399 13,464 13,482 4,209 9,433 13,392 12,131 79,510 9,204 9,129 9,090 3,295 6,325 8,958 7,938 53,939 68.69% 67.80% 67.42% 78.28% 67.05% 66.89% 65.44% 67.84% 5,688 5,225 2,161 281 3,096 3,088 1,209 201 54.43% 59.10% 55.95% 71.53% 173 76 43.93% 173 13,701 69 7,739 39.88% 56.48% CHF(Daily) COPD(Daily) QualityofLifeEQ5D(Weekly) MentalHealthK10(Monthly) LivingWithandManaging Medical Conditions(HeiQ) MedicationsAdherence AverageCompliance(Questionnaires) PatientsunderthecareofthehospitalbasedCCCswereonaveragemorecompliantbothfortherecordingof vitalsigns,andtheirmeasurementschedules,comfortablyaveragingmorethan50%compliancewithboth,as demonstratedinTable20. Table21Patientcompliancewithmeasurementschedules(NSW+VIC+QLD) ItemofActivity Location:(NSW+VIC+QLD) Numberof Numberof Scheduled Items Items Completed VITALSIGNSMEASUREMENT BloodPressure 17,280 11,347 ECG 16,863 10,688 PulseOximetry 17,352 11,126 BloodGlucose 8,255 5,444 Spirometry 11,259 4,551 BodyTemperature 13,905 8,185 BodyWeight 12,991 6,186 AverageCompliance(Measurements) 97,905 57,527 % Compliance 65.67% 63.38% 64.12% 65.95% 40.42% 58.86% 47.62% 58.76% CHF(Daily) COPD(Daily) QualityofLifeEQ5D(Weekly) MentalHealthK10(Monthly) LivingWithandManaging MedicalConditions(HeiQ) MedicationsAdherence AverageCompliance(Questionnaires) 6,451 3,454 1,600 662 3,083 1,247 1,026 333 47.79% 36.10% 64.13% 50.30% 746 545 73.06% 35 12,948 24 6,258 68.57% 48.33% CSIROTelehealthTrialFinalReportMay2016 Page54of187 PatientsunderthecareofcommunitybasedCCCswereonaveragealittlelesscompliantasseeninTable21 (58.76%versus67.84%)withtheirmeasurementofvitalsignsandconsiderablylesscompliantwiththeir questionnaires(48.33%versus56.48%)thenpatientsunderthecareofhospitalbasedCCCs. UsageofTMCClinicianPortalandCSIROPortalbyCareCoordinators TMCClinicianPortal TheTMCClinicianportalallowedauthorisedclinicianstoviewandifnecessary,toeditpatientdatarecorded.It providedanumberoffacilitiesforsettingflagswhichwouldindicatethatpatient’smeasurementshaveexceeded individualbounds.Thesecouldbesetgloballyforthewholepatientcohort,orindividuallytoreflectindividual patientconditions. ProjectpolicywasthatpatientdatahadtobeviewedatleastonceadayduringtheMondaytoFridayworking week.ThedatashownFigure13spentonaverage<30minutesadayreviewingpatientdatafrom20patients(on averagemostsiteshadaround20parients). 2.5 30 2.0 25 Minutesspentonline NumberofLoginsperday 1.5 1.0 0.5 0.0 20 15 10 5 a.Averageloginsperday/Clinician b.Timeperloginreviewingpatientdata Figure13UseoftheTMCClinicianWebportalbyClinicalCareCoordinators ThiswouldsuggestthataCCCworkingfulltime(6.5hoursworkingtime)andresponsibleONLYformonitoring patientdatacouldmanageatheoreticalmaximumof20x(6.5hoursx60minutes/30)=260patientsaday.With additionaltimerequiredtomanagecomplexcases,communicatewithGPsandcarersandgenerallycoordinate thepatient’scare,therealisticfigureislikelytobeintheorderof100-150patients. WenotethatinTASpatientmonitoringwascarriedoutbythreespecialistnursesandintheACTmonitoringwas undertakenbyapanelofspecialistnurses.Intheremainingsitesmonitoringwasusuallycarriedoutbyasingle communitynurse.TheresultsshowninFigure14arebroadlyinlinewithprojectpolicyandindeedexceedthe minimumrequirementofreviewingthepatientdataatleastdaily. CSIROportal TheCSIROPortalprovidedausefuldepositoryofinformationonprogresswiththetrial,adisseminationsystem forthedistributionofinformationandproceduresandasocialforumwhereCCCsandPOscouldsharetheir experiences.ClinicalCareCoordinatorswerealsoencouragedtousetheCSIROPortaltotracktheiractivitiesand theircontacttimewithpatientsortheircarers.TheplotsinFigure14indicatethehospitalbasedsitesofTASand theACTwereloggingintotheCSIROportalonaverage1.4-1.6timesaday.Forthecommunitybasedsites,CCCs werelogginginonaveragejustoveronceaday. CSIROTelehealthTrialFinalReportMay2016 Page55of187 Numberofdailylogins 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 ALL NSW+QLD+VIC TAS+ACT Figure14RecordofaveragedailyloginstotheCSIROPortal/clinician Clinicians’perceptionsoftelemonitoringbenefittopatients PositivefeedbackwasreceivedfromPOsandCCCsintermsofimprovingpatientknowledgeaboutthenatureof theirchronicconditionsandsymptoms(Table22).89%ofthemrespondedthattelemonitoringhadimprovedthe patients’self-careandmadepatientsfeltmoresecureabouttheirhealthconditionsandasimilarpercentage believedthattelemonitoringwouldhavearoleinimprovingtheoverallqualityofcareprovidedtopatientsand wouldrecommendtheservicetootherpatients. POsandCCCsreportedissuesininteractingwithGPsandspecialistsandonly33%ratedtheseinteractionsas satisfactory.Theyalsohadproblemsintermsofincorporatingthetelemonitoringintotheirdailyroutineaswe haveseeninthequestionnaireandinterviews. Table22ProjectOfficersandCareCoordinatorsperceptionofbenefitstopatients ITEM %positive (e.g.agree/satisfiedand stronglyagreed/very satisfied)(N=9) EXPERIENCEINDELIVERINGTHESERVICE Interactingwithpatients Monitoringthepatients InteractingwithGPs InteractingwithSpecialists USABILITY TheTMCuserinterfacefortheclinicianswaseasytouse CSIROportalinterfacewaseasytouse PERCEIVEDBENEFITTOOVERALLQUALITYOFCARE Madethepatientfeelmoresecureabouttheirhealthcondition Improvedthepatient’sself-care Improvedhowthepatientmonitorstheirhealthcondition Telemonitoringhasaroleinimprovingtheoverallqualityofcareprovidedtopatients Improvedpatientknowledgeofthesymptomstheyshouldwatchfor Improvedpatientknowledgeofthewaytheycanbettermanagetheirillness Improvedpatientknowledgeofthenatureoftheirclinicalcondition Improvedhowthepatientmanagetheirhealthcondition COMPATIBILITYANDOBSERVABILITY Iwouldrecommendtelemonitoringservicetootherpatients Iwouldrecommendtelemonitoringservicetootherclinicians Overallhowsatisfiedareyouwiththetelemonitoringservice? Myroleinthetelemonitoringtrialhasbeeneasytoincorporateintomydailyroutine 67.0% 56.0% 33.0% 33.0% 56.0% 56.0% 89.0% 89.0% 89.0% 89.0% 78.0% 78.0% 67.0% 44.0% 89.0% 78.0% 56.0% 22.0% CSIROTelehealthTrialFinalReportMay2016 Page56of187 AllCCCs,POsandGPsweinterviewedbelievedthathometelemonitoringwouldhavepotentialpositiveimpacton theearlyinterventionforchronicdiseasepatients(Table22).SomeCCCsandPOs(e.g.TAS,VIC)andGPs (e.g.,QLD)foundthattheirpatientshaveimprovedknowledgeabouttheirchronicconditionsandwereableto learnthemeaningoftheirmeasurementsandtodiscussthesewithclinicians.OneofthePOsreportedthe followingduringasitevisit: “Bytalkingtopatients(e.g.duringthevisitstohomeforsoftwareupdates)Ihavelearnedthatpeoplearebeing moreandmoreempoweredbyTMCinformationandbeingabletogotoGPstotalkaboutmeasurements,learn moreabouttheirhealth.Theycanseethingsgoingupanddowneveryday.Oneofthebiggestopportunitiesfor reducinghospitalizationisbyCCCspickingupclinicaldeteriorationandsometimespatientsarepickingupthese.A patientsaidthatshewasreassuredthatsomeoneiskeepinganeyeonher.” MajorityofGPsweinterviewedpointedoutthattelemonitoringwouldbemoreusefulinruralsettings.Oneof thephysicianswhoworkedinhospitalbelievedthatitcouldplayanimportantroleinearlydischargeofpatients fromhospital. POsandCCCsalsomadecommentsaboutthebenefitsoftelemonitoringinthequestionnaire.Thefollowingare examplesofthesecomments: • • • • • • • Identifyingdeteriorationornewissues Offeringsupporttoeachindividualpatienttomeettheirneeds,notjustwhentheirreadingsareoutside theirparameters Patientscanseetheirreadingsandthisenablesthemtomakeinformedchoice Empowermentoftheclienttoself-managethroughawarenessandeducation Asaresultofearlydetection,careissoughtearlierhencereducing/avoidinghospitaladmissions Itisextremelyusefulforpatientsastheyareconfidenttakingcareoftheirownhealthandpeaceofmind thatthereissomeonetoassistthemifnecessary. Thevisualeffectofseeingdatareinforcedtheirinterestintheirownhealth,especiallymalepatients ThePOatTASsummarisedherreflectionsofthetrialinthequestionnaire: “Iperceivedtheimprovedclinicalmanagementbenefitstoincludefeweracuteexacerbationsthroughearly detectionandfewersubsequenthospitalisations.Thisshouldleadtopatientsreceivingtherightcareintheright place.Itshouldalsoimprovelongtermhealthoutcomesforthepatients. Benefitstothehealthsystemincludereducingtheburdenonhighdemand,highcostacutehospitalbeds. Telemonitoringalsohasthepotentialtoreducetheburdenonsectionsofprimaryhealthcarebypotentially reducingGPvisits.GPvisitscouldpotentiallybemoreproductivebyprovisionofpatienttrenddataenablinggood clinicalmanagementdecisionmaking.” “Atthisprojectsite,theprojecthasbeenverysuccessfulinachievingalloftheseoutcomestovaryingdegrees.” Carers’perceptionsoftelemonitoringbenefittopatients Familymembersofthepatientswevisitedhavebeensupportiveofpatients’useoftelemonitoring.Their knowledgeaboutpatients’chronicconditionshasbeenimprovedaswell.Thefollowingisfeedbackfroma patient’swife: “Itendtostressoutalotovermyhusband.Sincewehavethemachineathome,IfeelIcouldringtheGPandsay tohimmyhusbandissick.” “Thenurse’svisittousisabigplus.Welearnedthingsfromher.Sheistheonewhoputusonthelungseminar.” CSIROTelehealthTrialFinalReportMay2016 Page57of187 5.3 ImpactoftelemonitoringonpatientexpenditureonMBSandPBSitems. Thequantitativestatisticallyrobustevaluationofhealthandsocialeconomicoutcomesareacornerstoneofthis projectandtheclinicaltrialprotocolinChapter4describesindetailhowtheprojectobjectivesweretobemet oncethenumerousdatabasesfromathometelemonitoringandquestionnaireinstruments,PBSandMBSdata fromtheDHSandhospitaldata(whenavailable)werefullyintegratedandanalysed. Inthissectiondataisanalysedusingconventionalstatisticalmethods.Becauseofthetemporalnatureofhealth dataandtheunderlyingtrendscausedbytheincreasingburdenofchronicdiseasewithincreasingage,beforeand aftercomparisonscanbedifficult.Wehavechosentouse30daysasthetimeperiodoverwhichweanalysedand reportourresults,andintroducethreedifferentmethodswhichwillassistwiththeinterpretationofunderlying trendeffects. Method1: RegressionanalysisandANOCOVAanalysisofdifferencesinslopes Inthismethodweused30dayintervalsforMBSandPBSanalysisand100dayintervalsfornumberofadmissions andlengthofstay.Alldataweretimealignedsothatthetimeinterval“0”representedthedaywhen telemonitoringcommenced,and0to-35istheperiodof36x30daysBEFOREtheinterventionand1to12 representsthe12x30daysAFTERtheintervention.Thedisadvantageofthismethodisthattheeffectsof seasonalvariationscannotbeassessedandindeedareminimisedbecauseofaveragingeffects.Thismethod howeveremphasisesthattheinterventionisthefirstordereffectthatweareseekingtoanalyse. InMethod1,BeforeandAfterdataforMBScosts,PBScosts,numberofadmissionstohospitalandlengthofstay inhospitalwereanalysedfor(i)thewholepatientcohort,(ii)malesseparatelyand(iii)femalepatientsseparately, aswellaspatientswith(i)Cardiacconditions,(ii)Lungdiseaseand(iii)Diabetesastheirprimarycondition.In addition,patientsmonitoredinacommunitysettingandthosemonitoredinahospitalsettingwereanalysed separately. Method2: Mixedlineareffectsmodelling Linearmixed-effectsmodels(LME)areanimportantclassofstatisticalmodelsthatincorporatebothfixed-and randomeffectstermsinalinearpredictorexpressionfromwhichtheconditionalmeanoftheresponsecanbe evaluated.Thesemodelsareoftenusedtoanalysecorrelateddataasisoftenencounteredinbiostatistics.Linear mixed-effectsmodelsareextensionsoflinearregressionmodelsfordatathatarecollectedandsummarizedin groups.Thesemodelsdescribetherelationshipbetweenaresponsevariableandindependentvariables,with coefficientsthatcanvarywithrespecttooneormoregroupingvariables.Complexmodelscanbedevelopedthat simultaneouslyconsiderseasonaltimevariationsaswellasdifferencesbetweenmultipletestsites. Method2enhancestheanalysisundertakenusingMethod1byintroducingseasonaleffectsandsitespecific effects Method3:Cumulativesumofdifferences ThismethodcanbeusedtoidentifytimedependentchangesinthedifferencesbetweenTestandControl patients,followingthetelemonitoringinterventions.Byconsideringdifferences(Test-Controls)onlyseasonaland othercommoneffectsareeliminatedanddifferentialeffectsofthetelemonitoringinterventioncanbemore easilyidentified.Howeveradisadvantageisthatitisimpossibletoquantifythespecificeffectsoftheintervention ontheTestpatientsinabsolutedollarterms WehavechosentopresenttheresultsofMethod1intheResultschapterandtoleaveadditionaldetailed analysisusingMethods2and3canbefoundinSection5.10andChapter8.Thischoicewasmadetofocusthe analysisonthefirstordereffectoftelemonitoringontheoutcomesandtominimisepossibleseasonaleffects. Moreimportantlytheuseoflinearregressionspermitstheeasyquantificationofeffectsinabsolutedollarterms. Throughouttheseresultsindependentsamplest-testisusedwhentwoseparatesetsofindependentand normallydistributedsamplesareobtained,onefromeachofthetwopopulationsbeingcompared. CSIROTelehealthTrialFinalReportMay2016 Page58of187 HoweverasexplainedintheChapter4,theprojectdesignmakesrandomselectionofTestandControlpatients impossibleandthealternativeBeforeandAfterControlIntervention(BACI)designwasadopted. AsaconsequencestatisticalcomparisonsinthisstudycanonlybevalidlymadeonTest–Controlmatchedpairs andtestedusingthepairedsamplesorrepeatedmeasurest-tests.Inadditionthetimecourseofbeforeandafter datacanbeassessedusinglinearregressionandANCOVAanalysisofslopestoidentifystatisticallysignificant difference. MBSandPBSdatawasavailablefor100Testpatientsand137Controlpatients.WhentwomatchedControl patientsareavailabletheirdatawasaveraged. ApreliminarygraphicalanalysisofbothPBSandMBSdata,usingtheMATLABfunctionnormplotaswellasthe Chi-squaregoodnessoffittestindicatedthatthedatawasnotnormal.Bothlognormalandsqrttransformations werefoundtobeeffectiveinnormalisingthedata.Thesqrttransformationwaschosenasalittlebetterand appliedtodatabeforethelinearregressionwascarriedout. ThiswasrepeatedbothforTestpatientdataandControlpatientdata.DifferencedatacalculatedfromControl– Testforeachdatapointwasfoundtobenormallydistributedanddidnotneedtheapplicationofthesqrt transform. CSIROTelehealthTrialFinalReportMay2016 Page59of187 DescriptivestatisticsformatchedTestandControlpatients Inordertocomparethestatisticalmatchoftestandcontrolpatientsattheonsetoftelemonitoring,individual PBSandMBScostsandeventsweresummedoveraperiodof100daysjustpriortothebeginningofthe interventionandcomparedtothefirst100daysofmonitoringforeachindividualpatient. WhenaTestpatienthasmorethanoneControl,thedataforthetwoControlpatientswereaveragedtoobtaina matchedpair. Table23BaselinecomparisonbetweenTestandmatchedControlpatientsbeforeandafterintervention. Variable NumberofvisitstoGPs CostofvisitstoGPs Numberofvisitsto/byAllied Health Costofvisitsto/byAlliedHealth NumberofvisitstoSpecialists CostofvisitstoSpecialists Numberofmedications prescribed TotalCostofmedications prescribed TotalCostofProcedures/Tests TotalCostofLaboratoryTests TotalcostofMBSandPBSitems PatienttravelcostinvisitingGPs Control Test Before Before 4.2 5.7 (3.4-5.1) 183.7 (146-223) 0.5 (0.3-0.8) 25.1 (14.6-41.7) 1.3 (0.9-1.9) 130.6 (85.6-192) 25.5 (4.4-7.1) 245 (189-306) 0.6 (0.3-0.9) 30.2 (17-51.8) 1.6 (1.1-2.2) 159.1 (105-232) 28.1 (22-28.4) (23.8-31.9) 1076.7 959 (867-1288) (814-1088) 525.1 (320-830) 134.8 625.1 (385-976) 133 (91-192) (89.3-191) 2019.7 2029.9 39.2 44.4 (1633-2406) (1697-2338) (27.3-54.3) (30-63.3) P Value 0.04* 0.35 0.42 0.40 0.15 0.22 0.21 0.3 0.35 0.43 0.17 0.48 Control Test After After 4.2 5.6 (3.4–5.0) 193.8 PValue <0.01** (4.4-6.8) 250.4 (153-236) (196-308) 0.5 (0.3-0.7) (0.4-1.1) 0.7 0.20 24 38.1 (21.1-66.5) (15.4-35.8) 1.3 (0.9-1.9) 133.2 1.9 198.3 (127-298) 25.6 28.3 (23.7-32.5) 1163.3 (928-1404) 419.6 (269-630) 104.9 979.5 (817-1130) 543.8 (353-806) 109.8 (74.1-143) (75.9-153) 2078.5 2076.9 40.8 44.9 (1678-2479) (1738-2391) (28.1-57.1) 0.32 0.04* (1.3-2.7) (85.5-200) (22.2-28.5) 0.09 0.15 0.37 0.25 0.22 0.39 0.17 0.34 (30.8-63) Note:Theannualvalueforeachparametercanbeeasilyobtainedbymultiplyingeachentryby3.65. TherewassignificantdifferencebetweenthenumberofvisitstotheGPrecordedforTestandControlpatients, bothforthe100daysbeforetheinterventionandimmediatelyaftertheintervention,althoughthenumberof visitsdidnotchangesubstantially.AslightincreaseinthenumberofvisitstospecialistsmadebyTestpatients aftertheinterventionwasalsoobserved.Nootherparametersweresignificantlydifferent.Theabovetable demonstratesthatTestpatientsandtheirControlswerewellmatchedwithrespecttothePBSandMBSitems identifiedinTable23. HowevertraditionalBACIbefore-and-afteranalysescanprovidemisleadingresultswhenoutcomesarenonstationaryasisshowndiagrammaticallybelowinFigure15; CSIROTelehealthTrialFinalReportMay2016 Page60of187 SameMEANS? BEFORE AFTER Figure15Beforeandaftermeansmayappearidenticalwhendataisnonstationary LinearregressionanalysisofimpactoftelemonitoringinterventionontotalMBSexpenditure ForthisanalysisalloutofhospitalMBScostsweresummedover30consecutivedayintervals.Thesecosts included,mostoutofhospitalcostsforthemajorityofMBSItemnumbersavailable,asoutlinedbelowinTable 24; Table24MBSItemNumbersincludedinanalysis ITEMDESCRIPTION MBSITEMNumbersIncluded GPVisits–NormalHours 3,23,24,35,36,37,44 GPVisits–AfterHours 597,598,599,2504,2517,2521,2525,2546,2552,5000,5020,5023,5028,504 0,5060,5063 PrimaryCareAssessmentsandCarePlanning 700,703,705,707,715,721,723,729,731,732,739,743,750 SpecialistVisits–otherthanPsychiatric 104,105,110,116,119,132,133,141,143,385,503,511,828,830,832,880,600 7,6009,6011,6015 AlliedHealth 53,54,57,59,60,65,10951,10953,10954,10958,10960,10962,10964,10966, 10987,10993,10996,10997,80010–82215 Laboratorytests(Haematology,chemistry, 65060-73940 immunology,tissuepathology,cytopathology, basictestsandcollectioncosts) CostswereavailableasCostofvisit,GovernmentContributiontocostandPatientContribution.Inmostcasesthe PatientContributionwaszeroandaccordinglytheCostofvisitalonewasconsidered.HospitalflagsorInhospital costswereignoredaswewereinformedthatthesewereonlysetifin-hospitalcostswereinfactcharged,which inmanycasestheymaynotbe.Intheplotsbelow(Figure16)thezeroxcoordinateisatthestartof telemonitoring. CSIROTelehealthTrialFinalReportMay2016 Page61of187 Figure16sqrt(MBSCosts)plottedfor(a)Testpatientsand(b)Controlpatientsat30dayintervals. Linearregressionlinesarecalculatedafterremovalofoutliers,whicharemarkedinred LinearregressionwascarriedoutusingthefitcommandintheMATLABstatisticstoolbox.Outliers,markedinred areexcludedfromthelinearregression.Thecommandpredobswasusedtoplot95%PredictionIntervalsaslight dottedredlines.Notethatpredictionintervalsindicatea95%probabilitythatafutureobservationatxwillfall withinitsboundaries.Standardgoodnessoffitmeasures,includingSSE–sumofsquaresduetoerror,R2–the coefficientofdetermination,theR2valueadjustedfordegreeoffreedomandthestdError–fitstandarderroror rootmeansquareerrorarealsoavailable.Theseareusedtogetherwithone–wayanalysisofcovariance(anocova) todeterminewhethertheslopesoftheBEFOREandAFTERportionsofthelinearregressionlinesaredifferent. TheDifferencedata(Control-Test)issimilarlyanalysed,butwithouttheapplicationofanytransform. Figure17PlotofDifferences(Control-Test)forMBSexpenditureagainst30dayintervals IftheControlpatientswereexactlymatchedtoTestpatientsforMBSexpenditure,theBEFOREpartofthelinear fitwouldhaveazeroslopeandaninterceptveryclosetozeroasshowninFigure17.Acloselookattheplotof differencesshowsthattheslopeisinfactnegativeandtheinterceptatthepointofcommencementof telemonitoringis-$55.38onaverage,indicatingthatMBSexpenditureovera30dayperiodforTestpatientswas greaterthanthatforControlsatthattime.Ifprojectedoverayearthisdifferenceinexpenditureiscloseto$670. Fortheplotsshownabovethelinearregressionfitsandtheresultsoftheanocovaanalysisaregivenintabular formbelowinTable25. Significantdifferencesareindicatedby<0.05*,<0.01**and<0.001***. CSIROTelehealthTrialFinalReportMay2016 Page62of187 Table25Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–Allpatients BEFORE AFTER Slope Slope Sig 0.05098 -0.03953 CONTROL 0.1 (0.0293,0.0727) (-0.1305,0.0515) 0.0919 -0.2729 TEST <0.001** (0.0625,0.1213) (-0.4236,-0.1222) P 0.0268* 0.009** -0.9446 3.916 DIFF 0.1025 (Control-Test) (-2.073,0.1839) (-3.251,11.08) BEFORE Intercept 12.58 (12.13,13.02) 14.06 (13.47,14.66) -55.38 (-78.71,-32.05) AFTER Intercept 12.98 (12.29,13.66) 14.44 (13.33,15.55) -30.91 (-83.66,21.84) Table25showsthattheonlysignificantdifferencewasintheslopeoftheBEFOREsegmentandtheslopeofthe AFTERsegmentforTestpatients,indicatingthattherewasasignificantreductioninMBSexpenditurefollowing thestartoftelemonitoring. Asimilaranalysiswasundertakenforsubgroupswithinthetotalpatientcohorttotestwhethertheseresultswere differentformale(67;Table26)andfemale(33;Table27)participants,patientswithpredominantly cardiovascular(50;),respiratory(30;Table29)ordiabeticdisease(20;Table30),andthosewhoweremonitored withinacommunityenvironment(62;Table31)orwithinahospitalenvironment(38;).Thesetablesareprovided below. Table26Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–MALEpatientsonly BEFORE AFTER Slope Slope Sig 0.0565 -0.101 CONTROL 0.0212* (0.0343,0.0788) (-0.3048,0.1028) 0.085 -0.3023 TEST <0.001*** (0.0612,0.1088) (-0.5747,-0.0298) P 0.08 0.2 0.002462 2.48 DIFF 0.4614 (Control-Test) (-1.303,1.308) (-6.512,11.47) BEFORE Intercept 12.48 (12.03,12.92) 13.65 (13.17,14.13) -43.13 (-68.65,-17.62) AFTER Intercept 13.55 (12.05,15.05) 14.41 (12.4,16.41) -18.25 (-84.72,48.22) Table27Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–FEMALEpatientsonly. BEFORE AFTER Slope Slope Sig 0.05126 -0.0638 CONTROL 0.167 (0.0202,0.0823) (-0.2345,0.1068) 0.05415 -0.3003 TEST 0.0025** (0.0165,0.0918) (-0.6168,0.0162) P 0.904 0.1568 -0.8574 5.585 DIFF 0.1733 (Control-Test) (-2.511,0.7962) (-6.333,17.5) BEFORE Intercept 13.04 (12.41,13.67) 13.99 (13.23,14.75) -50.77 (-85.98,-15.56) AFTER Intercept 12.72 (11.52,13.93) 14.67 (12.4,16.95) -67.11 (-148.7,14.51) CSIROTelehealthTrialFinalReportMay2016 Page63of187 Table28Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–CARDIACpatientsonly BEFORE AFTER Slope Slope Sig 0.0728 -0.1134 CONTROL 0.03* (0.0397,0.1058) (-0.2965,0.0697) 0.1039 -0.1973 TEST 0.0024** (0.0681,0.1396) (-0.4004,0.0058) P 0.1999 0.4964 -1.324 0.835 DIFF 0.605 (Control-Test) (-2.946,0.2974) (-7.975,9.645) BEFORE Intercept 13.01 (12.33,13.69) 14.31 (13.58,15.03) -65.39 (-98.14,-32.64) AFTER Intercept 13.29 (11.91,14.67) 13.73 (12.25,15.22) 3.024 (-63.86,69.91) Table29Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–RESPIRATORYpatientsonly BEFORE AFTER Slope Slope Sig 0.0881 0.0567 CONTROL 0.7152 (0.0524,0.1239) (-0.0963,0.2097) 0.0708 -0.3984 TEST <0.001*** (0.0348,0.1067) (-0.6472,0.1497) P 0.4878 0.0024** 0.8285 12.94 DIFF 0.004** (Control-Test) (-0.894,2.551) (5.511,20.37) BEFORE Intercept 13.16 (12.41,13.9) 13.34 (12.63,14.06) 4.638 (-30.74,40.01) AFTER Intercept 12.69 (11.53,13.84) 15.17 (13.29,17.05) -89.32 (-144,-34.65) Table30Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–DIABETICpatientsonly BEFORE AFTER Slope Slope Sig -0.0054 -0.0043 CONTROL 0.9907 (-0.0407, (-0.217,0.2084) 0.0299) 0.0956 -0.3345 TEST 0.0022** (0.0491,0.1421) (-0.6846,0.0156) P <0.001*** 0.0839 -1.221 8.573 DIFF 0.0924 (Control-Test) (-3.457,1.016) (-3.84,20.99) BEFORE Intercept 11.36 AFTER Intercept 12.39 (10.60,12.11) (10.83,13.94) 14.66 (13.67,15.65) -68.56 (-115.8,-21.33) 16.08 (13.56,18.6) -93.61 (-182.9,-4.336) Table31Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–COMMUNITYmonitoredpatients BEFORE AFTER Slope Slope Sig 0.0497 -0.1053 CONTROL 0.0162** (0.0265,0.073) (-0.2635,0.0530) 0.0755 -0.4224 TEST <0.001*** (0.0475,0.1035) (-0.6647,-0.18) P 0.1558 0.0257* -0.5152 -0.028 DIFF 0.9 (Control-Test) (-1.794,0.7639) (-12.07,12.02) BEFORE Intercept 12.32 (11.84,12.8) 14.22 (13.65,14.79) -71.88 (-96.83,-46.93) AFTER Intercept 13.67 (12.48,14.86) 15.35 (13.56,17.13) 3.119 (-85.54,91.77) CSIROTelehealthTrialFinalReportMay2016 Page64of187 Table32Linearregressionandanocovaanalysisforsqrt(MBSexpenditure)–HOSPITALmonitoredpatients BEFORE AFTER Slope Slope 0.0819 0.0542 CONTROL (0.0459,0.1179) (-0.0232,0.1315) 0.101 -0.1088 TEST (0.0592,0.1428) (-0.2545,0.0370) P 0.4883 0.0388 -0.4694 9.429 DIFF (Control-Test) (-2.295,1.357) (3.513,15.34) Sig 0.7308 0.0423* 0.0212 BEFORE Intercept 13.62 (12.85,14.38) 13.81 (12.97,14.65) -23.37 (-61.45,14.71) AFTER Intercept 11.84 (11.28,12.41) 13.38 (12.31,14.46) -82.55 (-126.1,-39.01) ImpactoftelemonitoringonMBSexpenditure Areviewofthesetablesleadstothefollowingconclusions; • • • ForeverysubgrouptherewasasignificantdecreaseinslopeAFTERthestartoftelemonitoring Formales,cardiacpatients,andcommunitybasedpatientstherewereapparentsignificantreductionsin slopeforcontrolpatientsbeforeandaftertheintervention.Theremaindershowednosignificant change. Additionalanocovaanalysiscomparingslopeofthecombinedbeforeandafterdataasasinglelinetothe beforedataalone,Figure18showedthatformalepatients,forcardiacpatientsandforpatients monitoredinthecommunity,therewasnosignificantdifferencewithP=0.9289,P=0.3582andP=0.5636 respectively. Figure18Linearregressionandanocovacomparisonofregressionlinebeforeintervention(redtrace)andregression linefullyextendedfortimeperiodsafterinterventionforALLMBSControls(bluetrace). • • AlthoughtherewereclearchangesinslopeforDifferences,theywereonlysignificantforrespiratory patients(P=0.004)andthosebeingmonitoredthroughhospitalprograms(P=0.0212) ThereweresignificantdifferencesintheslopeofBeforeandAfterdatabetweenTestandControl patients,overthethreeyearsprecedingtheintervention.Forallpatientsandfordiabeticpatientsthese differencesweresignificantwithP=0.0268andP<0.001respectively. CSIROTelehealthTrialFinalReportMay2016 Page65of187 IneverycaseotherthanforrespiratorypatientstheslopesforTestpatientswerehigherthanforControl patientsindicatingthatTestpatientswereingeneralincreasingtheirexpenditureonMBSitemsata fasterratethanControlpatients,suggestingthatinallprobabilitytheyweresicker.Thiscanbe demonstratedbycomparingtheannualrateofMBSexpenditureatthepointoftelemonitoring intervention.Thisisestimatedbyusingtheinterceptvalue,squaringitandapplyingthescalingfactor 365/30toobtainanestimateoftheperannumexpenditure. Table33EstimateofannualexpenditureonMBSItemsforallpatientcohorts PATIENTCOHORT Allpatients(N=100) Malepatientsonly(N=67) Femalepatientsonly(N=33) PatientswithCardiacdiseaseastheir primarydiagnosis(N=50) PatientswithRespiratorydiseaseas theirprimarydiagnosis(N=30) PatientswithDiabetesastheir primarydiagnosis(N=20) Patientsmanagedinacommunity setting(N=62) Patientsmanagedinahospital setting(N=38) • • TEST $2405 $2267 $2381 CONTROL $1925 $1895 $2069 $2491 $2059 $2165 $2107 $2615 $1570 $2460 $1847 $2320 $2257 TheTable33abovedemonstratesclearlythatonaverage,Testpatientsatthestartofthe telemonitoringinterventionhavesignificantlyhighercostsonMBSitemsthantheirmatchedControl patients.IftheseMBScostscanbeconsideredaproxyforgeneralwell-being(healthierindividuals generatelowerMBScosts),thenwecanconcludethatourTestpatientswereconsiderablysickerthan theirmatchedcontrols. ThelargestdifferencewasobservedfordiabeticpatientswhereTestpatientsgenerated$2,615ofMBS costsperannumwhilsttheircontrolsgenerated$1,570,morethanathousanddollarsless. TheestimatesofannualMBSexpenditurebasedonthelinearregressionspresentedintheprevioussection provideagraphicalrepresentationthatforalmosteverypatientcohortinthestudy,MBSexpenditureand itsrateofincreasewashigherforTestpatientsthantheirmatchedcontrols.PatientsfromtheACTand Tasmania,managedbyhospitalbasedcarecoordinatorsappeartohavebeenthemostcloselymatched withrespecttoMBSexpenditure. AnnualsavingsinMBSexpenditure • Thelinearregressionsforsqrt(30dayMBScosts)developedforTestpatients,ControlPatientsand Differences(Control-Test)provideabestfitestimateofexpenditurebeforeandafterintervention.To calculatingestimatesofperannumexpenditure,weneedtoconvertsqrt(30dayMBScosts)toannual costs.Asaresultthefunctionsbeforeandafterinterventionbecomequadraticandcalculationsof savingsrequirethedifferencingofpredictedcostsafteroneyearbasedonaprojectionofBEFOREdata oneyearpastthestartofintervention,andtheareaundertheTESTpatientcurveforoneyearpast intervention.ThisisshownbelowinsomedetailforMBScostsforallTestpatients. CSIROTelehealthTrialFinalReportMay2016 Page66of187 Figure19EstimateofimpactoftelemonitoringonMBSexpenditure • • InFigure19abovetheaverageageofTestpatientsatthestartofinterventionisusedasthereference point.Thelinearregressionforsqrt(MBScostsover30days)isconvertedtoannualexpenditureandis projectedforwardtopredictexpenditureatage72.ThetotalMBSexpenditurefortheyearis estimatedfromtheareaundertheannualexpenditurecurvefromage71toage72.Howeverfollowing intervention,theslopeoftheregressionlinechangesandtheareaofthecurvebeneaththeactual expenditurecurve,shownindarkblueestimatestheactualMBScostsforthatyear.Thedifference representsthesavingoveroneyear,estimatedtobe$720or28%oftheprojectedexpenditure. Howevertheassumptionthatthetwocurvesmeetexactlyattheonsetofinterventionisa simplificationthatmayover-estimatethesavings.Ifindeedtheimpactofinterventiontakessometime totakeeffect,wewouldexpectthepointofintersectiontofallsometimeafterthestartof telemonitoring,subjecttothevariabilityoftheexpendituredata. CSIROTelehealthTrialFinalReportMay2016 Page67of187 • ThisisinfactwhatisobservedinthemajorityofcasesasshowninFigure20below. Figure20EstimatesofannualMBSexpenditureforTESTpatients(red)andCONTROLpatients(blue),before(solid) andafter(dottedlines)intervention. Note:RegressionlinesforControlpatientsthatwerenotsignificantlydifferentafterintervention,areshownas simpleextensionoftheregressionlinebeforeintervention. CSIROTelehealthTrialFinalReportMay2016 Page68of187 ControlpatientsdidnotdemonstrateanysignificantchangesinregressionslopesotherthanforControlsfor HospitalMonitoredTestpatientswhodemonstratedasignificantdropintheirMBSexpenditureafterthe interventionof$624.Wenotethatthisdropisnotassociatedwithachangeinslope(P=0.7308)butratheradrop inMBSexpenditureimmediatelyafterthestartoftheinterventionontheTestpatients.Thereasonsforthisdrop cannotbeeasilyexplained,otherthantonotethatthispatientcohortissmall(N=38)andthesedataexhibit considerablenaturalvariability. TheestimatesofannualMBSexpenditurebasedonthelinearregressionspresentedintheprevioussection provideagraphicalrepresentationthatforalmosteverypatientcohortinthestudy,MBSexpenditureanditsrate ofincreasewashigherforTestpatientsthantheirmatchedcontrols.Theverylargedifferenceshownfordiabetes patientsmaybeafunctionofthesmallnumberofpatientsinthiscohort(N=20).PatientsfromtheACTand Tasmania,managedbyhospitalbasedcarecoordinatorsappeartohavebeenthemostcloselymatchedwith respecttoMBSexpenditure. Wealsonotethatthepointofintersectionofcostcurvesbeforeandafterinterventionforsixoftheeightpatient cohorts,fallbetween31daysforallpatientsand117daysforpatientswithrespiratorydisease.Itistemptingto speculatethatthisrepresentsthedelayfromthestartofinterventiontowhenaneffectonMBSexpenditure beginstohaveeffect. Estimatingbeforeandaftercosts,andthereforesavings,usingthemethodsoutlinedabove,arelikelytoresultin morerealisticestimates.Asanexample,overallsavingsinMBScostsbasedonthesimplifiedmethodshownin Figure19areestimatedat$720whilstwiththemorerobustmethoddescribedabovefallsto$611.Itislikelythat thebestestimateofsavingsinMBSexpenditureisbetween$611and$720perannum(seeTable34). CSIROTelehealthTrialFinalReportMay2016 Page69of187 Table34EstimatesofMBScostsandsavingsofTestpatientsoneyearbeforeandoneyearaftertheintervention PATIENTCOHORT % Predicted Estimated Reduction Predicted Actual RateofMBS RateofMBS RateofMBS inrateof AnnualCost AnnualCost Expenditure Expenditure Expenditure MBS ofMBS ofMBS atstartof atYear+1 atYear+1 expenditure itemsafter itemsafter Intervention (Without (With overone Intervention Intervention Intervention) Intervention) year % Savings inMBS expenses overone year Allpatients(N=100) $2,405 $2,803 $1,504 46.3 $2,602 $1,991 $611 23.5 Malepatientsonly(N=67) $2,267 $2,623 $1,401 46.6 $2,444 $1,914 $529 21.7 Femalepatientsonly(N=33) $2,381 $2,611 $1,477 43.5 $2,495 $2,001 $495 19.8 PatientswithCardiacdiseaseas theirprimarydiagnosis(N=50) $2,491 $2,951 $1,562 47.1 $2,719 $1,915 $804 29.6 PatientswithRespiratorydisease astheirprimarydiagnosis(N=30) $2,165 $2,454 $1,296 47.2 $2,308 $1,899 $409 17.7 PatientswithDiabetesastheir primarydiagnosis(N=20) $2,615 $3,046 $1,755 42.4 $2,828 $2,344 $484 17.1 Patientsmanagedina communitysetting(N=62) $2,460 $2,788 $1,269 54.5 $2,623 $1,975 $648 24.7 Patientsmanagedinahospital setting(N=38) $2,320 $2,752 $1,768 35.7 $2,534 $1,969 $564 22.3 CSIROTelehealthTrialFinalReportMay2016 Savingsin MBS Expenses overone year Page70of187 AnalysisofDifferences(Control–Test)forMBSexpenditure Intheestimateofcostsasoutlinedabove,nocompensationismadeforanychangesinControlthatmayhave occurredafterinterventionasnosignificantchangeswereobservedinsevenoutoftheeightpatientcohorts examined.Controlpatientsdidnotdemonstrateanysignificantchangesinregressionslopesotherthanfor ControlsforHospitalMonitoredTestpatientswhodemonstratedasignificantdropof$624intheirMBS expenditureaftertheintervention.ThisdropinMBSexpenditureofControlpatientscannotbeexplainedand maybesimplyaconsequenceofthedataspreadandtherelativelysmallnumberofpatients(N=38)inthiscohort. However,ifthisdropinMBSexpenditureforControlsistakenintoconsideration,thentherelativechangeinMBS expenditureforTestpatientsrelativetotheirControlsinthiscohortisnegligible,indeednegativeat-$60. ChangesinMBSexpenditureofTestpatientsrelativetotheirControlscanalsobeestimatedbyusingthelinear regressionequationsdevelopedfordifferencesbetweenControlandTestexpenditure,usingsimilarmethodsas outlinedabove. Sincenotransformwasappliedtodifferencedata,thereisnoneedtocalculateareas,asthemeanofendpoints atstartofinterventionandoneyearlaterwillprovidethesameresult.TheresultsareshownbelowinTable35. Table35EstimatesofMBSsavingsofTestPatientsrelativetoControlpatientsoneyearaftertheintervention,using differences(Control–Test). PATIENTCOHORT Diff Year0 Projected Projected Average Savings Diffat Average Diffafter relativeto Year1 Diff Intervention Controls Allpatients(N=100) -$674 -$812 -$743 -$85 $657 Malepatientsonly(N=67) -$525 -$524 -$525 -$38 $487 Femalepatientsonly (N=33) -$618 -$743 -$680 -$544 $136 PatientswithCardiac diseaseastheirprimary diagnosis(N=50) -$796 -$989 -$893 $99 $991 PatientswithRespiratory diseaseastheirprimary diagnosis(N=30) $56 $177 $117 $237 $120 PatientswithDiabetesas theirprimarydiagnosis (N=20) -$834 -$1,012 -$924 -$696 $228 Patientsmanagedina communitysetting(N=62) -$875 -$950 -$912 $36 $948 Patientsmanagedina hospitalsetting(N=38) -$284 -$353 -$319 -$539 -$220 Inthetableabove,savingsarecalculatedonthebasisthattherewerenosignificantchangesinControlsfollowing theintervention.TheresultsofcalculatingrelativesavingsinMBSexpenditureofTestandControlpatientsare broadlysimilar,asshowninTable36below; CSIROTelehealthTrialFinalReportMay2016 Page71of187 Table36ComparisonofMBSsavingscalculatedfromTestpatientsaloneandfromDifferences(Control-Test) Community ALL MALES FEMALES CARDIAC RESPIRATORY DIABETES Monitored (N=100) (N=67) (N=33) (N=50) (N=30) (N=20) (N=62) Hospital Monitored (N=38) UsingTEST PatientsOnly $611 $529 $495 $804 $409 $484 $648 -$60* Using DIFFERENCES $657 $487 $136 $991 $120 $228 $948 -$220 Average $634 $508 $316 $898 $265 $356 $798 -$140 *IncludescompensationforasignificantdecreaseinControlcostsforthispatientcohortafterintervention Itisencouragingthatforthetwolargestpatientcohortswheredataarelikelytobemostreliable,thedifferences betweenthetwomethodsarenegligible.ThedataabovesuggeststhatthegreatestperannumreductionsinMBS expenditurewereforCardiacpatients($898)andpatientsmonitoredinaCommunitysetting($798). Linearregressionanalysisofimpactoftelemonitoringinterventionon totalPBSexpenditure ThetimecourseofPBSexpenditurewasanalysedinamannersimilartothatusedforMBSexpenditure,although itwasnotedthatPBSdatashowedsignificantlyhighervariability.PBSdatawasprovidedinasimplerformatthan MBSdatawithDateofSupply,PatientContribution,GovernmentContributionandClassofdrugs(ATCCode) provided.ForourstudyweonlyconsideredtotalcostofPBSItems. Linearregressionwascarriedoutasbefore,usingthefitcommandintheMATLABstatisticstoolbox.Outliers, markedinredwereexcludedfromthelinearregression.Thecommandpredobswasusedtoplot95%Prediction IntervalsasdottedredlinesshowninFigure21.Notethatpredictionintervalsindicatea95%probabilitythata futureobservationatxwillfallwithinitsboundaries.Standardgoodnessoffitmeasures,includingSSE–sumof squaresduetoerror,R2–thecoefficientofdetermination,theR2valueadjustedfordegreeoffreedomandthe stdError–fitstandard[;;;orrootmeansquareerrorarealsoavailable.Theseareusedtogetherwithone–way analysisofcovariance(anocova)todeterminewhethertheslopesoftheBEFOREandAFTERportionsofthelinear regressionlinesaredifferent. Figure21sqrt(MBSCosts)plottedfor(a)Testpatientsand(b)Controlpatientsat30dayintervals.Linearregression linesarecalculatedafterremovalofoutliers,whicharemarkedinred TheDifferencedata(Control-Test)issimilarlyanalysed(Figure22),butwithouttheapplicationofanytransform. CSIROTelehealthTrialFinalReportMay2016 Page72of187 Figure22PlotofDifferences(Control-Test)forPBSexpenditureagainst30dayintervals Asbefore,iftheControlpatientswereexactlymatchedagainstPBSexpenditure,theBEFOREpartofthelinearfit wouldhaveazeroslopeandaninterceptveryclosetozero.Acloselookattheplotofdifferencesshowsthatthe slopeisinfactpositiveandtheinterceptatthepointofcommencementoftelemonitoringis$73.67onaverage, indicatingthatPBSexpenditureovera30dayperiodforControlpatientswasgreaterthanthatforTestpatients atthattime.IfprojectedoverayearthisdifferenceinPBSexpenditureiscloseto$896. ItisinterestingtonotethatforMBSexpenditure,expenditurewashigherforTestpatients.Fortheplotsshown abovethelinearregressionfitsandtheresultsoftheanocovaanalysisaregivenintabularforminTable37below. Significantdifferencesareindicatedby*<0.05,**<0.01and***<0.001. Table37Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–Allpatients BEFORE AFTER Slope Slope Sig 0.0824 0.1584 CONTROL 0.0462* (0.0671,0.0976) (0.1012,0.2155) 0.0408 -0.1717 TEST <0.001*** (0.0260,0.0557) (-0.2361,-0.1074) P P<0.001*** P<0.001*** 3.392 11.06 DIFF <0.0084** (Control-Test) (2.337,4.448) (4.842,17.27) BEFORE Intercept 16.5 (16.19,16.81) 15.66 (15.36-15.96) 73.67 (52.11,95.22) AFTER Intercept 15.39 (14.97,15.81) 16.03 (15.55,16.5) 6.51 (-39.23,52.25) TheanalysisaboveshowsthattheALLslopesofbeforeandaftersegmentsweresignificantlydifferent.TheAFTER slopeforControlpatientswasmarginallysignificant(P=0.046)butincreasedratherthandecreased.ForTest patients,theAFTERslopewassignificantlylowerthantheBEFOREslope(P<0.001).TheslopeofPBSexpenditure forControlpatientswasalsohigherthanforTestpatients,areversalofwhatwasobservedforMBSexpenditure. ThesedifferencesbetweenthetimecourseofPBSandMBSexpendituremaysuggestthatahigherPBS expenditureandbetteradherencetomedicationsschedulesmaybeassociatedwithabetterhealthcareoutcome andthusareducedexpenditureonMBSItems. Asimilaranalysiswasundertakenforsubgroupswithinthetotalpatientcohorttotestwhethertheseresultswere differentbetweenmale(67;Table38)andfemale(33;Table39)participants,patientswithpredominantly cardiovascular(50;Table40),respiratory(30;Table41)ordiabeticdisease(20;Table42),andthosewhowere monitoredwithinawithinacommunityenvironment(62;Table43)orwithinahospitalenvironment(38;Table 44).Thesetablesareprovidedbelow. CSIROTelehealthTrialFinalReportMay2016 Page73of187 Table38Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–MALEpatientsonly BEFORE AFTER Slope Slope Sig 0.0956 0.0616 CONTROL 0.4533 (0.0771,0.1140) (-0.0116,0.1349) 0.0491 -0.1965 TEST <0.001*** (0.0275,0.0707) (-0.3236,-0.0693) P 0.0015** <0.001*** 3.062 2.151 DIFF 0.7904 (-5.719,10.02) (Control-Test) (1.699,4.425) BEFORE Intercept 16.64 (16.26,17.02) 15.77 (15.33,16.2) 68.19 (40.71,95.67) AFTER Intercept 15.38 (14.85,15.9) 15.99 (15.05,16.93) 5.149 (-51.6,61.9) Table39Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–FEMALEpatientsonly BEFORE AFTER Slope Slope Sig 0.0714 0.3349 CONTROL <0.001*** (0.0441,0.0987) (0.1720,0.4979) 0.0309 -0.1605 TEST 0.0082** (-0.2949,(0.0031,0.0588) 0.0262) P 0.0392* <0.001*** 3.188 27.76 DIFF <0.001*** (Control-Test) (1.411,4.965) (21.56,33.96) BEFORE Intercept 16.62 (16.03,17.2) 15.35 AFTER Intercept 15.38 (14.18,16.58) 16.17 (14.79,15.9) (15.21,17.14) 82.01 (44.24,119.8) 11.33 (-34.29,56.95) Table40Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–CARDIACpatientsonly BEFORE AFTER Slope Slope Sig 0.0866 0.1395 CONTROL 0.4517 (0.0586,0.1146) (0.0707,0.2083) 0.046 -0.1893 TEST <0.001*** (-0.3542,(0.0287,0.0632) 0.0244) P 0.0164* <0.001*** 3.11 7.688 DIFF 0.3672 (Control-Test) (1.31,4.909) (-3.926,19.3) BEFORE Intercept 16.18 (15.61,16.75) 14.92 AFTER Intercept 14.19 (13.7,14.68) 15.56 (14.57,15.27) (14.49,16.63) 77.84 (41.55,114.1) -42.72 (-121.5,36.05) Table41Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–RESPIRATORYpatientsonly BEFORE AFTER Slope Slope 0.0678 0.0751 CONTROL (0.0389,0.0966) (-0.1863,0.3366) 0.0423 -0.0238 TEST (0.0156,0.0690) (-0.2801,0.2325) P 0.1903 0.5452 1.139 1.27 DIFF (Control-Test) (-0.1092,2.387) (-11.17,13.71) Sig 0.9343 0.4523 0.9728 BEFORE Intercept 16.44 (15.86,17.03) 16.04 (15.5,16.57) 28.28 (1.567,54.99) AFTER Intercept 16.45 (14.7,18.2) 15.66 (13.92,17.4) 73.59 (-17.95,165.1) CSIROTelehealthTrialFinalReportMay2016 Page74of187 Table42Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–DIABETICpatientsonly BEFORE AFTER Slope Slope Sig 0.0915 0.5278 CONTROL <0.001*** (0.0552,0.1279) (0.2302,0.8254) 0.0181 -0.3171 TEST <0.001*** (-0.0156,0.0518) (-0.4688,-0.1654) P 0.004** <0.001*** 4.283 47.2 DIFF <0.001*** (Control-Test) (2.28,6.285) (32.94,61.46) BEFORE Intercept 17.35 (16.61,18.09) 16.67 (16.02,17.33) 75.38 (37.52,117.2) AFTER Intercept 15.98 (13.79,18.17) 18.01 (16.89,19.13) -28.98 (-133.9,75.97) Table43Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–COMMUNITYmonitoredpatients BEFORE AFTER Slope Slope Sig 0.0485 0.0161 CONTROL 0.557 (0.03,0.0670) (-0.1197,0.152) 0.032 -0.2991 TEST <0.001*** (0.0121,0.0518) (-0.4387,-0.1595) P 0.2184 0.002** 0.6645 10.7 DIFF 0.004** (Control-Test) (-0.6433,1.972) (3.649,17.76) BEFORE Intercept 15.34 (14.98,15.71) 15.48 (15.09,15.86) -1.802 (-27.87,24.27) AFTER Intercept 14.79 (13.86,15.71) 16.51 (15.49,17.54) -61.48 (-113.4,-9.559) Table44Linearregressionandanocovaanalysisforsqrt(PBSexpenditure)–HOSPITALmonitoredpatients BEFORE AFTER Slope Slope 0.1479 0.0781 CONTROL (0.1132,0.1826) (-0.0862,0.2425) 0.0463 -0.0756 TEST (0.0204,0.0721) (-0.1922,0.0410) P <0.001*** 0.0986 7.311 13.68 DIFF (Control-Test) (5.267,9.356) (4.173,23.19) Sig 0.4386 0.0519 0.255 BEFORE Intercept 18.56 (17.85,19.27) 15.78 (15.27,16.28) 185.1 (144.8,225.4) AFTER Intercept 17.36 (16.18,18.54) 15.9 (15.04,16.75) 83.4 (18.2,148.6) ImpactoftelemonitoringonPBSexpenditure Areviewofthesetablesleadstothefollowingconclusions; • • ForallTestpatients(P<0.001)andmostsubgroupstherewasasignificantdecreaseinslopeAFTERthe telemonitoringintervention,exceptforRespiratorypatients(P=0.4523)andpatientsmonitoredinan Hospitalenvironment(P=0.0519)wherethedecreasewasvisiblebutwasnotsignificant ForthecompleteControlpatientcohorttherewasamarginallysignificant(P=0.0462)increaseinslope aftertheintervention,andverysignificantincreasesinslopeforFemalepatients(P<0.001)andDiabetic patients(P<0.001).HoweverfurtherancovaanalysiscomparingControldatabeforetothecombined before+afterdatathesethreepatientgroupsshowedthatinnocasewasthedifferenceinslope significant(Figure23),withPvaluesof0.1543,0.3523and0.1115respectively. CSIROTelehealthTrialFinalReportMay2016 Page75of187 Figure23Ancovaanalysisofdifferencesinslopeofbeforedatasegmenttocombinedbefore+afterdataforthe completepatientcohort(N=100).AsP>0.05theslopeswerenotdifferent. • • • • Howeversurprisingly,althoughtherewasnosignificantdifferenceinslopeforMalepatientsandthose sufferingfromcardiacdisease,ancovaanalysisofthesegmentbeforeinterventiontothecombined before+aftersegmentdidshowasignificantchange(P=0.0044andP=0.0222respectively)associated withasignificantdropintheinterceptoftheregressionline,belowthatforthedatabefore intervention. TheslopesbeforeandafterforDifferencedataweresignificantoverall(P=0.008),forfemalepatients (P<0.001),fordiabeticpatients(P=<0.001)aswellasforpatientsmonitoredincommunitysettings (P=0.004).Forallotherpatientcohorts,theslopesbeforeandafterchangedinthedirectionindicating thatcostsforTestpatientswerefallingaftertheintervention,butwerenotconsideredsignificant (P>0.05). ThereweresignificantdifferencesintheslopeofTestandControlpatientdata,overthethreeyears precedingtheintervention,forthetotalcohortofpatients(P<0.001),aswellasformalepatients (P<0.0015),femalepatients(P=0.0392),cardiacpatients(P=0.0164),diabeticpatients(P=0.004)and patientsmonitoredinhospitalenvironments(P<0.001).Differenceswerenotsignificantforrespiratory (P=0.1903)andpatientsmonitoredinthecommunity(P=0.6645). Forthetotalpatientcohort,theslopesofcontrolsweresignificantlylargerthantheslopeofTestdata afterthetelemonitoringintervention.Thiswasobservedforeverypatientcohortotherthanfor respiratorypatients(P=0.5452)andpatientsmonitoredinhospitalsettings(P=0986). CSIROTelehealthTrialFinalReportMay2016 Page76of187 DifferencesinPBSexpenditureatthestartoftelemonitoringcanbeeasilyestimatedasbeforebyusingthe interceptvalue,squaringitandapplyingthescalingfactor365/30toobtainanestimateoftheperannum expenditure.Astheseestimatesarebasedonathreeyearhistorytheyarelikelytobereliable. Table45EstimateofannualexpenditureonPBSItemsforallpatientcohorts PATIENTCOHORT Allpatients(N=100) Malepatientsonly(N=67) Femalepatientsonly(N=33) PatientswithCardiovasculardisease astheirprimarydiagnosis(N=50) PatientswithRespiratorydiseaseas theirprimarydiagnosis(N=30) PatientswithDiabetesastheir primarydiagnosis(N=20) Patientsmanagedinacommunity setting(N=62) Patientsmanagedinahospitalsetting (N=38) TEST $2984 $3026 $2867 CONTROL $3312 $3369 $3361 $2708 $3185 $3130 $3288 $3381 $3662 $2916 $2863 $3030 $4191 Table45abovedemonstratesthatControlpatientsatthestartofthetelemonitoringinterventionhavegenerally higherPBSexpenditurethanTestpatients,butthesedifferencesarenotlikelytobesignificant.Thisisthe oppositetowhatwasobservedforMBSexpenditureanditistemptingtosuggestthatTestpatientsweresicker (higherMBSexpenditure)becausetheywereeitherlessadherentwiththeirmedicationsregimeorwereundermedicatedfortheircondition.OverallControlpatientsspent$328morethanTestpatientsperannumontheir medications.Thelargestperannumdifferenceof$1,161wasobservedforpatientsmanagedinaHospitalsetting. Thisdifferenceisdifficulttoexplain. AnnualsavingsinPBSexpenditure Thelinearregressionsforsqrt(30dayPBScosts)developedforTestpatients,ControlPatientsandDifferences (Control-Test)provideabestfitestimateofexpenditurebeforeandafterintervention.Beforecalculatingreal costs,weneedtoconvertsqrt(30dayPBScosts)toannualcosts.Asaresultthefunctionsbeforeandafter interventionbecomequadraticandcalculationsofsavingsrequirethedifferencingofpredictedcostsafterone yearbasedonaprojectionofBEFOREdataoneyearpastthestartofinterventionandtheareaundertheTEST patientcurveforoneyearpastintervention.ThisisshownbelowinsomedetailforPBScostsforallTestpatients. Figure24EstimationofsavingsonPBSExpenditurecurveprojectedforwardoneyear CSIROTelehealthTrialFinalReportMay2016 Page77of187 InFigure24abovetheaverageageofTestpatientsatthestartofinterventionisusedasthereferencepoint.The linearregressionforsqrt(PBScostsover30days)isconvertedtoannualexpenditureandisprojectedforwardto predictexpenditureatage72.NotethatthepredictedrateofannualPBSexpenditureintheabsenceofthe telehealthinterventionwas$3,176,andthiswasreducedby29.5%to$2,240. ThetotalsavingsinPBSexpenditurefortheyearcanbeestimatedfromtheareaundertheannualexpenditure curvefromage71toage72beforeandafterintervention.Followingintervention,theslopeoftheregressionline changesandtheareaofthecurvebetweenthepredictedandtheactualexpenditurecurve,shownindarkblue estimatestheactualPBScostsforthatyear.Thedifferencerepresentsthesavingoveroneyear,estimatedtobe $476or15%oftheprojectedexpenditure. Howevertheassumptionthatthetwocurvesmeetexactlyattheonsetofinterventionisasimplificationthatmay over-estimatethesavings.Ifindeedtheimpactofinterventiontakessometimetotakeeffect,wewouldexpect thepointofintersectiontofallsometimeafterthestartoftelemonitoring,subjecttothevariabilityofthe expendituredata. TheestimatesofannualPBSexpenditurebasedonthelinearregressionspresentedinFigure24,providea graphicalrepresentationthatoverallPBSexpenditureanditsrateofincrease,washigherforControlpatients thanTestpatients.TheonlyexceptionappearstobeforCommunitybasedpatientswhoatthepointof interventionwerecloselymatchedtotheircontrols. ThelargestdifferenceinPBSexpenditureatthestartofinterventionwasforpatientsmonitoredbyhospitalbased services.Wealsonotethatthepointofintersectionofcostcurvesbeforeandafterinterventionforsevenofthe eightpatientcohorts,fallbetween27and129days.Thelongestdelaybeforeanimpactisobservedwas129days forfemalepatientsand120daysfordiabeticpatients.Itistemptingtospeculatethatthisrepresentsthedelay fromthestartofinterventiontowhenaneffectonPBSexpenditurebeginstobenoticed. CSIROTelehealthTrialFinalReportMay2016 Page78of187 Figure25EstimatesofannualPBSexpenditureforPBSTestpatients(red)andControlpatients(blue),before(solid lines)andafter(dottedlines)intervention. Note:RegressionlinesforControlpatientsthatwerenotsignificantlydifferentafterinterventionareshownasa simpleextensionoftheregressionlinebeforeintervention. Estimatingbeforeandaftercostsandthereforesavings,usingthemethodsoutlinedabove,arelikelytoresultin morerealisticestimates.Asanexample,overallsavingsinPBScostsbasedonthesimplifiedmethodshownin Figure25areestimatedat$476whilstwiththemorerobustmethoddescribedabovefallsto$354(seeTable46). ItislikelythatthebestestimateofsavingsinPBSexpenditurelieswithinthisrange. CSIROTelehealthTrialFinalReportMay2016 Page79of187 Table46EstimatesofPBScostsandsavingsforTestpatientsoneyearaftertheintervention PATIENTCOHORT PredictedRate Estimated %Reduction Predicted RateofPBS ofPBS RateofPBS inrateof ActualAnnual AnnualCost Expenditure Expenditureat Expenditure PBS CostofPBS ofPBSitems atstartof Year+1 atYear+1 expenditure itemsafter before Intervention (Without (With overone Intervention Intervention Intervention) Intervention) year % Savings inPBS expenses overone year Allpatients(N=100) $2,984 $3,176 $2,365 25.5 $3,080 $2,726 $354 11.5 Malepatientsonly(N=67) $3,026 $3,259 $2,250 31.0 $3,142 $2,665 $477 15.2 Femalepatientsonly(N=33) $2,867 $3,009 $2,459 18.3 $2,938 $2,757 $181 6.2 PatientswithCardiacdiseaseastheir primarydiagnosis(N=50) $2,708 $2,915 $2,138 26.7 $2,812 $2,504 $308 10.9 PatientswithRespiratorydiseaseas theirprimarydiagnosis(N=30) $3,130 $3,334 $2,874 13.8 $3,232 $2,929 $303 9.4 PatientswithDiabetesastheirprimary diagnosis(N=20) $3,381 $3,471 $2,437 29.8 $3,426 $3,068 $358 10.4 Patientsmanagedinacommunity setting(N=62) $2,916 $3,064 $2,016 34.2 $2,990 $2,587 $403 13.5 Patientsmanagedinahospitalsetting (N=38) $3,030 $3,250 $2,730 16.0 $3,139 $2,899 $240 7.7 CSIROTelehealthTrialFinalReportMay2016 Savingsin PBS Expenses overone year Page80of187 AnalysisofDifferences(Control–Test)forPBSexpenditure Intheestimateofcostsasoutlinedabove,nocompensationismadeforanychangesinControlthatmayhaveoccurred afterinterventionasinmostcases,otherthanforMalepatientsandCardiacpatientsnosignificantchangeswere observedwhenancovaanalysiswasusedtotestslopesofthecombinedbeforeandaftersegments.Howeverfor FemaleControlpatientsandfordiabeticControlpatients(Figure26),therewasahighlysignificant(P<0.001)increase inslopeafterthestartofinterventionwhichcannotbeexplained.ThisincreaseinPBSexpenditureoveroneyearwas estimatedas$265forFemalepatientsand$696forDiabeticpatients.ThereductioninPBScostsforthesetwoTest patientgroupsrelativetotheircontrolsthusincreasesto$446and$1,054respectively. Figure26sqrt(30dayPBSExpenditure)for(A)FemalePatients(N=33)and(B)DiabeticPatients(N=20) HowevertheeffectofchangesinPBSexpenditurebyControlscanalsobeaccountedforbyusingthelinearregression equationsdevelopedfordifferencesbetweenControlandTestexpenditure,usingsimilarmethodsasoutlinedabove. Sincenotransformwasappliedtodifferencedata,thereisnoneedtocalculateareas,asthemeanofendpointsat startofinterventionandoneyearlaterwillprovidethesameanswer.TheresultsareshownbelowinTable47. Table47EstimatesofPBSsavingsoneyearaftertheintervention,usingdifferences(Control-Test) PATIENTCOHORT Projected Difference Difference Year0 atYear1 Average Projected Difference Average after Difference Intervention Changein Control-Test After Intervention Allpatients(N=100) Malepatientsonly(N=67) Femalepatientsonly(N=33) $896 $830 $998 $1,398 $1,283 $1,470 $1,147 $1,056 $1,234 $1,192 $222 $2,295 $44 -$834 $1,062 PatientswithCardiacdiseaseas theirprimarydiagnosis(N=50) $947 $1,407 $1,177 $49 -$1,128 PatientswithRespiratorydisease astheirprimarydiagnosis(N=30) $344 $513 $428 $989 $561 PatientswithDiabetesastheir primarydiagnosis(N=20) $917 $1,551 $1,234 $3,267 $2,033 Patientsmanagedinacommunity setting(N=62) -$22 $76 $27 $222 $195 $2,252 $3,334 $2,793 $2,027 -$766 Patientsmanagedinahospital setting(N=38) CSIROTelehealthTrialFinalReportMay2016 Page81of187 TheresultsoftheinterventiononPBSexpenditureareconsiderablymoredifficulttointerpretbecauseanumberof ControlpatientcohortsshowedasignificantchangeintheirPBSexpenditurefollowingthestartofinterventionas showninTable48. Table48ComparisonofPBSsavingscalculatedfromTestpatientsaloneandfromDifferences(Control-Test) Savingsareshownaspositivevaluesandincreasesareshownasnegativevalues Community Hospital ALL MALES FEMALES CARDIAC RESPIRATORY DIABETES Monitored Monitored (N=100) (N=67) (N=33) (N=50) (N=30) (N=20) (N=62) (N=38) SavingsUsingTest $354 $477 $181 $308 $303 $358 $403 $240 PatientsOnly SavingsUsing $260 $590 -$265 $642 -$23 -$696 $278 $740 ControlsOnly* NetSavingsrelative $94 -$113 $446 -$334 $326 $1,054 $125 -$500 toControls FromDifferences $44 -$834 $1,062 -$1,128 $561 $2,033 $195 -$766 AverageDifference (FallinTestrelative $69 -$474 $754 -$731 $444 $1,544 $160 -$633 toControls) *AssumingthatallchangesinControlafterinterventionwerestatisticallysignificant Therelativesavingscalculatedfromdifferences(row4)broadlymatchthosecalculatedfromTestpatientsrelativeto theircontrols(row3).Anegativevalueinrow5oftheTableabovemeansthattherewasanincreaseinthePBS expenditureofTestpatientsrelativetotheirControls.ThiswasobservedMalepatients,Cardiacpatientsandthose beingmonitoredinahospitalenvironmentwherethefallinPBSexpenditurewasgreaterforControlsthanforTest patients.Wehavenoexplanationfortheseobservations. Anincreaseintheslopeof(Control-Test)differencesaftertheinterventionmeanseitherthatPBScostsforControls haveincreased,PBScostsfordiabeticpatientshavedecreased,orthatbothhaveoccurredsimultaneously.Anincrease inslopeandareductionintheinterceptcanbeinterpretedtoindicatethattheeffectoftheinterventionisonly observedafterasignificanttimedelay. FromTables38-45wenotethatforControlpatientstherewasamarginallysignificantincrease(P=0.046)intheoverall rateofPBSexpenditureafterintervention,andahighlysignificantincrease(P<0.001)bothforFemalepatientsand Diabeticpatients.Inaddition,althoughtherewasnosignificantdifferenceinslopeformalepatientsandthose sufferingfromcardiacdisease,beforeandafterintervention,anocovaanalysisofthesegmentbeforeinterventionto thecombinedbefore+aftersegmentdidshowasignificantchange(P=0.0044andP=0.0222respectively),associated withashiftdownwardsintheintercept,butnosignificantchangeinslope. TheseeffectsoftheinterventiononControlpatientdataaredifficulttoexplain,otherthantonotethatFemale patients(N=33)andDiabeticpatients(N=20)arerelativelysmallcohorts.Thiscannotbesaidofmalepatients(N=67) andcardiacpatients(N=50),butwenotethat68%ofpatientswithcardiacconditionsweremale. SimilarlythereweresignificantincreasesinslopesofDifferencesoverall(P<0.008),aswellasforFemalepatients (P<0.001)andDiabeticpatients(P<0.001).ThisisconsistentwithanincreaseinPBScostsofControlpatientsaswellasa decreaseinPBSexpenditureofequivalentTestpatientcohort. CSIROTelehealthTrialFinalReportMay2016 Page82of187 5.4 AnalysisofHospitalData–Numberofadmissionsandlengthofstay HospitalDatawasintendedtobesourcedforallTestandControlpatientsselectedfromhospitallistsateachofthesix testsites.HoweverthemajorityofTestandControlpatientsinVICandNSWandasignificantnumberfromQLDwere notselectedfromhospitallistsandtheirhospitaldatawerethusnotavailableforanalysis.Thefinalselectionof53Test and64ControlpatientsforwhichhospitaldatawasavailableisshowninTable49below; Table49SelectionofTestandControlpatientsforanalysisofhospitaladmissionsandLOS EligiblePatientsin HospitalLists PatientsSelected fromHospitalLists Patientsselected fromoutside HospitalList AllPatientsSelected Patientswithdrawn Patientsdied Patientsmatched forPBS/MBS Analysis Patientsmatched foranalysisof hospitaladmission andLOS PatientsRejected foranalysisof hospitaladmission andLOS Finalpatients matchedforanalysis ofhospital admissionandLOS TAS ACT HospitalBased VIC 210 282 520 NSW QLD CommunityBased 230 TOTAL 187 1429 T C T C T C T C T C T C 29 56 16 22 0 1 7 4 19 27 71 110 - 4 - 1 26 48 10 8 7 2 43 63 29 7 4 60 - 7 16 2 1 23 - 3 26 1 2 49 - 2 17 6 - 12 - - 26 2 1 29 - 2 114 18 8 173 - 14 25 55 13 19 25 35 14 8 23 20 100 137 25 52 13 19 13 13 12 3 23 20 86 107 2 18 1 3 13 13 12 3 5 6 33 43 23 34 12 16 - - - - 18 14 53 64 Ofthe53TestPatientsselected,29sufferedfromHeartDisease,21sufferedfromRespiratorydiseaseand3were diabetics.Theaverageagewas70.8±8.7years,notsignificantlydifferentfromthelargercohort. FortheavailableTestandControlpatientsforwhichdatawasavailable,alladmissionsinvolvingatleastoneovernight staywerecountedandsummedovertimeintervalsof100daysbeforeandafteradmission.Thetimeperiodof100 dayswasselectedratherthanthe30dayintervalsselectedforPBSandMBSexpenditureashospitaleventsaremuch lessfrequentandwouldgeneratealargenumberofzeroentriesoveranyparticular30dayinterval.Hospitaladmission andLengthofStay(LOS)datawasnormallydistributedanddidnotrequireanytransformationpriortoanalysis. ThetimecourseofchangesinthenumberofadmissionsandLOSwereanalysedinamannersimilartothatusedfor PBSandMBSexpenditure. Linearregressionanalysisofnumberofadmissions Linearregressionwascarriedoutasbefore,usingthefitcommandintheMATLABstatisticstoolbox.Outliers,markedin redwereexcludedfromthelinearregression.Thecommandpredobswasusedtoplot95%PredictionIntervalsas dottedredlines.Notethatpredictionintervalsindicatea95%probabilitythatafutureobservationatxwillfallwithin CSIROTelehealthTrialFinalReportMay2016 Page83of187 itsboundaries.Standardgoodnessoffitmeasures,includingSSE–sumofsquaresduetoerror,R2–thecoefficientof determination,theR2valueadjustedfordegreeoffreedomandthestdError–fitstandarderrororrootmeansquare errorarealsoavailable.Theseareusedtogetherwithone–wayanalysisofcovariance(anocova)todeterminewhether theslopesoftheBEFOREandAFTERportionsofthelinearregressionlinesaredifferent(Figure27). Figure27FitoflinearregressionlinesforNumberofHospitaladmissionsover100dayintervalsbeforeandafter intervention Asbefore,iftheControlpatientswereexactlymatchedagainstPBSexpenditure,theBEFOREpartofthelinearfitof Differenceswouldhaveazeroslopeandaninterceptveryclosetozero.Acloselookattheplotofdifferencesshows thattheslopeisinfactnegativeandtheinterceptatthepointofcommencementoftelemonitoringisalmostexactly 0.5admissions/annum.ThisindicatesthatthenumberofadmissionswasgreaterforTestpatientsovertheperiodprior tointerventionandjustatthestartofintervention. Fortheplotsshownabovethelinearregressionfitsandtheresultsoftheanocovaanalysisaregivenintabularformin Table50below.Significantdifferencesareindicatedby*<0.05,**<0.01and***<0.001. Table50ResultsofregressionanalysisofNumberofHospitalAdmissionsforBeforeandAfternumberofadmissions BEFORE AFTER Slope Slope Sig 0.0311 0.0661 CONTROL 0.4576 (0.0137,0.0485) (-0.0432,0.1754) 0.0402 -0.1109 TEST 0.0094** (0.0215,0.0588) (-0.2592,0.0374) P 0.4429 0.0145* DIFF -0.0107 0.177 0.0018** (Control(-0.0295,0.0082) (0.1146,0.2393) Test) BEFORE Intercept 0.5463 (0.423,0.6696) 0.6998 (0.5678,0.8318) -0.1361 AFTER Intercept 0.2624 (-0.0368,0.5617) 0.8011 (0.3949,1.207) -0.5387 (-0.2727,0.0005) (-0.7095,-0.3678) CSIROTelehealthTrialFinalReportMay2016 Page84of187 Impactoftelemonitoringonnumberofadmissions ThelinearregressionanalysisshowninTable51showsthatthechangeinslopeBeforeandAfterinterventionwas significantonlyforTestpatients(P=0.0094)andforDifferencedata(P=0.0018),butwasnotsignificantforControl patients.Additionalconfirmationthattherewasnosignificantdifference(P=0.2342)forControlswasfromtheancova analysisofControldatabeforeandthecombinedBeforeandAfterdata.Similarlytherewerenosignificantdifferences inslopeforTestandControlpatientsbefore(P=0.6629),butthedifferencesinslopeweresignificant(P=0.0145)after intervention. Assumingthatthereferencepointisusedasthestartofinterventionitiseasytocalculatethatonaveragethe predictedrateofadmissionwouldfallby53%andthetotalnumberofadmissionsoveroneyearwouldbereducedby almostoneadmissionperannum. Table51Resultsofinterventiononnumberandrateofhospitaladmissionsperannumusingsimplifyingassumptions Rateof Predicted Estimated % Predicted Actual Reduction %Change Admissions Rateat Rateat Change Number Number inNumber inNumber atstartof Year+1 Year+1 inRate Admissions Admissions Admissions Admissions Intervention (N/annum) (N/annum) inYearafter inYearafter overone overone (N/annum) Intervention Intervention year year (N/annum) (N/annum) (N/annum) 2.55 3.09 1.45 53.2% 2.82 1.82 1.00 35.7% Howeveraswasdiscussedpreviously,thebestestimateoftheimpactofinterventionmaybeshowndiagrammatically asshownbelowinFigure28. Figure28Estimateofimpactofinterventiononnumberofadmissionsperannum. Note:RedlineisforTestpatientsandbluelineisforControlPatients.SolidlinesareforresponseBeforeintervention anddottedlinesrepresentresponseAfterIntervention.AstheslopesofControlsbeforeandafterwerenotsignificant, theControlAfterresponseisrepresentedasacontinuationoftheBeforeresponse. Intheabovefiguretheinterceptatwhichtherateofannualadmissionsbeginstochangeis67days.Itisreasonableto assumethatittakesalittleovertwomonthsbeforetheimpactofinterventionoftherateofadmissionbeginstotake effect.Fromthesegraphicalestimatethefollowingdatamaybeeasilyderived. CSIROTelehealthTrialFinalReportMay2016 Page85of187 Table52EstimatedimpactofInterventiononnumberofadmissionsperannum Rateof Predicted Estimated % Predicted Actual Reduction %Change Admissions Rateat Rateat Change Number Number inNumber inNumber atstartof Year+1 Year+1 inRate Admissions Admissions Admissions Admissions Intervention (N/annum) (N/annum) inYearafter inYearafter overone overone (N/annum) Intervention Intervention year year (N/annum) (N/annum) (N/annum) 2.55 3.09 1.45 53.2% 2.82 2.15 0.67 23.8% Itisthereforelikelythattheeffectoftheinterventionwastoreducetherateofadmissionby53%resultinginan averagereductioninhospitaladmissionsfollowinginterventionofbetween0.67and1.0admissionsperannum (seeTable52). Analysisofdifferences(Control–Test)fornumberofadmissions Intheestimateoftheeffectofinterventiononthenumberofadmissionscarriedoutabove,nocompensationismade foranychangesinControlthatmayhaveoccurredafterinterventionasnosignificantdifferenceswerenotedinControl patientsbeforeandafterintervention,andnosignificantchangeswereobservedwhenancovaanalysiswasusedto testslopesofthecombinedbeforeandaftersegments. HowevertheeffectofchangesinNumberofAdmissionsforControlpatientscanbeaccountedforbyusingthelinear regressionequationsdevelopedfordifferencesbetweenControlandTestexpenditure,usingsimilarmethodsas outlinedabove.Sincenotransformwasappliedtodifferencedata,thereisnoneedtocalculateareas,asthemeanof endpointsatstartofinterventionandoneyearlaterwillprovidethesameanswer.Amoreaccurateresultcanthenbe calculatedusingtheinterceptbetweentheBeforeandAfterdataasshowninFigure29. Figure29LinearregressionofdifferencesforNumberofadmissions/annum ThedataaboveinFigure29showsthatthefirsteffectoftheinterventionisobserved214daysafterthestart.The resultsfromtheanalysisofthelinearregressionfordifferencesareshowninTable53. . CSIROTelehealthTrialFinalReportMay2016 Page86of187 Table53EstimatesofNumberofadmissionsoneyearaftertheintervention,usingdifferences(Control-Test) PATIENTCOHORT (Differences) Allpatients(N=53) Difference Projected Year0 Difference atYear1 (days) (days) -0.50 -0.64 Difference Projected atYear1 Average after Difference intervention (days) (days) 0.39 -0.57 Average Difference after Intervention -0.35 Changein Control-Test After Intervention 0.22 TheresultsobtainedfromdifferencesarelowerthanobtaineddirectlyfromTestdatainpartbecausetheintercept occurslaterat214days.Howeverthedifferencedataalsoshowsthatafteroneyearofinterventiontherateof admissionforTestpatientsrelativetoControlsis1.03admission/annumlessthanthatpredictedwithoutthe intervention. LinearregressionanalysisofLengthofStay(LOS) LengthofStay(LOS)wasanalysedinasimilarmannertonumberofadmissions.Linearregressionwascarriedoutas before,usingthefitcommandintheMATLABstatisticstoolbox.Outliers,markedinredwereexcludedfromthelinear regression.Thecommandpredobswasusedtoplot95%PredictionIntervalsasdottedredlinesasshownin Figure30.Notethatpredictionintervalsindicatea95%probabilitythatafutureobservationatxwillfallwithinits boundaries.Standardgoodnessoffitmeasures,includingSSE–sumofsquaresduetoerror,R2–thecoefficientof determination,theR2valueadjustedfordegreeoffreedomandthestdError–fitstandarderrororrootmeansquare errorarealsoavailable.Theseareusedtogetherwithone–wayanalysisofcovariance(anocova)todeterminewhether theslopesoftheBEFOREandAFTERportionsofthelinearregressionlinesaredifferent. Figure30FitoflinearregressionlinesforLengthofStay(LOS)over100dayintervalsbeforeandafterintervention CSIROTelehealthTrialFinalReportMay2016 Page87of187 ThegraphicaldatashownaboveandsupportedbytheresultsoflinearregressiongiveninTable54belowindicatethat Testpatientswereconsiderablymorelikelytobeadmittedtohospitalthantheircontrols. Table54ResultsofregressionanalysisofLengthofStay(LOS)forBeforeandAfterintervention BEFORE AFTER Slope Slope 0.1452 0.1 CONTROL (0.0669,0.2235) (-1.836,2.036) 0.3597 -1.038 TEST (0.2049,0.5145) (-2.791,0.7141) P 0.0125* 0.1339 -0.2145 1.138 DIFF (-0.3883,-0.0407) (0.5418,1.735) Sig 0.869 0.006** <0.01** BEFORE Intercept 2.739 (2.186,3.293) 5.424 (4.329,6.518) -2.685 (-3.914,-1.455) AFTER Intercept 2.785 (-2.516,8.086) 5.957 (1.158,10.76) -3.172 (-4.806,-1.539) ImpactofinterventiononLengthofStay(LOS) Followingthestartofintervention,Testpatientsexperiencedasignificant(P=0.006)reductionintheirrateofhospital staysrelativetotheircontrols(P=0.869).Inadditiontherewasasignificantdifference(P=0.0125)inslopesforTestand Controlpatientsbeforeintervention,withTestpatientsshowinganaveragelengthofstayof19.8daysasagainst10.0 daysforcontrolsatthestartofintervention.ThiswouldsuggestthatTestpatientswereconsiderablymoreillthantheir Controls. Asbothnumberofadmissionsandlengthofstaywereanalysedwithoutanytransformation,theimpactof telemonitoringcanbereadilyanalysedfromtheregressionanalysisshowninTable55.Assumingthatthestartof interventionisusedasthereferencepointisusedasitiseasytocalculatethatonaveragethepredictedrateoflength ofstaywouldfallbyalmost76%,andthetotallengthofstayoveroneyearwouldbereducedbyapproximately9.3 daysperannum. Table55Resultsofinterventiononlengthofstay(LOS)perannumusingsimplifyingassumptions RateofLOS Estimated Estimated % Predicted Estimated Estimated %Change atstartof RateofLOS RateofLOS Change LOSover LOSinYear reduction inLOSover Intervention oneyear oneyear inRate oneyear after inLOSover oneyear (days) after, after ofLOS without Intervention oneyear without intervention Intervention (days) (days) intervention (days) (days) (days) 19.8 24.6 6.0 75.7% 22.2 12.9 9.3 41.9% CSIROTelehealthTrialFinalReportMay2016 Page88of187 Howeveraswasdiscussedpreviously,thebestestimateoftheimpactofinterventionmaybeshowninFigure31 below,wheretheinterceptbetweentheresponsebeforeinterventionandafterinterventioniscalculatedas38days. Figure31EstimateofimpactofinterventiononLOSperannum. Note:RedlineisforTestpatientsandbluelineisforControlPatients.SolidlinesareforresponseBeforeintervention anddottedlinesrepresentresponseAfterIntervention.AstheslopesofControlsbeforeandafterwerenotsignificant, theControlAfterresponseisrepresentedasacontinuationoftheBeforeresponse. Takingthisinterceptintoconsideration,theeffectofinterventionontheaveragelengthofstayisshownbelowinTable 56. Table56Resultsofinterventiononlengthofstay(LOS)perannum RateofLOSat Predicted Estimated % Predicted Estimated Estimated %Changein startof RateofLOS RateofLOS Change LOSover LOSinyear reduction LOSover Intervention without with inRate oneyear after inLOSover oneyear (days) intervention Intervention ofLOS without Intervention oneyear after Year+1 Year+1 Intervention (days) (days) intervention (days) (days) (days) 19.8 24.6 7.9 67.9% 22.2 14.7 7.5 33.8% TheeffectofthetelemonitoringinterventiononLengthofStaymaythusbeestimatedasanaveragereductionof between7.5and9.3daysovertheyearfollowingthestartoftheintervention.Notehoweverthatafteroneyearof interventiontheaverageexpectedLOShadfallenbyalmost68%fromthepredictedvalueof24.6to7.9days. Analysisofdifferences(Control–Test)forLengthofStay Intheanalysisoftheeffectofinterventiononlengthofstay(LOS)carriedoutabove,nocompensationismadeforany changesinControlthatmayhaveoccurredafterinterventionasnosignificantdifferenceswerenotedinControl patientsbeforeandafterintervention,andnosignificantchangeswereobservedwhenanocovaanalysiswasusedto testslopesofthecombinedbeforeandaftersegments. HowevertheeffectofchangesinLOSforControlpatientscanbeaccountedforbyusingthelinearregressionequations developedfordifferencesbetweenControlandTestexpenditure,usingsimilarmethodsasoutlinedabove.Sinceno transformwasappliedtodifferencedata,thereisnoneedtocalculateareas,asthemeanofendpointsatstartof interventionandoneyearlaterwillprovidethesameanswer.Amoreaccurateresultcanthenbecalculatedusingthe interceptbetweentheBeforeandAfterdataasshowninFigure32below. CSIROTelehealthTrialFinalReportMay2016 Page89of187 Figure32LinearregressionofdifferencesforLOS/annum Figure32aboveshowsthatthefirsteffectoftheinterventionisobserved36daysafterthestart.Theresultsfromthe analysisofthelinearregressionfordifferencesareshownbelowinTable57. Table57EstimatesofNumberofadmissionsoneyearaftertheintervention,usingdifferences(Control-Test) PATIENTCOHORT Difference Projected Estimated Projected Average Changein (Differences) Year0 Difference Difference Average Difference Control-Test (days/annum) afterone oneyear Difference afterone After year after without yearof Intervention (days/annum) intervention intervention Intervention (days/annum) (days/annum) (days/annum) (days/annum) 3.6 Allpatients(N=53) -9.8 -12.7 -11.2 -3.9 7.3 TheresultsobtainedfromdifferencesisveryclosetotheestimatedreductioninLOSoveroneyearof7.5daysobtained fromTestpatientdatabeforeandafterintervention.Thedifferencedataalsoshowsthatafteroneyearofintervention therateofLOSforTestpatientsrelativetoControlsis14.3days/annum,comparabletothe16.7days/annumobtained fromTestpatientsalone. 5.5 EffectoftelemonitoringinterventiononMortality Thesimplestdeathratethatiscommonlycalculatedisthecrudedeathrate(CDR),definedasthetotalnumberof deathsdividedbythepopulation.Althoughitdoesrelatethenumberofeventstothepopulation,thecruderatedoes nottakeintoaccounttheagedistributionofthepopulation.Assuch,itisnotanappropriatemeasureforcomparing differencesbetweenpopulationgroupsorforassessingchangeinmortalityovertime. Tocomparemortalitybetweentwogroupstheeffectofthepopulation’sagedistributionmustbetakenintoaccount.A bettermeasureistherefore,theage-specificdeathrate(ASDRs),definedastheratioofthenumberofdeathsinagiven agegrouptothepopulationofthatagegroup. AnothercommonlyusedmeasureistheAdjustedDeathRate(ADR).HoweverinourcasetheADRisnotanappropriate measureaswedonothaveastandardnationalreferencepopulationforourspecificpatientcohort,andratesbasedon smallnumbersofdeathswillexhibitalargeamountofrandomvariation. Asaresultwehavechosentouseagespecificdeathrates(ASDRs)tocompareTestpatientstotheircontrolsandtoa referencedatabaseofeligiblepatientsderivedfromhospitallists.Thismasterregister(MR)fileof1429patientswas formedbysearchingthehospitalrecordsineachLocalHealthDistrictineachstateandTerritorythatparticipatedinthe trial,forpatientswhosatisfiedourclinicalcriteriaforadmissionintothetrial.Henceallpatientsonthismasterregister wereeligibleforparticipationinthetrial.Deathsofpatientsinthismasterfileweresubsequentlycrosscheckedagainst therecordsoftheBirths,DeathsandMarriages(BDM)registersineachStateandTerritory.Thesedataarepresumed tobecompleteandaccurate. CSIROTelehealthTrialFinalReportMay2016 Page90of187 Mortalitycalculationsbasedoncomparativecrudedeathrates Crudedeathrateswerecalculatedonthecorepatientgroupof100Testpatientsand137Controlpatientsfromthe startoftheprojectinMarch2013tothecompletionoftheprojectonthe31stofDecember2014. HoweverasnotallTestandControlpatientsweresourcedfromtheMasterRegister,mortalitydatawasonlyavailable for57Testpatientsand77Controlpatientsonthemasterlistof1429patients.Mortalitydatafortheremaining43Test patientsand60ControlpatientswerecheckedagainsttheRyerson10IndexofdeathnoticesandobituariesinAustralian newspaperswhichcontains5,332,370noticesfrom307differentAustraliannewspapers.Searchingbynamewas carriedoutusingcomputerisedsearchalgorithmsandnameswerethenmatchedagainstageandsexandwhenever possiblelocation,beforebeingaccepted. Althoughthesedatawascarefullychecked,deathsofcontrolpatientsmaynothavebeenalwaysrecordedthroughthe publicationofdeathnotices,andthesedatamustberegardedasbeinglessreliablethanthemortalitydatasourced fromthemasterregisterandcrossreferencedwiththeBDMregister.DeathsofTestpatientshowever,areaccurately recordedasthesepatientswerebeingmonitoredandwereinregularcontactwiththeircarecoordinators. MortalityfigureswerecalculatedfortheincompletecohortofTestandControlpatientsidentifiedintheMaster RegistermatchedagainstBDMdataforthetotalcohortof1429candidateseligibleforparticipationintheclinicaltrial, andthecompletecohortof100Testand137ControlpatientsmatchedagainsttheMasterRegistryandtheRyerson IndexofDeathNotices.TheresultsareshowninTable58. Table58ComparativeMortalitydatausingdifferentdatasources Source BDM Master Number(N) NumberofDeaths CrudeDeathRate %ReductioninDeaths relativetocontrols * Source BDMMasterRegister All Test 1429 251 17.6% 57 5 8.8% 50.1% Control (Matched)* 77 57 13 9 16.9% 15.8% Control 48.0% 44.5% Source BDMMasterRegister+RyersonIndex Test Control 100 8 8.00% 137 16 11.7% Control (Matched)* 100 9.5 9.5 31.5% 15.8% Testpatientscanhaveeitheroneortwomatchedcontrols.Ifbothmatchedcontrolsdie,thisiscountedas1death.If onlyoneofthetwomatchedcontrolsdies,thisiscountedas0.5deaths.IfaTestpatienthasonlyoneControlandthat Controldies,thatiscountedas1death. ThesedatashowthatControlpatientsselectedfromhospitallistshaveaverysimilarcrudedeathrateasthepatientsin theMasterRegistryofeligiblepatients.ForTestandControlpatientsselectedonlyfromtheMasterfile,testpatients havea50.1%reducedmortalityrelativetothecohortof1429patients,a48%reductioninmortalityrelativetothe cohortofControlpatientsanda44.5%reductionrelativetotheirmatchedControls. Howeverwhenthemortalityofthecontrolgroupiscalculatedwiththeadditionofthe60Controlpatientswhose mortalityfigureswerederivedwithreferencetotheRyersonIndexthereductioninmortalityrelativetocontrolsfallsto 31.5%and15.8%respectively.Thisisstronglysuggestiveoftwopossibilities.FirstlythatControlpatientsnotselected fromhospitallistswerelessillandlesslikelytopassawayfromtheirconditionorsecondly,thatanumbermayhave passedawaybuttheirdeathnoticeswereneverpublished. ItmaythereforebemoreproductivetocompareagespecificdeathratesofTestpatientsagainstthemuchlarger masterdatabaseof1429patients. 10 http://www.ryersonindex.org/ CSIROTelehealthTrialFinalReportMay2016 Page91of187 AgespecificDeathRatesofTestpatientsrelativetotheBDMdatabase TheageofeligiblepatientsintheMasterDatabaseonthe1stJanuary2014was73.4±10.8years,significantlyhigher (twotailedt-test,unequalvariance,P=0.012)fromtheagedistributionof100Testpatients(71.0±8.7years).Theage distributionforeligiblepatientsintheMasterdirectoryisgivenbelowinTable59andFigure33. Table59AgeDistributioninMasterRegistry ACT NSW QLD TAS VIC AGEDISTRIBUTION 50-60 60-70 70-80 80-90 90-100 TOTAL 56 121 161 143 39 520 39 56 66 55 14 230 30 43 44 63 9 189 25 37 82 55 10 209 30 53 88 98 12 281 180 310 441 414 84 1429 Figure33AgedistributioninMasterRegistry Table60AgeadjusteddistributionofDeathsovertheperiodofthetrial DEATHS 50-60 60-70 70-80 80-90 90-100 TOTAL ACT 3 12 14 32 17 78 NSW 5 15 16 15 8 59 QLD 2 3 4 9 3 21 TAS 4 10 19 12 4 49 VIC 3 6 7 23 5 44 17 46 60 91 37 251 Figure34AgeadjusteddeathratesinMasterRegistry Table61AgeadjusteddeathsofTestpatientsrelativetoBDMmaster DeathsinBDMMaster AgeSpecificDeathRate Weights TestPatientbyAge AgeSpecificDeaths ExpectedDeaths DeathsSaved * 50-60 180 9.4% 0.126 41 1 3.85 2.85 AgeDistribution 60-70 70-80 80-90 90-100 N 310 441 414 84 1429 14.8% 13.6% 22.0% 44.0% 17.6%* 0.217 0.309 0.290 0.059 1.0 31 14 13 1 100 2 4 1 0 8 4.59 1.9 2.86 0.44 13.64 2.59 -2.1 1.86 0.44 5.64 CrudeDeathRate Usingageadjusteddeathrates(Table61;Figure34)calculatedfromtheMasterRegisterofeligiblepatients,13.64 deathswereexpectedbutonlyeightwererecorded.Thisrepresentsasavingof5.64lives,areductionof41.3%.Thisis ingoodagreementwiththereductionof48.0%and44.5%calculatedrelativetomatchedcontrols. CSIROTelehealthTrialFinalReportMay2016 Page92of187 5.6 Testpatientself-reportedmeasuresatfollow-up Inthissectionchangesinself-reportedmeasuresfromentrytofollowupareanalysedandreported.Patientswere enrolledatdifferenttimeandfollow-updatacollectioncontinueduntiltheendofDecember2014.Someofthetest patientsdidnotnecessarilyalwaysfollowtherecommendedscheduleforansweringquestionnairesandsomeofthem answeredmorefrequentlythanrequired.Thefollowingdataanalysisandreportstrategiesareadopted: Questionnarieresultsatentry,3months,6months,9monthsand12monthstimepointsareincludedforeach testpatients • Onlyquestionnairesthatarefullycompletedbothatentryandtheparticularfollow-uptimepointsare accepted • Onlypatientswhohavebeenmonitoredformorethan3monthsareincluded. Asaresultofthequestionnairecomplianceandourdataanalysisstrategies,thetotalnumbersoftestpatients(N) reportedineachtimepointsineachquestionnairevary.Wilcoxonsignedrankstestareusedtoexaminethewithin groupdifferencesbetweenthebaselineandavailablefollow-updatafortheK10,heiQ,andMoriskyquestionnaires. Resultsofbaselineandfollow-upofEQ-5D5dimensionquestionsarecomparedandreportedinadescriptiveform. • Allstatisticaltestsaretwo-tailed,andapvalue<0.05isacceptedasindicatingstatisticallysignificantdifferences. StatisticalanalysisisperformedusingSPSS17.0andMicrosoftExcel. Table62Kessler10resultsatbaselineandfollow-up K10 N Entry Follow-up Median(SD) Median(SD) PValue Entryvs.3months 37 16(8.20) 15(9.13) P=.036 Entryvs.6months 51 17(8.86) 15(9.18) P=.003 Entryvs.9months 39 17(7.87) 15(8.32) P=.070 Entryvs.12months 27 17(9.10) 14(9.80) P=.035 TheresultsinTable62comparebaselinewithfollow-upfortheK10anxietyanddepressionquestionnaire.Basedonthe availablecasesforentryandindividualfollow-ups,ourresultsshowedthattestpatientsweresignificantlyimprovedat the3months,6monthsand12months’timepointsassessments(p=.036,p=.03andp=.035).Itappearsthat telemonitoringproducedimprovementintestpatientsanxietyanddepression. CSIROTelehealthTrialFinalReportMay2016 Page93of187 Table63EQ5Dresultsonbaselineandfollow-up(proportionoflevels1,2and3answers) level1(noproblem) B 3M N=55 0.35 0.31 B 6M N=51 0.41 0.27 B 9M N=40 0.54 0.34 B 12M N=28 0.50 0.25 level2(someproblems) 0.65 0.69 0.57 0.71 0.46 0.66 0.50 0.75 level3(extremeproblems) 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.00 Self-care level1(noproblem) 0.65 0.56 0.59 0.61 0.71 0.66 0.68 0.71 level2(someproblems) 0.33 0.44 0.37 0.37 0.27 0.32 0.21 0.25 level3(extremeproblems) 0.02 0.00 0.04 0.02 0.02 0.02 0.11 0.04 Usualactivities level1(noproblem) 0.27 0.31 0.22 0.27 0.30 0.33 0.30 0.33 level2(someproblems) 0.73 0.60 0.75 0.63 0.68 0.55 0.63 0.52 level3(extremeproblems) 0.00 0.09 0.04 0.10 0.03 0.13 0.07 0.15 Pain/discomfort level1(noproblem) 0.22 0.33 0.20 0.29 0.34 0.32 0.25 0.29 level2(someproblems) 0.67 0.49 0.69 0.53 0.54 0.61 0.61 0.57 level3(extremeproblems) 0.11 0.18 0.12 0.18 0.12 0.07 0.14 0.14 EQ5D Mobility Anxiety/Depression level1(noproblem) 0.55 0.56 0.55 0.59 0.59 0.66 0.64 0.71 level2(someproblems) 0.44 0.36 0.39 0.35 0.41 0.29 0.32 0.21 level3(extremeproblems) 0.02 0.07 0.06 0.06 0.00 0.05 0.04 0.07 Note:B-baseline,M-months EQ5Dresults(Table63)showthattheproportionsofpatientswhosereponseswere“noproblem”increasedslightlyin themeasuresofAnxiety/Depression,Pain/DisconfortandUsualactivitiesinallfollow-uptimepoints.Patientsreported slightlymoreproblemsinMobilityandSelf-caremeasures.ThefindingofAnxietyanddepressionisconsistentwiththe resultofK10. Table64HeiQresultsatbaselineandfollow-up HeiQ N Entry Mean(SD) Selfmonitoringandinsight Entryvs.3months 21 2.94 (0.32) Entryvs.6months 46 3.05(0.38) Entryvs.9months 32 2.98(0.25) Entryvs.12months 19 3.09(0.31) Healthservicenavigation Entryvs.3months 21 3.11(0.41) Entryvs.6months 46 3.24(0.49) Entryvs.9months 32 3.08(0.35) Entryvs.12months 19 3.28(0.45) Socialintegrationandsupport Entryvs.3months 21 3.06(0.43) Entryvs.6months 46 3.05(0.59) Entryvs.9months 32 2.94(0.57) Entryvs.12months 19 2.95(0.58) Follow-up Mean(SD) PValue 3.11 (0.29) 3.09(0.24) 3.04(0.25) 3.10(0.33) 0.022 0.661 0.323 0.977 3.18(0.36) 3.17(0.34) 3.20(0.37) 3.17(0.35) 0.449 0.312 0.100 0.305 3.17(0.36) 3.08(0.42) 3.00(0.40) 2.97(0.56) 0.284 0.856 0.861 0.833 CSIROTelehealthTrialFinalReportMay2016 Page94of187 HeiQmeasures(selfmonitoringandinsight,healthservicesnavigationandsocialisolation)fortestpatientswerestable withslightincreasesoverthemonitoringperiod(Table64).Nostatisticalsignificancewasobservedexceptin3month Selfmonitoringandinsight(P=0.022). Table65MoriskyMedicationAdherenceresultsatbaselineandfollow-up MoriskyMedication Adherence N Entry Median(SD) Follow-up Median(SD) PValue Entryvs.3months 6 8.00(1.31) 8.00(1.70) 0.157 Entryvs.6months 29 8.00(1.09) 8.00(1.03) 0.937 Entryvs.9months 18 7.00(1.11) 7.50(0.97) 0.446 Entryvs.12months 18 8.00(0.99) 8.00(1.14) 0.623 Moriskymedicationadherencemeasuresfortestpatientswerestablewithaslightdecreasein9monthtimepoint (Table65).Nostatisticalsignificancewasobservedinalltimepoints. 5.7 ImplementingahighdefinitionWebRTCteleconferencingsystem ThissubstantialbodyofworkisdescribedindetailinAppendix8.5.VideoconferencingforpatientsinthisTelehealth TrialwasinitiallymadeavailablethroughtheTelemedcaretelehealthdevicein-buildvideoconferencingcapabilityas discussedintheAppendix.However,tofulfiltherequirementofdeliveringvideoconferencingathighdefinition (1280x720pixels)25fps,aselectionprocesswascarriedouttodetermineanappropriatetabletsuitableforthis purposeconsideringuseraspectsappropriateforanelderlypatient.TheSamsungGalaxyNote8inchandNote10inch tableswereselectedbothwithfrontcamerascapableofcapturingvideoatgreaterthan720p(1280x720pixels)for furtherassessment. Initialtestingdemonstratedthatneitherthe8inchnorthe10inchtabletcansend720pat25fpsvideousingthefront camera,butcanreceiveanddisplay720pvideoat30fps.ThisdownscalingofupstreamvideoisanAndroidoperating system/Chromefeaturewhichcan’tbecontrolled.Theseconclusionswereconfirmedbytwoexternalorganisations AttendAnywhereandMedtechGlobal,bothofwhomareexperiencedinprovidingvideoconferencingservices. Followingtheresultofthisinitialtesting,additionalresearchwasundertakentofindanappropriatevideoconferencing platformtodeliverthisserviceviathetablet. Afterreviewingseveralavailableplatforms,WebRTC(WebReal-TimeCommunication)wasselected,togetherwiththe new2014versionoftheSamsungGalaxyNote10inchtablet.UsingWebRTC,astandards-basedvideoconferencing systemwasdevelopedandtestedfortheTelehealthTrial. Laboratorytestingwasperformedofthedevelopedvideoconferencingsystemtoidentifywhetherthesystemcan supporttwowayHDquality(i.e.,720p25framespersecond)videoconferencingbetweenpatientandclinicalnurse coordinatorusingSamsungGalaxyNote10”tablet. Wesubsequentlyundertookasmallscalepilotofvideoconferencingin2014usingtheSamsungtabletwithTest patients.Twosites(VICandTAS)and4patientsparticipatedinthepilot.Patientsansweredaquestionnairedeveloped byCSIROafterusingthetabletsforonemonth.TheCCCsatVICandTASalsomadecommentsontheirexperienceof usingthevideoconferencingtocommunicatewiththeirpatients. CSIROTelehealthTrialFinalReportMay2016 Page95of187 Table66Patients’responsestothevideoconferencingquestionnaire ITEM Thevideoconferencingtoolwaseasytouse Ifeltcomfortableholdingthevideoconferencingtoolduringtheconsultations Iwassatisfiedwiththesizeofthevideo Thevideoconferencingtoolworkedwellallthetime Ifeltcomfortablecommunicatingwithmytelemonitoringnursebyusingthevideo conferencingtool Thevideoqualitywasgood Theaudioqualitywasgood Talkingtothenurseduringavideoconferencingconsultationwasassatisfyingas talkinginperson Thevideoconferencingtoolmadeiteasierformetocommunicatewithmy telemonitoringnurse Thevideoconferencingconsultationcanenhancetheexistingtelemonitoringservice Iwasabletoexplainmysituationwellenoughduringavideoconferencing consultation Overall,Iwassatisfiedwithmyrecentvideoconferencingconsultationswithmy telemonitoringnurse Ipreferthevideoconferencingconsultationstotalktomytelemonitoringnursemore thantheusualtelephoneconsultations Iwouldusethemobilevideoconferencingtooltotalktomytelemonitoringnurse again Meanscores (0-stronglydisagree, 5-stronglyagree) (N=4) 3.75 4.25 3.5 2.67 4.33 3.33 3.00 4.00 3.00 4.25 4.00 3.33 3.67 4.00 Thequestionnaireresults(Table66)showedthattheoverallresponsesfromthepatientswerepositiveintermsof beingabletocommunicatewiththenurseandexplainingtheirhealthstatus.Theybelievedthatvideoconferencing couldenhancethetelemonitoringservice.Theyfeltthatthevideoconferencingtoolwaseasytouse.Howeverthey foundthatthetooldidnotworkwellallthetime.Theyindicatedthattheywouldliketousethemobilevideo conferencingtooltotalktotheirtelemonitoringnurseinthefutureifpossible. CSIROTelehealthTrialFinalReportMay2016 Page96of187 ThefeedbackfromCCCswasalsopositive.Weaskedquestionsaboutwhattheylikedandwhattheydidnotlikeabout thevideoconferencingtool.Theybelievetheabilityofbeingableto“see”eachotherenhancedtheirrapportwith patients: • • • • • • • Videoconferencingatitsmostbasicleveladdstothetherapeuticrelationshipbetweenapatientand clinician. Itcanincreaseapatient'sfeelingofsafetyastheyarenot'assuming'thatsomebodyischeckingtheir readingsviathetelemonitoringservice,insteadthey'know'thattheyarebeingreviewedandcanreadily discusstheirreadingsandfeelingswithaclinician. Thepatientdoesnothavetoleavetheirownhomeforabasicconsultation,whichsavesthepressureon communityresourcesandfriends/families. Patientswholivealoneandwithlimitedsupportorabilitytomobiliseinthecommunitymayfeelagreat dealmoresupportedbeingreviewedintheirhomeswithouttheneedtoaccesstransportandthetime requiredinamedicalpracticeforbasicmonitoring. Patientscoulddischargefromhospitalearly,andcontinuetobemonitoredfromtheirhomeforaset periodoftime,savinghugecostsofhospitalstayjustforpurposeofmonitoring. Peoplearebeingmonitoredintheirownsetting,whiletheyareeatingtheirowndietandexercising(ornot) attheirnormalrate. Idealtoreviewmedicationsormedicationadministration,injectiontechnique. Theyreportedonsomeissues,includingregulareducationsinitiallyrequired,networkconnectionproblem, unnecessaryfunctionsandiconsontheinterfaceandoperationaldifficultiesforpatientswithfinemotorproblems. Theywouldliketoseealongertrialofvideoconferencingifpossibletoaddressingtheissues. TheCCCsatTASmadethefollowingcomments: “Fromaclinician'sperspectivevideoconferencingenhancestheabilitytoreviewandassessapatient.Body languageisanimportantaspectofphysicalassessmentasyoucanactuallyviewaperson'sworkofbreathing, skincolour,emotions,personalgrooming.Itgivesadditionalinformationabouthowapersonisonanygivenday, whichiseasiertodisguisewithaquicktelephonecall.Whenyouhavethisassessmentitneedstobeactedon whichenhancesmanagementofapatient. Ipersonallyfoundthatalthoughthevideoconferencingtrialwasshort,Idevelopedagreatrapportwiththe patientswhotrialledthistool,andinjustafewsessionshadfoundoutagreatdealabouthowtheylive.They too,developedarapportwithmeandwiththiscomestrust. Iwasabletovideoconferencefromseverallocations,usingthelaptopanddongle,althoughthereweresome limitationsduetointernetcoverage.Ididnothavetobeinaparticularofficeorsuburb.Thisincreasedflexibility frommyperspective. Ibelievetheoutcomescouldbeenhancedifpatientsunderstoodtheydidn'thavetousethevideoconferenceat settimesonly,butcouldusetelemonitoringandvideoconferencingatthetimestheyfeelunwell,asmorecanbe gainedforthecliniciantocapturethesemoments.” CSIROTelehealthTrialFinalReportMay2016 Page97of187 5.8 DemonstrationoftelehealthreportuploadtoPCEHR TheprimaryobjectivewastodemonstratehowPCEHRconnectivitycouldbeachievedbytheprojectandtodelivera vitalsignsmonitoringreportstothePCEHR’sSoftwareVendorTest(SVT)environment.Asecondobjectivewasto describetelehealth/PCEHRintegrationapproachesforproductionenvironments. ThetestenvironmentdevelopedfortheintegrationoftheCSIROTelehealthprojectwiththePCEHRwasasfollows; • • • • • ThetrialparticipantusestheTMCdeviceintheirhome.ThedevicesendsvitalsignsandotherdatatoTMC’s servers. OnaperiodicbasisTMCsendsvitalsignsmonitoringreportstoCSIRO’sprojectserver. CSIROsoftware,actingintheroleofaPCEHRClinicalInformationSystemwithintheSoftwareVendorTest(SVT) environment,packagesthevitalsignsmonitoringreportintoanEventSummaryXMLdocument,thenuploads theXMLdocumenttothePCEHRviatheBusiness-to-business(B2B)gateway. Studyteammembers,actingaspatients,demonstratehowpatientsviewvitalsignsmonitoringreportsasEvent SummaryrecordsusingthePCEHRconsumerportal. Studyteammembers,actingasmembersofthepatient’scareteam,demonstratehowhealthcareproviders viewvitalsignsmonitoringreportsasEventSummaryrecordsusingthePCEHRproviderportal. ThisschemawassuccessfullyimplementedasatestenvironmentasdescribedinAppendix8.6. Basedonthisexperience,andourunderstandingofthePCEHRarchitectureandoperationalenvironments,PCEHR integrationfortelehealthvendorssuchasTMCisviable.VendorswillneedtochoosethemostappropriatePCEHR systemrolefromanumberofpossiblealternatives(ClinicalInformationSystemoraContractServiceProvider). AnenhancementtothePCEHRidentifiedbythisstudyandinthePCEHRreview11isthedevelopmentofanewclinical documenttypeforclinicalmeasurementsthatwouldallowclinicalmeasurementstobeinserteddirectlytoElectronic HealthRecordsandGPmanagementsystems.ThePCEHRintegrationworkconductedforthisstudywouldhaveutilised aclinicalmeasurementsdocumenttypeinpreferencetoEventSummary,haditbeenavailable,asamoreappropriate meansofstoringvitalsignsmonitoringdata. 5.9 Developmentofariskstratificationsystemfortelehealth ThisprojectisdescribedingreaterdetailinAppendix8.7andhasbeenpublishedinaspecialeditionoftheJournalof IntelligentSystems,2016;25(1):37-53. Thisprojectrepresentsapreliminaryattempttoriskstratifychronicallyillpatientsonadailybasistoidentifypatients whoareillbutstable,thosewhoareshowinganearlyexacerbationoftheirconditionandmostimportantly,thosewho aredemonstratinganacuteexacerbationoftheirchronicconditionthatifunattendedcouldleadtoanunscheduled hospitaladmission. Accordinglyadecisionsupportsystemwasdevelopedfortwolevelsofmathematicalcapability.Nurseswithastatistical backgroundareprovidedwithin-depthinformationallowingthemtodetectchangesinmean,meansquareerror(and hencevariation),andcorrelationsusingavariationondynamicprinciplecomponents.Lessmathematicallyinclined nursesareofferedinformationabouttrends,changepoints,andasimplermultivariateviewofapatient’swell-being involvingparallelcoordinateplots. 11 http://www.health.gov.au/internet/main/publishing.nsf/Content/PCEHR-Review CSIROTelehealthTrialFinalReportMay2016 Page98of187 FiveCCC’swereaskedtoprovidefeedbackontheprototypedecisionsupportsystem.Feedbackwasrequestedfrom eachCCCaftertheyhadreceivedonetrainingsessionofabout30minontheoverviewplot,trendplots,changepoints, andparallelcoordinateplots. Thefeedbackfromtwonurseswasthattheyhavesomevaluebutarenotlookedatbecauseoftimeconstraints. Anothersaid,“PersonallyIwouldnotusethemastheyareonadifferentportal–theyneedtobeintegratedintothe portalweuseformanagingourpatients.”InNSWandACT,theCCChadnothadenoughexperiencewiththedecision supportsystemtocomment–mosttestpatientshadnotbeenmonitoredthatlong,andtheywerenotatthestage wheretheycouldeffectivelyusethedecisionsupportandevaluateitsvalue. At-hometelemonitoringofferstheopportunitytotrackthepatients’conditionsonadailybasisand,shouldearly evidenceofanexacerbationbeobserved,toorchestratethemostappropriateandtimelyresponsetoavoidan unscheduledhospitalisation.Inourstudy,oneCCCmonitorsupto25patients,whichisapproximatelyone-thirdofa full-timepatientmonitoringload.TheCCCswereallexperiencednursesbuthavenotreceivedanysignificantadditional trainingonhowtointerpretthelongitudinalpatients’record,andtypicallyusetheirownclinicalexperienceand judgementtodeterminewhenandhowtointervene. Thequestionofwhetherthis“closetothepatientcoalface”modelisthebestwaytomonitorpatients’healthstatusis stillunresolved.Analternativemodelthatisbeingconsideredistheestablishmentofspecialisedcallcentresstaffedby highlytrainedclinicianswhoareveryexperiencedatidentifyingearlysignsofanexacerbationofapatient’shealth statusandhavetheresourcesandtheauthoritytocommunicatetheirconcernstothepatient’scarers,whetherthey maybeaGPoracommunitynurse. Inanenvironmentwherearegionalcallcentremaybemonitoringtensofthousandsofpatients,ourproposeddecision supportsystemcouldbecomeanindispensabletoolformorecost-effectiveandbettermanagementofachronicallyill population. 5.10 Discussionofresults Likeallcomplexclinicaltrialsthisprojecthassufferedfromnumeroussetbacks.Table10providesasummaryofthe evolutionofpatientdemographicsasthetrialprogressed.Amongstsomeofthemajorissuesthatimpactedonthe analysisarethefollowing; • • • • Werecruitedandconsented114TestPatientsand173Controlpatients,butoftheseonly71Testpatientsand 110Controlpatientswerefromthehospitallistsprovided.Thiscausedsomeconsiderabledifficultyinthe reliableassessmentofmortalityandtheanalysisofhospitaladmissionsandlengthofstay. Ofthe114Testpatientsconsented14hadmissingdataintheirDHSrecordsandhadtoberemovedfrom furtheranalysis.Similarlyofthe173Testpatientsconsented,only137patientshadcompleteDHSdata.No explanationwasavailablefromtheDHSastowhysomepatientshadmissingdataintheirDHSrecords. Testpatientswererecruitedandinitiatedtelemonitoringoveralongperiodoftimesothatwhilsttheaverage numberofdaysthatpatientsweremonitoredwas276daystherewasaconsiderablespreadfrom<100daysto >500days.Theperiodforanalysisoftheeffectoftelemonitoringwasthuslimitedto12monthsaspatient numbersrapidlyfallandthedataspreadincreasesforperiods>12months. Forsomepatientsconsentedearlyinthetrial,signedconsentwasprovidedonlythroughtoJune2014.When thetrialdurationwasextendedtotheendofDecember2014,newconsentformsfortheextendedperiodwere notsignedandasresultDHSdataforthesepatientswasonlymadeavailablethroughtoJune2014. TestandControlpatientsweregenerallywellmatchedinprimarydiagnosisandSEIFAindexacrosssites(Figure9). HoweveronreceiptofDHSdataattheendofthetrialitwasoftenobservedthatMBSandPBSexpenditurewasNOT wellmatchedatthestartoftelemonitoring.SincewebelievethatMBSexpenditureisagoodproxyforthelevelof severityofapatient’schroniccondition,itwouldbeofinteresttore-analysethedataavailablewithmatchedcontrols beingmatchedonMBSexpenditureovertheprevioussixmonths,aswellastheothercriteriadescribedinTable4. CSIROTelehealthTrialFinalReportMay2016 Page99of187 Datawasanalysedusingthreedifferentmethodsdesignedtoidentifythetimedependentimpactsoftelemonitoringon MBSandPBSexpenditureaswellasnumberofadmissionstohospitalandlengthofstay,andagedependentmortality. Method1,basedonlinearregressionandANCOVAanalysisofTestandControlpatientsaswellasDifferences(Control –Test)wasappliedtooverallMBSandPBSdataaswellasdataforMaleandFemalepatients,andpatientsselectedon thebasisoftheirprimarydiagnosis.Additionaldatasegmentationwascarriedouttodifferentiatepatientsbeing monitoredinHospitalsettingsandthosebeingmonitoredinCommunitysettings.Linearregressionmodellingwasthen usedtoprovideestimatesofthetimecourseofchangesinRATESofMBSandPBSexpenditureandHospitalisationand LOS,andthroughsimpleintegration,estimatesofSAVINGSmadeovertheyearfollowingthestartoftelemonitoring. Method2wasaBACIlinearmixedeffectsmodellingapproachwhichalsoinvestigatedthepossibleimpactofseasonal variations,genderandsitespecificdifferences.Becauseofthesignificant“smearing”ofstartdatesfortelemonitoring, andrelativelysmallnumbers,thisanalysisprovidesprimarilyaqualitativeanalysisoftheimpactoftelemonitoringat eachsite. Method3concentratesonthecumulativesumofdifferencesofaverage30daycosts.Thismethodcannotprovide absoluteestimatesofcostsavingsbutachangeinslope,andthetimeatwhichthisoccurs,providesstrongvisual confirmationoftheimpactoftelemonitoringovertime.Thismethodwasappliedprimarilytoimportantelementsof MBScosts,namelyGPcosts,specialistcosts,laboratorycosts,costofprocedures,numberofGPvisits,numberof specialistvisitsandnumberofprocedures. ImpactoftelemonitoringonMBScosts OverallexpenditureonMBSitemswas$2,405pawithTestpatientsspendingonaverage$480morethanControl patients(Table33).TherewasacleardropinMBScostsovertimeforTestpatientsfollowingtheintervention,whilst therewasnosignificantchangeforControls.Therewasa46.3%dropintherateofMBSexpenditureintheyear followingthestartofintervention,representingasavingof$611(Table34)overthatyear.Generallysavingswere greaterforpatientswithcardiacconditions$804andthosemanagedincommunitysettings($648).Savingswereleast forpatientswithchronicrespiratoryconditions($409).Theseresultswerebroadlycorroboratedbytheanalysisof differences(Table36)andintheBACIlmeanalysis. BACIlmeanalysisshowninSection8.3.3showsamarkeddecreaseinMBScostsinTAS,QLDandNSWandsmaller decreasesinBIC.ReductionsinMBScostsoverthelasteightmonthsofthetrialwerebetween12%and30%fortest patientsandbetween-7%and6%forControlpatients. TheslopeoftheCUMSUMplotshowedagradualchangeofslopeforGPcostsandadramaticchangeinslopeof Specialistcostsandofprocedures.Laboratorycostsbegantofallonlytowardstheveryendofthetrialinlate2014. HencewecanconcludethatMBSexpenditurefellthemostinNSW(30%)andACT(25%)andleastinVIC,andthat thesesavingswereprimarilymadethroughmodestfallsinthenumberandcostofGPvisitsandsignificantfallsinthe numberandcostsofspecialistvisitsandprocedurescarriedout.Laboratorycostsbegantofallonlyinthelasttwo monthsofthetrial. ImpactoftelemonitoringonPBScosts Itiswellknown12thatpolypharmacyiscommonwiththeelderlychronicallyillperson,withthoseaged65-74years typicallytaking>6medications.OurPBSdataindicatesthatthemediannumberofPBSentriesrecordedinthe databasewere68,76,82and80perannumfortheyears2011–2014respectively.Theserepresentanaverageof6-7 scriptsbeingfilledpermonth,completelyconsistentwiththepublisheddataonchronicallyillpatients. HoweverthespreadnoticedinthePBSdatawasconsiderable,rangingfromasfewaszeroentriestoasmanyas400 entriesperannum.Whilsttheuppernumbermaybeconceivable,itishardtobelievethatchronicallyillpatientswere eithernotfillingscriptsatall,orveryfew.AccordinglyoutlierswereidentifiedusingthesimpleTukeyrulesonquartiles, 12 http://www.nps.org.au/__data/assets/pdf_file/0003/15780/news13_polypharmacy_1200.pdf CSIROTelehealthTrialFinalReportMay2016 Page100of187 wherepatientswithentriesexceeding±1.5IQRfromthemedianvaluewererejected.NonethelesstheremainingPBS datastillshowedsignificantlygreatervariabilitythanMBSdata,withonoccasionrunsofzeroentriesforperiodranging from3-9months.Wecannotexplainthesemissingdata. OverallexpenditureonPBSitemswas$2,984pawithTestpatientsspendingonaverage$328palessthanControl patients(Table45).PBSresultshoweverwerefarlessconclusiveprobablybecauseofthelargespreadofmonthlycosts observedintheDepartmentofHumanServicesdatabases.Therewasnone-the-lessanoverall25.5%dropintherateof PBSexpenditureintheyearfollowingthestartofintervention,representingasavingof$354(Table46)overthatyear. Generallysavingsweregreaterformalepatients($477)andleastforfemalepatients($181). Analysisofdifferences(Table47)howevershowednooverallchangeinPBSexpenditure($44pa),withlargeincreases recordedformales($834pa)andcardiacpatients($1,128pa)andlargereductionsrelativetocontrolsrecordedfor Femalepatients($1062pa)andDiabeticpatients($2,033pa).ThecohortofMalepatientsandCardiacpatientsoverlap considerablyandbothdemonstratedinexplicabledropsinPBSexpenditurefollowingtheintervention.Diabetic patientsandtoalesserextentFemalepatientsachievedlargesavingsrelativetocontrolsasaresultofaninexplicable increaseintherateofPBSexpenditureaftertheintervention. TheseinconclusiveresultsaresupportedbytheBACIlmeanalysiscarriedoutinSection8.3.4. Muchmorepronouncedseasonalvariationswereobservedatallsites,butnosignificantdifferencesinbeforeandafter PBScostswereobserved,otherthanforamodestfallintheACTandamoresignificantfallinNSW.Cumulativesumof differencesanalysiswasnotperformedonPBSdata. Impactoftelemonitoringonhospitaladmissionsandlengthofstay(LOS) Hospitaldatawasonlyanalysedfor53Testpatientsand64matchedControlpatientsforwhomhospitaldatain HospitalRoundtableformatwasavailablefromtheLocalHealthDistrict.Becauseofthesereducednumbers,analysis wasonlycarriedoutonthetotalcohort.Ofthe53Testpatientsselected,29sufferedfromHeartDisease,21suffered fromRespiratorydiseaseand3werediabetics. Basedontheirrateofadmissionatthestartofintervention(2.55admissionspa)Testpatientswerepredictedtohave 3.09admissionspaoneyearaftertheintervention.Howeveroneyearafterthestartoftelemonitoring,theirrateof admissionfellto1.45pa,areductionofmorethan53%.Overoneyearofthetelemonitoringintervention,this representsareductionofbetween0.67and1.0admissionspa.Theeffectofthetelemonitoringonrateofadmissionto hospitalbeginstobecomevisibleonlyaftertwomonths. Analysisofdifferencesgaveasimilarresult,buttheimpactoftelemonitoringonadmissionsonlybecomesevidentafter approximatelysevenmonths.TheDifferencedataalsoshowsthatafteroneyearofinterventiontherateofadmission forTestpatientsrelativetoControls(Table53),is1.03admission/annumlessthanthatpredictedwithoutthe intervention.ThisisingoodagreementwiththedataderivedfromTestpatientsalone(Table51). ThelinearregressionanalysisprovidesrobustevidencethattherewasnochangeinLOSforcontrolpatientswhilst therewasasignificantfallinLOSintheyearfollowingthetelemonitoringintervention(Figure21andTable54).Test patientsatthestartoftelemonitoringhadlengthofstaysofapproximately19.8days,whichafteroneyearwere projectedtoincreaseto24.6days.TelemonitoringreducedtheprojectedrateofLOSafteroneyear(24.6days)toa rateofLOSonly6.0dayspa,areductionofalmost76%.Thisimpactbeginsalittleoveronemonthfromthestartof telemonitoring,significantlyearlierthantheimpactonnumberofadmissions.Thissuggeststhatwhilstadmissionsmay notbeinitiallyreduced,lengthofstayisreduced.Overtheyearfollowingthetelemonitoringinterventionthisleadsto asavingofbetween7.5and9.3daysinlengthofstay. AstherewasnochangeintheLOStrajectoryofControlpatientsitisnotsurprisingthattheanalysisofdifferencesleads toalmostidenticalresults.Initialimpactoftheinterventionbecomingevidentalittleoveronemonthfromthestartof telemonitoring,andleadstoasavingof7.5daysovertheyear. CSIROTelehealthTrialFinalReportMay2016 Page101of187 Effectoftelemonitoringonmortality Mortalitywascalculatedmostreliablyfor57Testpatientsand77Controlpatientsonthemasterlistof1429patients. WedonotconsidertheRyersonIndexofdeathnoticesareliablealternativeandasaresultwerecommendignoring themortalitydatawhichincludesdeathsidentifiedonlyfromdeathnotices. TheresultsshowninTable58showthatthecrudedeathrateforthewholemasterfileof1429patientswas17.6%, matchingcloselythe15.8%recordedforourcontrolpatients.SincethecrudedeathrateforourTestpatientswas8.8% the%reductioninmortalityis48%forControlpatientsasawhole,and44.5%whenControlsarematchedtoTest patients. AnalysisofagespecificdeathratesintheMasterrecordof1429patientsthenpermitsanestimateofthenumberof deathsexpectedineachagegroupforTestpatientstobemade.Thiswas13.64deaths.Sinceonly8deathswere recordedamongourTestpatients,thisrepresentsareductioninmortalityof41.3%. Testpatientself-reportedmeasuresatfollow-up Theseresultswereanalysedfromfollowupquestionnairesadministeredat3,6,9and12monthstoasubsetofthe totalTestpatientcohortrepresentedby37,51,39and27patientsrespectively.Resultsindicatethatanxietyand depressionmeasures(K10Questionnaire)weresignificantlyimprovedat3,6and12months,butfailedtodemonstrate significanceatthe0.05levelat9months. ResultsfortheEQ5DQualityoflifequestionnairewerebroadlyconsistentwithK10resultsforAnxietyandDepression butpatientsreportedslightlymoreproblemsinMobilityandSelf-caremeasures.HeiQmeasures(selfmonitoringand insight,healthservicesnavigationandsocialisolation)fortestpatientswerestablewithslightincreasesoverthe monitoringperiod(Table64).Nostatisticalsignificancewasobservedexceptat3monthSelfmonitoringandinsight(P =0.022).Moriskymedicationadherencemeasuresfortestpatientswerestablewithaslightdecreasein9monthtime point(Table65).Nostatisticalsignificancewasobservedinalltimepoints. CSIROTelehealthTrialFinalReportMay2016 Page102of187 6. Conclusions TestpatientsandControlpatientswerestatisticallywellmatchedanddidnotdemonstrateanystatisticallysignificant differences.Therewerenosignificantdifferencesbetweenage,genderorBMIofTestandControlpatientsatbaseline. IntheTestpatientcohort67%weremaleand33%female,withthesefiguresmorecloselymatched(55%malesand 45%females),fortheControlpatientgroup.TherewerenostatisticaldifferencesobservedbetweenTestandControl patientseitherwithrespecttotheSEIFAstatusortheirprimarydiseasediagnosis. HoweveronanalysisofMBSdataandPBSdataitbecameevidentthatTestpatientshadfasterratesofgrowthofMBS expenditureovertimeandconsiderablyhigherMBScoststhanControlpatientsatstartoftelemonitoring.Interestingly, forPBScostsControlpatientshadahigherrateofincreaseovertimethanTestpatientsandatstartoftelemonitoring hadhigherPBSexpenditure. ResultspresentedinChapter5suggestthattelemonitoringiswellacceptedbypatientswhocomplywellwiththe scheduledmeasurementprotocols.Patientsalmostuniversallyexpressedstrongsupportfortheserviceandreported betterunderstandingandself-managementoftheirchronicconditions.EngagementwithGPswasasignificantproblem forthetrialwithpooruptakeoftheopportunityforGPstoviewpatientdataon-lineandreporteddifficultiesbyCCCsin communicatingwithGPswhenchangesinthepatients’conditionwarrantedatimelyintervention. TheTASandACTsitesrepresentonemodelwherepatientsreceivednormalcareinthecommunitybutweremonitored byateamofspecialistnursesbasedinhospitalsettings.TheNSW,QLDandVICsitesrepresentanothermodelofcare wherebypatientsweremonitoredbynursesoperatingincommunitysettingswithoutnecessarilythebackingand supportofaregionalhospital.Communitybasedtelemonitoringmodelsappearedtogenerallydeliverbettereconomic resultsthanhospitalbasedmodels. Theprojectencounteredanumberofunexpectedexternaldifficultiesintheidentification,recruitmentandconsenting ofTestpatients.Thesehadasignificantimpactontheoutcomesofthestudy.Abriefsummaryisprovidedbelow; 1. RolloutoftheNBNwasmuchslowerandpatchierthanexpectedateverysiteotherthanTAS,andparticularly impactedthesitesintheNepeanBlueMountainareaandTownsville. 2. ConnectionoftelehealthservicesviafibretothenodewasdeemedunacceptablebythepreviousGovernment thusmakingitimpossibletoconnectanypatientsintheCanberraACTareauntillate2013whentheincoming governmentrelaxedtherequirementtoconnectpatientsONLYtoNBNinternetservices. 3. AlthoughtheNH&MRCstatedthatEthicsapprovalwasrequiredfromonlyonenationallyaccreditedHREC committee,everysiteotherthanTASrequirednewEthicsapplicationsandsitespecificapprovalstobe submittedtolocalHRECcommitteesbeforetheprojectcouldproceed.Insomecasestherequirementsoflocal HRECcommitteeswereinconflictwiththeCSIROHRECapprovalandtheseconflictswereonoccasionslowto resolve.Theseissuescontributedinmanycasestoanadditionaldelayintherolloutoftheprojectof2-3 months. 4. Selectionofpatientswasintendedtobemadefromlistsofeligiblepatientsmadeavailablebylocalhospitals. ThiswasadheredtowellinTAS,ACTandQLDbutpoorlyinNSWandnotatallinVIC,whereourlocalsite,the DjerriwarrhHealthServicesandlocalMelton-BacchusMarshhospitalwasunabletogeneratepatientlists. Thesedifficultiesledtoconsiderableuncertaintyanddatawastageinthefinaldataanalysisphaseofthe project. 5. Hospitaldatawasdifficulttosource.NeitherMelton-BacchusMarshlocalhospitalnortheNepeanBlue Mountainswereabletoprovideanyhospitaldatadespitestrenuousefforts.Costofadmissiondatawasonly availablefromTownsville-MackayHospital(QLD). 6. AhighnumberofrefusalstoparticipateaseitherTestpatientsorControlpatients.Thismadethetaskof identifyingandconsentingpatientsmuchmoreprotractedandtimeconsuming. 7. Localpoliticalandadministrativedifficultiesinlocalhealthdistrictsledtolongdelaysinidentifyingtheclinical hostsfortheproject.Thesewererelatedinonecase,tomassiveorganisationalchangestakingplaceinthe TownsvilleHealthDistrictfollowingtheelectionofthenewstategovernmentinQueensland,andinanother, CSIROTelehealthTrialFinalReportMay2016 Page103of187 theinabilityoftheConnectedCareprogramattheNepeanBlueMountainsLHDtohosttheproject.Boththese circumstancesrequiredtheidentificationofalternativehostsfortheproject,whichinbothcaseswerethelocal MedicareLocalorganisations. 8. SignificantdelaysinthenegotiationoftheContractwiththeCommonwealthandevenlongerdelaysinsigning serviceagreementswitheachofthesixoriginalclinicalsitesandtwoindustrypartners. 9. Allpatientsfortheprojecthadtobenewlyidentifiedandconsented,nonewerereadilyavailablefromanyof theparticipatingclinicalpartners.ThecomplexrecruitmentprocessesimposedbytheCSIROHRECorthelocal HRECsmayhaveledinparttoahighrateofrefusal.Thismadetherecruitmentofpatientsafarmorecomplex andlengthyprocessthanwasoriginallyexpected. 10. ThedifficultiesinrecruitingTestpatientsandthenecessitytohaveTestpatientsmonitoredforatleastsix monthsmeantthatalltheeffortwasfocusedonthattasktothedetrimentanddelayinalsorecruitingControl patients,whichwererecruitedatalaterdate. Notwithstandingthesedifficulties,theCSIRONationalTelehealthProjecthasprovidedalargeamountofvaluabledata ontheimpactofintroducingtelemonitoringservicesatfivedifferentlocationseachwithadifferentmodelofcarefor themanagementofchronicdiseaseinthecommunity.Togethertheseservicemodelscanbeconsideredrepresentative oftheAustralianhealthcaresystem. Positiveimpactsoftelemonitoringafteroneyearinclude; • • • • • • • • • 46.3%reductionsinrateofMBSexpenditure 25.5%reductioninrateofPBSexpenditure 53.2%reductionintherateofadmissiontohospital 75.7%reductionintherateoflengthofstay >40%reductioninmortality >60%useradherencetomeasurementprotocols >50%useradherencetoquestionnaireadministration >83%useracceptanceanduseoftelemonitoringtechnology >89%ofclinicianswouldrecommendtelemonitoringservicestootherpatients Therewasahighlevelofsatisfactionwiththetelehealthserviceandtheeaseofuseofthetelemonitoringtechnology. Amajority(87.5%)reportedthattheyweresatisfiedwiththetelemonitoringservice(Table18).Theiroverall experiencewithtelehealthnurseswaspositiveintermsofthetimeandsupporttheyreceivedfromtheCCCs.However only12.2%ofpatients’GPsreviewedthetelemonitoringresultsduringpatients’visitsandonly34.7%patientsagreed thattelemonitoringimprovedtheircommunicationswithGPs.Amajority(73.5%)weresatisfiedwiththeirinternet connections. AsshowninTable18,testpatientsfoundthattelemonitoringhadimprovedtheirknowledgeabouttheirconditions (69.4%)andsymptomstowatchfor(77.6%).Theyreportedthattheyhadbecomemoreinvolvedinmonitoringtheir healthconditions(79.6%)andimprovedtheirself-care(71.4%)asaresultoftelemonitoring.Asmallnumber(12.2%) feltthatseeingtheirvitalsignseverydayandtalkingtotelehealthnursesmadethemanxiousorworried.Alarge majority(89.8%)ofthemrespondedthattheywouldrecommendtelemonitoringservicetootherpeople. Compliancewiththemeasurementprotocolsscheduledforeachpatientwasgenerallyhighwithpatientscarryingout theirscheduledmeasurementsonadailybasisalmost63%ofthetime.Astrongcorrelationwasfoundbetweenthe levelofinvolvementoftheCCCandpatientcompliance.ThehighertheCCCengagementwiththepatientandthe monitoringofpatientdata,thehigherwasthelevelofcompliancefromthepatient. ClinicalCareCoordinatorsgenerallyviewedeverypatientsrecorddailyandtrackedtimespentoneverypatientusing theCSIROWEBportal. CSIROTelehealthTrialFinalReportMay2016 Page104of187 AllCCCs,POsandGPsweinterviewedbelievedthatthehometelemonitoringwouldhavepotentialpositiveimpacton theearlyinterventionforchronicdiseasepatients.TheTASPOhasofferedheropinionsandherexperiencesonthe benefitsoftelehealthmonitoringinAppendix8.8.SomeCCCsandPOs(e.g.TAS,VIC)andGPs(e.g.,QLD)foundthat theirpatientshaveimprovedknowledgeabouttheirchronicconditionsandhavebeenabletolearnthemeasurements whichareimportanttotheirchronicconditionanddiscussthesewithclinicians. ThedatashowninFigure13suggeststhatonaverage,CCCsaccessedtheTMCClinicianWebPortaltwiceadayand spendonaverageatotalofbetween30and40minutesadayreviewingpatientdata.Theplotsshownin Figure14indicatethehospitalbasedsitesofTASandtheACTwereloggingintotheCSIROportalonaverage1.4times aday.Forthecommunitybasedsites,CCCswerelogginginonaveragejustlessthanonceaday. GPswererequiredtoprovideconsentfortheparticipationoftheirpatients(onlytheTestpatients).Atthattimethey weregiventheopportunityofviewingpatientdatadirectlyonscreen,ortoreceivePDFreportsontheirpatients’ longitudinalrecordseitherbye-mail,faxorthepost.Only16%chosetohavetheoptionofviewingtheirpatient’s recordsonline.MajorityofGPsinterviewedpointedoutthattelemonitoringwouldbemoreusefulinruralsettings.One ofthephysicianswhoworkedinahospitalbelievedthatitcouldplayanimportantroleinearlydischargeofpatients fromhospital. GPengagementwiththeprojectwashoweveroneofthemoredisappointingaspectsoftheprojects.Obtainingtheir consentcouldtakemonths,thusimposingdelaysontheprojectandCCCsfrequentlyreportedgreatdifficultiesin makingcontactwiththepatient’sGPwhenexacerbationoftheirpatient’schronicconditionwasbecomingevident. Thereturnoninvestmentfromsuchanationalinitiativewouldbeintheorderof5:1byreducingdemandonhospital inpatientandoutpatientservices,reducedvisitstoGPs,reducedvisitsfromcommunitynursesandanoverallreduced demandonincreasinglyscarceclinicalresources.Thiscouldbeachievedwithanimprovementinpatientself- management,highlevelsofpatientsatisfactionandaperceivedimprovementinpatientqualityoflifeandhealth outcomes. HowevertoachievetheseoutcomesgreatercooperationbetweenStateandFederalfundingagencieswillberequired toestablishpolicyframeworksandtargetedfundingmodelstoscaleuptelehealthservicesnationally.Inaddition systemlevelorganisationalchangesandchangesinlocalgovernanceandworkplacecultureswillneedtobeactively promotedastheintroductionofnewmodelsofcarealwayssucceedorfailattheoperationalandpatientcoalface. 6.1 CostofDeliveringTelehealthServices DatashowninFigure13suggeststhatonaverage,CCCsaccessedtheTMCClinicianWebPortaltwiceadayandspent onaverageatotalofbetween30and40minutesadayreviewingpatientdata.ThusaCCCworkingfulltimeand responsibleONLYformonitoringpatientdatacouldmanageatheoreticalmaximumof240-320patientsaday.With additionaltimerequiredtomanagecomplexcases,communicatewithGPsandcarersandgenerallycoordinatethe patient’scare,therealisticfigureislikelytobecloserto100patients.Dataprovidedbyonesiteforthemonitoringof 25patientsispresentedinTable67asfollows; Table67CostofClinicalCareCoordination Nurse AnnualCost includingOHs Role Timespent Hours(/week) Costper annum 1 $78,970 ClinicalCareCoordinationandHandover 10 $36,793 2 $103,808 ClinicalCareCoordinationandHandover 3 $13,495 3 $92,199 ClinicalCareCoordinationandHandover 1 $2,766 TOTAL 14 $36,793 ThesecostssuggestthataCCCwouldcostapproximately$100,000pa($55.55/hour),includingoverheads.Sincein ourtrial14hoursaweekwerespentmonitoring25patients,eachpatientrequired33.6minutesperweekofattention. CSIROTelehealthTrialFinalReportMay2016 Page105of187 Thesecostsconvertto$6.22perpatientperdayandsuggestthatasinglenurseworkingfulltimecouldmanage68 patients.Othersitesreportedsomewhatlowercosts. Giventhatthisisatrialandnotanestablishedserviceitislikelythatimprovedproceduresandprocessesaswellas increasedefficiencyandtheuseofpredictiveanalyticstoolstoautomaticallyriskstratifypatients,wouldbringthe monitoringcostperpatientperdaytoapproximately$4.00/day.Thiswouldallowasinglenursetomonitor∼100 patients.WenotethattheVeteransAdministrationintheUSAusesonecarecoordinatorfor150patients. Estimatingpotentialreturnoninvestmentoftelemonitoringservice. AtypicaltelemonitoringsystembasedonTabletwiththreeBluetoothmeasurementdevicescostsapproximately $1,324(CostsprovidedbyTelemedcare).Ignoringsettingupcostsoftheservice. • • • • • • Capitalcostaveraging$1324amortisedover4yearsat7%interest Internetcosts(3/4Gdatacosts,10MBmonthlyplan) Hosting,maintenanceandWebservices@$70/month Nursecoordination(100patients/clinicalcarecoordinator,$4/day/patient) TOTAL ESTIMATEOFANNUALCOST $2,760pa SavingsinMBSandPBScosts(approximate,fromCSIROtrialdata) ReducedLOS,averaging7.5beddays@$2,051/day Reduceddemandoncommunitynurses (Reductionofonevisit/week@$60/visit) ESTIMATEOFANNUALSAVINGS $19,263 RETURNONINVESTMENT Withoutinvolvementofcommunitynurse $35/month $5/month $70/month $120/month $230/month $1,000pa $15,383pa $2,880pa 5.98 4.9 Notes: 1. Basedon48weeksayear,9:00–5:00monitoring 2. Monitoringthreevitalsigns+clinicalquestionnaires 3. AssumesthatnormalcareisGPwith/withoutCommunitynurse 4. Costofbedday=$2051(QueenslandHealth’s2012-2013Averagepatientcost- hospitalandhealthcareactivitybasedcostingcollection) 6.2 Healtheconomicsoftelemonitoring DatapresentedbytheAIHW[1]basedonthe2004-2005NationalHealthsurveyindicatesthat22.9%ofthe3.34million Australiansagedover6513havethreeormorechronicconditions.Ifpatientsagedover65andsufferingfromchronic diseaseandmultipleco-morbiditieshavemorehospitaladmissionsandlengthofstay,thenover750,000Australians agedover65wouldbegoodcandidatesforathometelemonitoring. Conservativelyreducingthisfigureforconditionssuchascancerandneuromusculardisordersnotcommonlyamenable tohomemonitoring,suggeststhatapproximately500,000peopleinAustraliawouldbenefitfromathome telemonitoring.Ifacriticalmassofpatientstoachieveeconomiesofscaleweretobeintheorderof10,000patients, thenfifty(50)telemonitoringcentreswouldbeneedednationally,eachfundedatalevelofapproximately$40meach, 13 http://www.abs.gov.au/Ausstats/[email protected]/mf/3235.0 CSIROTelehealthTrialFinalReportMay2016 Page106of187 atatotalcostof$2.0b.WithmeanstestingandcostsharingtheCommonwealthinvestmentcouldbereducedtothe orderof$1bannually. Ifonehospitaladmissionforachronicallyillpatient,atanaveragecostof$6,000couldbeavoided,costsavingsofthe orderof$3bperannumcouldbeachieved,areturnoninvestment(ROI)ofbetween2and3.Additionalsavingswould alsobemadefromafarmoreefficientuseofexistingclinicalresourcesincludinga2-3foldincreaseincaseloadfor eachcommunitynurseandareductioninpatientvisitstotheirGP. Awell-regulatedtelehealthmarketexceeding$2bperannumwouldbesuretoattractprivatesectorcompetitionand investmentsintotelehealth. Thehealtheconomicsofimplementingatelemonitoringservicesnationallyhasbeenanalysedandanumberofservice modelsproposed.Atthisearlystageoftheevolutionoftelemonitoringserviceswerecommendthatmonitoringand clinicaltriagecontinuetobecarriedoutasclosetothecoalfaceaspossibletotheprovisionofhands-oncareto chronicallyillpatients. ThenecessitytoalignthosewhopaywiththosewhobenefitinachievingashighaReturnonInvestmentaspossible suggeststhatonereimbursementmodelmightbetohaveLocalHealthDistrictstakeresponsibilityforimplementing telemonitoringservicesandclinicaltriagecallcentres,withasignificantperformancebasedcrosssubsidyfromthe Commonwealthgovernment.Clinicaltriageandmonitoringservicescouldthenbemadeavailableforallchronicallyill patientsirrespectivewhethertheyareunderthecareofaGP,acommunitynurseemployedbytheLHD,ora communitynurseemployedbyanNGO. Fromasimpleanalysisofpopulationhealthdataweconcludethatinorderof500,000peopleagedover65with complexchronicconditionsandmultipleco-morbiditieswhoareadmittedtohospitalatleastonceeachyearwould benefitfromathometelemonitoringoftheirvitalsignsandfromon-goingclinicalmonitoringandtriageoftheirhealth status. 6.3 OrganisationalChangeManagementandImpactonWorkplaceCulture Ourexperiencethroughoutthetrialhasdemonstratedconvincinglythatsuccessfuldeploymentofade-novo telemonitoringservicerequiresthefollowingsuccessfactorstobeinplace; 1. Strongsupportandleadershipfromthehealthservicemanagementteamandtheformationofstrongclinical governancefortheservice. 2. Strongalignmentofworkplacecultureandvalueswiththeobjectivesoftelemonitoring.Thiswilloftenrequire theimplementationofextensivetrainingandeducationprograms. 3. Aclear“ownership”andengagementnotonlywiththepatient,butwiththepatient’scarerswhomayinclude relatives,neighbours,communitynursesandGPs. 4. Supportfortelemonitoringservicesthroughautomatedriskstratificationprotocolsthatcanidentifywithhigh probabilitypatientswhoaredemonstratinganexacerbationoftheirconditionandmayrequireimmediate attentiontoavoidanunnecessaryhospitalisation. 5. CleargovernanceprotocolsandlinesofcommunicationbetweentheCCCandthepatient’scareteam,in particularthepatient’sGP. 6. Fundingmodelsfromstateandfederaljurisdictionswhichclearlyalignthosewhopayandthosewhobenefit fromthetelemonitoringofchronicallyillpatients. CSIROTelehealthTrialFinalReportMay2016 Page107of187 6.4 Benefitsforpatientsandclinicians TherearemanyexamplesinourDataportalofexacerbationsbeingavoidedthroughtheearlyidentificationofchanges inthepatient’svitalsignsandthetimelyorchestrationofaclinicalresponsefromthepatient’scaregiver.Two examplesareprovidedbelow. − Example1 “OurpatienthadonlybeenmonitoringforacoupleofdayswhentheCCCnoticedexceptionalpeaksandlowsinblood glucosemeasurements.Shecontactedthepatientandrecommendedavisittotheemergencydepartment.Theclient livesaloneandwasunsurewhetherthesituationwasseriousenoughtopresshervital-callalarm.Theinterventionof theClinicalCoordinatorpromptedhertoseekmedicalassistance.ShehassincehadfollowupvisitstoherGP,whohas beensentreportsofthepatient'sreadings.Thepatientwillbeseeingadiabeticeducatortobringherdiabetesunder control”. − Example2 “Inotedfrommeasurementstaken18.2.14thatPtXXXhadaveryslightdecreaseinSpO2(2%frombaseline),dropin spirometryandincreaseintemp(thoughtechnicallystillafebrile)Shehadreportedachangeinhowshewasfeelingand hercoughinherCOPDquestionnaire.ImessagedviatheTMCUnitXXXandthendecidedtocallheron19.2.14.Though patienthadcommencedoralantibioticsthepreviousweek(initialledbyGPafterIrecommendedsheseehim)shehad notimprovedandhadmorecough.IthencontactedOutpatientdepartmenttoestablishifherRespiratoryPhysicianhad avacancyinhisclinicthatdayandsecureditforher.IcontactedPtwiththeappointmenttimeandproducedareport fortheConsultant”. Impactoftelemonitoringonpatientsandclinicians; − − − − − − − − Normalcarebypatients’GPsand/orcommunitynursesisgreatlyfacilitatedbytheearlywarningofan exacerbationprovidedbyathometelemonitoring Improvedpatientunderstandingoftheirconditionandbetterpatientself-managementleadstoareduced demandonGPandnursingservices AlthoughGPsweregenerallynotheavilyinvolvedwiththeproject,asmallnumberwereabletoidentifysignificant benefitsfortheirpatientsbythe“earlywarningsystem”providedbythetelemonitoringservicethatcouldidentify anearlyexacerbationofthepatient’sconditionandorchestrateanoptimalresponsefromthepatientsclinical carerstoavoidunnecessaryhospitalisation SavingsareavailabletopatientsinreducingoutofpocketexpensesassociatedwithGPandhospitalvisitsaswell asreducedtravelcostsandlossofincomeforthosepatientsstillinemployment. Communitynurseshavethepotentialforsignificantlyincreasingtheircaseloadwithoutincreasingtheirworkload byonlyvisitingthosepatientswhohaveanevidentclinicalneedandareatriskofexacerbationoftheircondition. Visitstopatientswhoaresickbutstablecanbereduced. AsthepopulationagesGPsarefacingalargeincreaseinchronicallyillpatientsandmanyarealreadyrestricting theirdailylistsandrefusingtoacceptnewpatients.ThereisevidencethatvisitstoGPsfrompatientsenrolledina telemonitoringprogramcandropbyasmuchas50%[7-10]thusreducingthedemandforGPservicesatacritical timewhenaccesstoGPsisbecomingrationedbecauseoftheincreasingdemand. Benefitstohealthserviceprovidersarebecomingincreasinglyevidentasweengagewithhealthserviceproviders onthedevelopmentofsustainablebusinessmodelsforthecontinuationandindeedextensionoftheproject. Moreefficientuseofexistingclinicalstaffandreducedtraveltimeimpactdirectlyonbudgets. ThehealthworkforcehasgrowntobethelargestinAustraliaatapacethatisunsustainableandwhichmayimpact ontheavailabilityofpersonnelinotherproductiveelementsoftheeconomy.Moreefficientuseofexistingstaff throughbetterpatientmanagementandincreasedcase-loadswillmakeacontributiontobluntingtherateof increaseofdemandforstaff,andtheasynchronousnatureofmonitoringpatienthealthstatusmayencourage someofthe34,712RNsnotintheworkforcetoconsiderPTorFTre-entryintotheprofession. CSIROTelehealthTrialFinalReportMay2016 Page108of187 Healthcareprovidersinvolvedinthestudywereinterviewedbothindividuallyandcollectivelythroughfocusgroupsand theirviewshavebeensystematicallydocumented.GPcommunicationforumsandworkshopswerealsoorganisedata numberoftestsites. Resultsindicatethatcommunitynursescaneasilyidentifythebenefitsofathometelemonitoring,suchaspreviously unavailablelongitudinaltrackingoftheirpatients’condition,reducedneedtotraveltovisitpatients,greaterclinical preparednesswhentheyvisitpatients,improvedpatientawarenessoftheirconditionandgreaterpatientself- management. Communitynursesaregenerally,butnotuniversallystrongadvocatesofathometelemonitoring.Itisalsoevidentthat beforethebenefitsofhomemonitoringcanbeappreciated,existingworkplaceculturesmustberecognisedanddealt withcooperativelythrougheducationandtraining.Itislikelythatatsomesitesthisneedwasunderestimated. Communitynursesoftenhaveaverystrongpatientcentricfocusanddevelopcloserelationshipswithpatients,and someexpressconcernsthathometelemonitoringwillunderminethecapacityofnursestodeliverfocused, individualisedcaretopatients.However,mostnursesworkingwithpatientsinthecommunitybegintovalueand ultimatelydependonthecarecoordinationprovidedbythemonitoringnurseandrecognisetheirsignificant contributiontomorecosteffectiveandimprovedpatienthealthoutcomes. GPsareasyetlessengagedwithtelehealthwith17.9%notwishingtobeengagedatallwiththemonitoringofthe patient,andonly18.6%wishingtoviewpatientdataonline.Theremaining63.5%preferredtoreceivereportsontheir patientconditionviae-mailorfax.GPsweregenerallysurprisinglypoorlyinformedoftherangeandsophisticationof telehealthservicesavailableandweregenerallyunawareofthelargeinternationalliteratureavailableonthesubject. AtleasttwoGPsrefusedtoprovideconsentfortheirpatientstoparticipateandrefusedtoengageinanydialogueto explaintheirdecision. WhilstitispossiblethatalargeGPpracticeinaruralorremotelocationmaywishtoundertaketheclinicalmonitoring functionforacohortoftheirchronicallyillpatients,noremunerationexistsatpresenttofundthisserviceandGPs engagementwithtelehealthisprimarilylimitedtobeinginformedofanexacerbationoftheirpatient’sconditionbythe CCCandarrangingforthatpatienttovisitthesurgeryoronoccasiontobetransferredtohospitalviaambulance.These servicesaretypicallyremuneratedviastandardMBSItemnumbers 6.5 IntegrationofTelemonitoringservicesintothehealthcaresector Evidencecollectedtodayfromthetrialaswellastheinternationalevidencestronglysuggeststhatamonitoringservice needstobecloselyalignedwithalltheserviceswhichdelivercareinthecommunityandshouldhaveageographic reachwhichisalignedtoalocalhealthdistrict(LHD)orprimaryhealthnetwork(PHN). Withinsuchanentity,primarycareistypicallydeliveredthroughGPs,andcommunitynursesemployedbytheLHD,as wellastheprivatenotforprofitagedcaresectorandprivateproviders.Atthisstageinthedevelopmentoftelehealth services,anyofthesecareprovidersmaybecapableofprovidingatelehealthmonitoringandtriageserviceintheir areaifproperlyresourcedandtrainedtodeliverahighqualityservice. Monitoringservicesoperatingclosetothepatientcoalfacemayhavemanyadvantages.Howeverpossibledifficulties includefragmentationandpatchyandinconsistentlevelsofservicereflectingthequalityandtrainingofstaffavailable. Tomakethismodelworkwouldrequiresignificantlevelsofgovernmentinputtodevelopnationalgovernancemodels andlicencingarrangementsthatensureaconsistentlyhighlevelofserviceprovidedbyasmanyas31monitoring centresnationally,possiblyco-locatedwiththe31PrimaryHealthNetworks. HealthserviceorganisationscapableofprovidingatelehealthmonitoringserviceincludetheLocalHealthDistricts, PrimaryCareNetworks,andnotforprofitandfaithbasedhealthserviceproviderswhocurrentlyprovidealarge proportionofagedcareservicesinthecommunity. CSIROTelehealthTrialFinalReportMay2016 Page109of187 Analternativemorecentralisedmodelfortheoperationofmonitoringcentres,wouldbetheestablishmentofstate basedorevennationalcallcentres,staffedbyhighlytrainedcliniciansandsupportedbyextensiveICTresourcesfor automatedriskstratificationanddecisionsupportaswellasdetailedwebbasedelectronichealthrecordsofevery patientbeingmonitored,withdataontheirGP,theircommunitynurseaswellasfamilyandcommunitysupport networks. SuchacallcentrewouldalsobelinkedtomajornationalinitiativessuchasthePCEHR,theNeHTANationaleHealth Architecture,andtheeHealthInteroperabilityFrameworkaswellasthefoundationsestablishedbytheDepartment andHealthandAgingsuchastheHealthIdentifiersService,SecureMessageDeliveryandB2BServicesallowingthe developmentofsophisticatedpopulationbasedaswellasindividualpredictiveanalytics. 6.6 Sustainabilityoftelehealthenabledhealthcareservices DiscussionsstartedinNovember2014withallsitesregardingacontinuationoftheexistingtelemonitoringservicefor managingthechronicallyillinthecommunity.TwoMedicareLocalOrganisationswerefacingimminentclosureand werethusunabletoplananongoingtelehealthservice.AnglicanRetirementVillagesinNSWagreedtoextendtheir telemonitoringservicetoatotalnumberof40,andDjerriwarrhHealthServices(VIC)hascontinueditstelemonitoring servicefundedthroughinternalcostefficiencies,butisseekingstateGovernmentfundingtosupportanongoing service.ACTHealthwillcontinueandintendstoexpanditsexistingtelehealthservice. TelemedcarehaspartneredwithNorthernAustraliaPrimaryHealthLimited(previouslyTownsvilleMacKayPrimary HealthNetwork)andthelocalGPDivision,tosubmitabusinesscasetoTownsvilleHospitaltomanageanincreasing proportionofpatientswhoareadmittedfrequentlytothehospitalfortheirchroniccondition.Theproposalstartswith apreliminarycohortof500patientsandincreasesto2350patientsinthethirdyear.Thisproposalhasbeenaccepted inprinciplebyTownsvilleHospitalandadetailedsubmissionisbeingpreparedforfundingundertherecently announced$35mQueenslandHealthInnovationFund. Thisexcitingproposalhasthepotentialtoprovidethetemplateforsimilarmodelstobedeployedinall31Primary HealthNetworksinAustralia. Factorsinhibitingsustainabilityoftelehealthservices Therearemanyfactorsthatneedtobeconsideredinordertoachievesustainabilityoftheexistingservices.Funding andgovernancearetwokeyissues.SomefundingmechanismsfortelehealthalreadyexistthroughtheConsumer DirectedCareprogramoftheCommonwealthDepartmentofHealth.Howevertheseonlyapplytopatientswhoarein receiptofPackagestypicallyadministeredbyanagedcareserviceprovider. WerecommendthatadditionalresearchisundertakentodevelopAgedCareAssessmentprotocolswhichtakein considerationallaspectsofthepatient’sneedsandareabletoallocatearangeofservicesincludingathome telemonitoringtobettermanagethepatient’sconditioninthecommunity. Asstatedearlier,theonlyorganisationforwhichthereisanoptimalalignmentofcostandbenefitistheLocalHealth District,aStatecontrolledentityfundedprimarilybytheStatebutsupportedbytheCommonwealththroughvarious costsharingarrangements.LocalHealthDistrictshavetheclinicalresourcesandtheincentivetoprovidetelemonitoringservicesfortheirhighcostchronicallyillpatients,buttheevidencetodateisthattheylackthe organisationalmanagementcapabilityandtechnicalexpertiseaswellasgovernancestructurestoestablishand maintainaneffectivetelemonitoringservice. Themosteffectivewayofachievingsustainabilityintheprovisionoftelemonitoringservicesisinourviewtoestablisha NationalOfficechargedwithresponsibilityfordevelopingGovernanceModels,licensingandeducationalprogramsfor theoperationoftelehealthservicenationallyandthentoprovidefundingforeligibleorganisations,eitherpublic,not forprofitorforprofit,whocanguaranteeapopulationbaseofatleastonehundredpatientsfortheservicebasedona robustassessmentofpatientneeds.Thisisadistributedmodelthatshouldbeconsideredasastartingpointfor promotingthedevelopmentofsustainablemodelsnationally. CSIROTelehealthTrialFinalReportMay2016 Page110of187 AnalternativemodelworthyofconsiderationistohaveeachStateestablishanorganisationsimilarinfunctionand purposetotheOntarioTelemedicineNetwork14(OTN)inCanadawhichprovidespolicyinput,technicaland infrastructuresupporttolocalhealthdistrictsinthatstatetoestablishtelehealthservices. AnothermodelbasedonaPrivatePublicpartnershiparrangement,wouldbefortheCommonwealthandState governmentstousetheirextensivepatientdatabasestodeveloprobustdataanalyticaltechniquestoidentifypatients atriskofavoidablehospitalisationbecauseoftheirchronicconditions,andthenwritetendersforpublicandprivate entitiestodelivertelemonitoringservicesatsufficienteconomiesofscaletopromotequalityofservicesanddeliver significantcostefficiencies. IncentivesforprivatesectorinvestmentintoTelehealth Aspreviouslydiscussed,therearenumerousmodelsforthedeploymentoftelehealthnationally,providingthata marketisformedthatallowssufficienteconomiesofscaletobeachieved.Onewaytoincentiviseprivateinvestments intotelehealth,wouldbefortheCommonwealthandStategovernmentstousetheirextensivepatientdatabasesto developrobustdataanalyticaltechniquestoidentifypatientsatriskofavoidablehospitalisationbecauseoftheir chronicconditions,andthenwritetendersforpublicandprivateentitiestodelivertelemonitoringservicesatsufficient economiesofscaletopromotequalityofservicesanddeliversignificantcostefficiencies. Averysimpleanalysisofpopulationdemographicsbyage,chronicconditionsandriskofhospitalisationsuggeststhat approximately500,000–750,000peopleinAustraliawouldbenefitfromathometelemonitoring.Ifacriticalmassof patientstoachieveeconomiesofscaleweretobeintheorderof10,000patients,then50telemonitoringcentres wouldbeneedednationally,eachfundedatalevelofapproximately$40meach,atatotalcostof$2b.Withmeans testingandcostsharingtheCommonwealthinvestmentcouldbereducedtotheorderof$1bannually. Ifonehospitaladmissionforachronicallyillpatient,atanaveragecostof$6,000couldbeavoided,costsavingsofthe orderof$3bperannumcouldbeachieved,areturnoninvestment(ROI)ofbetween2and3.Additionsavingswould alsobemadefromafarmoreefficientuseofexistingclinicalresourcesincludinga2-3foldincreaseincaseloadfor eachcommunitynurseandareductioninpatientvisitstotheirGP. Awell-regulatedtelehealthmarketexceeding$2bperannumwouldbesuretoattractprivatesectorcompetitionand investmentsintotelehealth. InternationalevidenceforwideradoptionofTelemonitoringservices WhilstthemarketfortelehealthservicesinAustraliaandtoalesserextentinEuropeisstillinitsinfancy,arecentvisit totheAmericanTelemedicineAssociationandareviewoftheprogramandthelistofexhibitorsprovidedclear evidencethatacombinationofchangesinGovernmentregulationsandlicencingaswellasincreasedstateandfederal fundingandothereconomicimperativeshaveledtoquitewidespreadadoptionoftelehealthservicesinalmostevery stateintheUSA. AnumberoflessonscanbetakenfromtheUSexperienceoftelehealthfunding15.In1997,theBalancedBudgetAct mandatedthatMedicarereimbursefortelemedicineservices.Howeveranumberofconstraintsmadethepractical provisionofservicesdifficult.In2000CongresspassedtheBenefitsImprovementAct(BIPA),whichsetafeepervisitto coverfacilitycostsat‘originatingsites’(wherepatientexaminationoccurs);increasedthenumberofeligibleCPTcodes; expandedeligiblesitestoincludeanyruralareawithprofessionalshortagesandexpandedthedefinitionof‘originating site’toincludehospitals,ruralhealthclinicsandpractitionersoffices.Theseflexiblereimbursementprocedures incentivizehealthprofessionalsandencouragetheuseoftechnology.Mostprovidersbillasusualanddonotuse modifiersorspecializedCurrentProceduralTerminology(CPT)codes.Serviceprovidersgenerallyconsidertelemedicine 14 https://otn.ca/en 15 Naditz,A.Medicare’sandMedicaid’sNewReimbursementPoliciesforTelemedicine.Telemedicineande-Health14(2008),21-24. CSIROTelehealthTrialFinalReportMay2016 Page111of187 servicesinthesamewaytheywouldface-to-facemedicalpracticesandconsider‘specialcoding’systemsasgenerally beingcounter-productive. RecentlyH.R.5380,theMedicareTelehealthParityActof2014,wasintroducedwhichimprovestelemedicinecoverage inMedicare.H.R.5380createsaphasedapproachoverfouryearstoexpandcoverageoftelemedicine-provided servicesandremovearbitrarybarriersthatlimitaccesstoservicesforMedicarebeneficiaries.Includedinthese provisionsarethegradualremovalofgeographicrestrictionstopatientcare,andtheadditionofcoveragefor healthcareservicesthattakeplaceinotherlocationssuchasthehomeandwalk-inretailhealthclinics. Thebillalsoproposesimprovementsforcoveredservicessuchasservicesprovidedbydiabeteseducators,remote patientmonitoringforchronicdiseasemanagement,outpatienttherapies,hometelehealth,hospice,andhome dialysis.TheproposalauthorizestheGovernmentAccountabilityOffice(GAO)tostudythecostandclinical effectivenessofthesechanges. Thenumberofonlinemedicalconsultationsisexpectedtoincreasefromlessthanone-tenthof1%ofthetotalfor medicalconsultationstodayto20%ormorewithinthenext20years.Hospitals,healthsystems,healthplans, employers,andprovidergroupshaverapidlybeenadoptingtelehealthforitsabilitytoincreasereach,bettermanage chronicallyillpatients,andproducebetterclinicaloutcomes. Asaresult16DemocratsandRepublicansfromboththeHouseandtheSenatecametogetherinabipartisaneffortto introduceimportantlegislationwithsignificantpositiveimpactfortelemedicine.TheCreatingOpportunitiesNowfor NecessaryandEffectiveCareTechnologiesCONNECTforHealthAct(S.2484intheSenateandH.R.4442intheHouse) willgreatlyexpandproviders’abilitytoleverageinnovativetelehealthhealthcaretechnologiestoincreaseaccessto healthcareforMedicareenrolees—andbeappropriatelypaidfordoingso. Butastheproliferationofthesetechnologieshasincreased,Medicarepolicyhaslaggedsignificantlybehind.The infrastructureforcommercialandMedicaidpaymentfortelehealthandremotepatientmonitoringhassteadily improved,withstatesandhealthplanscommittingtoreimburseproviderswhoextendtheircarethroughtechnology. OnlyMedicarehasremainedstuck,requiringpatientstodrivetothecaretheyneed,ratherbenefitingfrom technologiesthatcanbringthecaretothem.Uptothispoint,onlyruralMedicareenroleescouldbenefitfromthese innovativecaremodels,andthenonlyiftheywerewillingtotravel. TheConnectforHealthActwillhelpproviderstransitionfromtoday’sfee-for-serviceenvironmenttothegoalsof alternativepaymentcreatedbytheMedicareAccessandCHIPReauthorizationAct(MACRA).Providersmakingthis transitionwillbeabletousetelehealthandremotepatientmonitoringwithoutthecurrentgeographicbarriers. Telehealthwouldbecomepayableinalternativepaymentmodelswithoutsiterestrictions,andbecomeapartofthe basicbenefitspackageforMedicareAdvantage.Thebillwillalsosignificantlyincreasethenumberofapproved locationsandusecasesforleveragingthesetechnologies. Thisannouncementmarksthemostsignificantefforttoembracetechnologyasavitalpartofourhealthcare ecosystemsinceEMRs.With50millionMedicareenrolees,manycopingwithmultiplechronicconditions,mobility issues,andsignificantwaittimestoaccesscare,it’stimetotakeoffthehandcuffs. TheUSAisusingacombinationofchangesinGovernmentregulationsandlicencingaswellasincreasedstateand federalfundingandothereconomicandmarketimperativestodrivewidespreadadoptionoftelehealthservicesin almosteverystateintheUSA. ClearlyinthisrespecttheUSAissomeyearsaheadofAustraliaincreatingthelegislativeframeworkandthemarket conditionforlargescalenationaldeploymentoftelehealthservicesinAustralia. 16 https://www.americanwell.com/new-bipartisan-legislation-promotes-telemedicine/ CSIROTelehealthTrialFinalReportMay2016 Page112of187 7. Financial Projectfunding,expenditureandin-kindsupportispresentedbelow.Theincomeandexpenditurepresentedintable belowisfortheDepartmentofHealthfundingperiodwhichendedinSeptember2014. FollowingtheDepartmentofHealthfundingperiod,CSIROcontinuedthetrialtoobtainatleast6monthstelehealth monitoringdatauntilendDecember2014.Followingthecompletionofthismonitoringphase,datacollectionand analysiswasundertakentofinalisetheevaluationfollowedbypreparationofthisfinalreport. AfinancialreportdetailingstatementofreceiptsandexpenditureinrespecttofundsprovidedbyDepartmentof Health,clarifyingallfundingexpenditurethroughouttheprojectfundedperiodwaspreparedbyanapprovedauditorat CSIROandthisauditedreportwassubmittedandapprovedinNovember2014bytheDepartmentofHealth. Tablebelowsummarisestheauditedincomeandexpenditurestatementasat30September2014. Fromtheaboveexpenditurereportthetotalexpenditure(cash)oftheprojectwas$3,558,624.Therefore,comparedto theoriginalbudgettheprojectwas$51,757overspentwhichis<2%overbudget. AsdiscussedaboveaftertheDepartmentofHealthfundingperiod,CSIROcontinuedthetelehealthtrialuntilend December2014andcompletedthedatacollection,analysisandwritingofthisfinalreport. Thisextensionoftheprojectcosted$344,000whichwasfundedbyCSIRO. CSIROTelehealthTrialFinalReportMay2016 Page113of187 Tablebelowsummarisesthein-kindsupportprovidedbypartnerorganisationforthisproject. InKindSupportfromPartnerOrganisations(exc.GST) ClinicalserviceProviders $792,237 Telemedcare $315,789 SamsungElectronics NetworkServicesProvideriiNet TotalIn-Kind $58,500 $137,549 $1,304,075 Totalprojectvalueisdetailedbelow: ExpenditureuntilendSep2014 $3,558,624 ExtensionoftheProject $344,000 In-kindfromallpartners $1,304,075 TotalProjectCost $5,206,699 CSIROTelehealthTrialFinalReportMay2016 Page114of187 8. Appendix 8.1DataArchitecture Thisstudyhadcomplexdatamanagementandorganisationalrequirementsbyvirtueofitsoperationinfivedifferent locationinfivedifferentstatesandterritories,eachwiththeirownEthicsrequirementsandwithdifferenthospital systemsfromwhichtosourcehospitaldata.Inthissectionwedescribeasecureandeffectiveservice-oriented approachforsecurelymanagingtelehealthservicesresearchdata. Thedataarchitectureanddataintegrationservicesdevelopedaspartofthisprojectmadeaconsiderablecontribution toresearchandbeinginthepublicdomain,warrantcloserexamination.Amoredetaileddescriptionhadbeen publishedelsewhere[39]. • • • • • • • • Datawascollectedinthisstudyfrommanydifferentsources,inmultipleformatsandwithvaryinglevelsof automation,withsomerequiringconsiderablemanualprocessing.Asimplifieddiagramofdatasourcesusedin thisstudyisshownschematicallyinFigure7. EntryandExitQuestionnaireswereadministeredonlinebyPOswhenTestandControlpatientswereconsented andwerestoredinOpenClinica17,theworld'sfirstcommercialopensourceclinicaltrialsoftwareforElectronic DataCapture(EDC)andClinicalDataManagement(CDM). PeriodicQuestionnaires(daily,weeklyormonthly)werescheduledontheTMCclinicianwebsiteandwere presentedandadministereddirectlyonthepatienttelemonitoringsystem.TheresultswerestoredintheTMC servers. Patientvitalsignswererecordedaslongitudinalrecordsandoriginalwaveformswererecordedandstoredin theTMCserverforqualitycontrolanddiagnosticpurposes.Allrecordswereaccessibletothecliniciansviathe TMCclinicianportal. HospitalDatawassourcedfromthePatientAdministrationSystemsofhospitalsservicingthetrialsitesandwas suppliedintheformatoftheHospitalRoundtable18.Thiscomprehensivedatasetwasrequestedforthe4.5 yearperiodofJuly2010throughto31stDecember2014. PBSandMBSdatawereprovidedbytheDepartmentofHumanServicesfollowingsuccessfulEthicalClearance bytheDepartmentandonreceiptofsignedconsentformsfromallpatients.Datawasmadeavailableforthe 4.5yearperiodofJuly2010throughto31stDecember2014. HIEDatafromfocusgroupsandstructuredinterviewsweretranscribedandannotatedbeforestoragein OPenClinica. ClinicaleventsanduserexperienceswerestoredintheCSIROportal.Theportalalsoservedasameansof communicationbetweenresearchersandcliniciansinthefieldandlinkingtoarangeofservices. Liferay19,anopensourceenterpriseportalwritteninJavaanddistributedundertheGNULesserGeneralPublicLicense, wasusedtodeveloptheCSIROTelehealthPortal.Liferayprovidescontentmanagement,collaboration,andsocial networkingfunctionalities,alongwithenterprisedatabasesanddocumentmanagementsolutions. 17 https://www.openclinica.com/ 18 https://www.healthroundtable.org/ 19 https://www.liferay.com/products/liferay-portal/overview CSIROTelehealthTrialFinalReportMay2016 Page115of187 Keyservicestousersincludedarolebaseduserauthenticationservice,socialnetworkservicetoprovideacommon forumforallresearchersandclinicalparticipantsaswellasarangeofdataservicessuchasactivitylogs,dataanalytics, patientdata,accesstoTMCandaccesstoOpenClinicaandprivatedocumentsasshowninFigure35below. Figure35CSIROPortalshowingbasicfunctionalityandaccesstomultipleservices. Thesedataservicesweresupportedbythreetypesofunderlyingdatamanagementsystems.Datafromservicessuchas TMCandactivitylogswerestoredinaMySQLdatabaseaslinkeddatabehindtheenterprisefirewall.Datacontaining patientpersonalinformationsuchasconsentdocumentssignedbypatients,andpatientpersonaldatausedforcreating linkeddataalsoneededtobemanagedandstoredsecurely.ThedocumentdatawasmanagedusingMicrosoft SharePoint,whereasasecureencrypteddatabasewasusedtomanagepatientpersonaldata.Allpatientpersonal attributessuchasfirstname,surname,dateofbirth,contactdetails, emergency details, contact GP/nurses, etc.were encrypted using theAES(AdvancedEncryptionStandard)algorithmwitha128bitkeylength. Alinkfileusingauniqueidentifierforallpatientswasusedtolinkdatacomingfromvariousdatasources.Sinceall patientswereenrolledonlineusingOpenClinica,theOpenClinicaIdentifier(OCID)wasusedasauniqueidentifierforall patientsenrolledinthestudy. Thereweretwodifferentmechanismsforcreatinglink-file.Inthefirstphase,thePOobtainedthesignedconsentform fromthepatientandthenenrolledthepatientsforthetrial.ThePOcollectedpatients’generaldata(whichwasdeidentified)andprivatedata(whichwasidentifiable)aspartoftheenrolmentprocess.ThePOthenenteredthedeidentifiedgeneraldataintoOpenClinicawhichassignedauniqueidentifierforthepatient,theOpenClinicaID(OCID) whichwasusedasauniqueidentifierforcreatingthelink-fileandlinkeddata.Theprivatepartofthedatawasthen storedinasecureencrypteddatabasebehindtheCSIROfirewallalongwiththeOCID.Thisprocesslinkedtheprivate andpublicpartsoftheentryquestionnairethroughOCID.Inthesecondphase,datacomingfromdifferentsources, suchasHospitalsortheDHSwerealsolinkedviatheOCID. OnlytheProjectDirector,theProjectManagerandtheClinicalTrialCoordinatorhadaccesstopersonalisedpatient data. CSIROTelehealthTrialFinalReportMay2016 Page116of187 8.2 DataIntegration Tointegratetelehealthserviceswithexistingmulti-disciplinaryhealthcareservices,acloudbasedtelehealthsystem usingSOA(Service-OrientedArchitecture)conceptswasdesigned,implementedanddeployed. Figure36DataIntegrationschemadevelopedbytheCSIROforthetrial Thetelehealthsystemwasdesignedtoworkasalight-weighttrustedthirdpartyservicebroker.Thehighlevel architecturalviewoftheservicebrokerisshowninFigure36.Thebasicideawasthateachserviceproviderpublished itsserviceswithappropriateauthenticationandauthorisationpolicies.Theauthenticationandauthorisationpolicies strictlyfollowedtheethicsclearanceobtainedfromeachserviceprovider.Theservicebrokercouldauthenticateto accesseachservice,andmadetheintegratedserviceavailabletocareteam(i.e.,CCC,generalpractitioner,etc.)and researchteam(i.e.,dataanalysts)followingthedataaccessandretentionpoliciesasspecifiedintheethicsclearance documentsfromdifferenthealthcareservices. Theservicebrokerprovidedascalablesolutionastherewasnodefinedlimittonumbersandtypesofservices. Furthermore,theinteractionsbetweenexistinghealthcareservicesandtheservicebrokeroccurredthroughmessages. ThemessageswereexchangedinXMLformat.ThoughtheimplementationdidnotuseHL7standard,weusedXML messageswiththeviewthatitcouldbepossibletomakethesystemHL7compliant. Theservicebrokerwasimplementedasacloudservice.Hence,therewasnoperformanceissueasthesystemtookthe benefitsofscalability,availability,andelasticityofferedbycloud.Thoughthebrokerwasdesignedtobeimplemented asalightweightservice,thetelehealthsysteminthecurrentimplementationfortheprojectactuallycollectedalldata andintegratedthem.Someoftheintegrationtaskscouldbeoff-loadedtootherservices(e.g.,decisionsupport service). CSIROTelehealthTrialFinalReportMay2016 Page117of187 DHSPBS/MBSDataformat CSIROTelehealthTrialFinalReportMay2016 Page118of187 HealthRoundtableFormat TheHealthRoundtable InpatientDataSpecifications 2013Julyto2014June ReleaseDate28/07/2014 Version:v1a DataSubmissionsDue:15thAugust2014(forinclusioninfirstroundofreports) Formoreinformationcontact:[email protected] +61(0)430097930 Wetrytoacceptwhateverdatayouhaveavailable;inwhateverformatyouhavetomakeitassimpleaspossiblefor eachhealthservice.Wewillletyouknowifwehavetroubleinterpretingwhatyousendus. ChangeHistory: 1. v1areleased,nochangesfrom2013Jul-Decdataspecs. TableofContents Overview 3 DataSpecifications 4 Episode/DemographicDataTable 4 DiagnosisCodeDataTable 8 ProcedureCodeDataTable 9 SNAPCodeDataTable 10 Overview Overviewofthe4tablesrequested CSIROTelehealthTrialFinalReportMay2016 Page119of187 DataSpecifications Pleasesupplythefollowinginformationforeachinpatientdischargedfrom01/07/2013and30/06/2014inclusive.Please submitseparatedemographic,diagnosis,procedure,andsnapcodedatatables. FieldsColouredThusareusedbytheNationalEfficientPricecalculation NOTE:Pleasesupplythefollowinginformationforeachadmittedepisode,whethertheyareacuteornon-acute/subacute. Episode/DemographicDataTable Field Format PossibleValues HospitalIdentifier A3 Any--constantforallrecordsinahospital’sdataset.Usea differentidentifierforeachfacilitytobeanalysedseparately. (Pleaseprovidelookuptabletoexplaintheidentifiers) SequenceNumber N10 Startwith2013000001incrementsbyoneforeachepisode dischargedon/after1July2013. UnitRecordNumber A10 Anyuniquepatientidentifiercommontoallepisodesfor thatpatient(encryptedidentifiersarepreferred,butthey mustrefertothesamepatientovertimetoenableanalysisof readmissionrates) EpisodeNumber A15 Anyuniqueepisodeidentifier.Thisfieldisalsousedtolinkto clinicalcostinginformation.Thisshouldbeauniquekeyfield foreachepisoderecord. AdmissionType A2 HospitalDefinedCodes,tobeusedprimarilytodistinguish betweenEmergencyandElectiveadmissions. Iftheadmissioncouldbeputofffor24hourswithoutadverse effectstothepatienttheadmissionshouldbeconsidered Elective.Directadmissionstowardsshouldbecodedbased onthe24-hourrule. EmergencyEventID A30 IfthepatientwasadmittedviatheEDthisistheevent identifierusedintheEDsystem.Usethesameencryption usedintheHRTEDdatasubmissionifanyisused. SourceofReferral A1(orhospitaldefined codesandtable) Indicateswherethepatientcamefrom:1=transferredfrom anotherhospital,2=typechange,3=admissionfromleave,4= other. AdmissionDate A10 Preferredformat:dd/mm/yyyy AdmissionTime A8 Timefrom00:00to23:59(Secondsoptional) SeparationDate A10 Preferredformat:dd/mm/yyyy SeparationTime A8 Timefrom00:00to23:59(Secondsoptional) BirthDate A10 Usethefollowingformat:dd/mm/yyyy AgeinYearson AdmissionDate N3 Padwithblanksifnotavailable.Validvaluesinclude000to 150 CSIROTelehealthTrialFinalReportMay2016 Page120of187 Field AgeinDays Format PossibleValues N3 Requiredifpatientislessthan365daysold AdmissionWeight *<1monthold N4 Weightingrams0001-9000 NeonatalLinkagetoMother’sEpisode A15 HospitalEpisodeNumberofmotherfornewbornsadmitted(includingstillbirths). Leaveblankifnotapplicableoravailable. A1 “M”or“1”=male“F”or“2”=female“X”or“3”=unknown IntendedLOS N1 RequiredifMDC10RehaborAftercareDRGs1-sameday,2-overnight,0-notentered Gender HoursonMechanicalVentilation N4 Numericdatainhours0-9999–requiredforgroupinginsomecases AcuteLOS N4 Numericdays. ICUHours N5 HoursinICU,roundedtonearesthour HospitalintheHome(HIH) N3 Numericdays.Numberofwholedayspatientwasin"HospitalintheHome"inthis episode.NotethesearesubtractedfromLOSsodonotincludeHITHdaysafterthis episodeended.DonotincludethisvalueifyougenerateanewepisodeforHITH portionofstay. MentalHealthLegalStatus N1 1=involuntarypatient,2=non-involuntary(ifblank,assumenon-involuntary) LeaveDays N3 Numericdays.Numberofdayspatientswereonleaveduringtheinpatientepisode. Note.ThesearesubtractedfromacuteLOS. NumberofPsychiatricCareDays.(NumberofQualifiedDaysforNeonates) N3 NumericDays.Thenumberofdaysinpsychiatriccare. SeeMETeORidentifier270300. N3 NumericDays.TheNumberofdaysaneonateisqualifiedasaseparateadmissiontothe motherformedicalcare.SeeMETeORidentifier270033,269504,327254. CareType HospitalDefined(pleasesupplyexplanatorytable) Indicateswhetherapatientisunderacuteornon-acutecare(egAcute,rehab,palliative,etc). Seehttp://meteor.aihw.gov.au/content/index.phtml/itemId/270174forexample. ForNZhospitals,thisshouldbethe3-characterHealthSpecialtyCode(wheremorethanoneHSCisavailableforan episode,assignthedischargeHSC).ThesewillthenbemappedbytoAustralianstandardcaretypes.Noexplanatory tableisnecessaryinthiscase. CSIROTelehealthTrialFinalReportMay2016 Page121of187 Field Format PossibleValues SeparationMode N2 Standardisedcodes01-09(CommonwealthDefinitions-See 3MGroupercodedefinitions) DRGAssignedby Hospital A4 PleaseprovideDRGifalreadyassignedbyhospital–Wewill validateindependentlyusingVisasysDRGGrouper(Please indicatetheDRGversionyouareusinginthe Facilityregionidentifier N2 Regionoffacility. Regioncodesare: 01=NewSouthWales 02=Victoria 03=Queensland 04=SouthAustralia 05=WesternAustralia 06=Tasmania 07=NorthernTerritory 08=AustralianCapitalTerritory 09=Otherterritories(Cocos(Keeling)Islands,Christmas IslandandJervisBayTerritory) 10=NewZealand Areaofusual Residence N5 5digits=StatisticalLocalArea(Australia)orDomicileCode (NZ).NoteassomePASsystemsonlyallow4digitsforthis fieldhealthservicesareprovidingthe4leftmostdigitsofthe SLA.Ifthisisthecasecanyouletusknowinasupporting document. N1 1= Serviceprovidedbythishealthserviceundercontract fromanotherpublichealthservice residenceof patient EpisodeProvider ContractCode 2= Serviceprovidedbythishealthserviceundercontract fromanotherprivatehealthservice 3= Serviceforthisepisodeprovidedbyanotherpublic healthservice 4= Serviceforthisepisodeprovidedbyaprivatehealth service FinancialClass A2 9–Nootherhealthserviceinvolvedcontractuallyinthis Hospitaldefinedcodestoindicatewhetherthepatient’scare episode isfundedbythestatehospitalsystem(“Public”patient),orby anyothermeans.Pleasesupplycodesalongwiththedata. ForNZhospitalspleaseusethePrincipalhealthservice purchasercodingfromtheNMDS. FundingSource N2 Fundingsourceforhospitalpatient,range01to13with 99=NotKnown[METeORidentifier:339080] CSIROTelehealthTrialFinalReportMay2016 Page122of187 Field Format PossibleValues EthnicOrigin A4 Codeindicatingethnicoriginofpatient ForAustralianHospitals: 1.AboriginalbutnotTorresStraitIslanderOrigin 2.TorresStraitIslanderbutnotAboriginalOrigin) 3.BothAboriginalandTorresStraitIslanderOrigin 4.NeitherAboriginalnorTorresStraitIslanderOrigin 5.Notstated/Inadequatelydefined ForNewZealandHospitals:StandardEthnicCode EthnicGroupcode:EthnicGroupcodedescription 10Europeannorfurtherdefined 11NZEuropean 12OtherEuropean 21NZMaori 30PacificIslandnotfurtherdefined 31Samoan 32CookIslandMaori 33Tongan 34Niuean 35Tokelauan 36Fijian DischargeUnit A10 DischargeWard A20 ClinicalSubunit A10 Identifier DateofDeath A10 37OtherPacificIsland Codeindicatingthenameoftheclinicalunitthatdischarged thepatient.(pleaseprovidealookuptablewiththefulltext 40Asiannotfurtherdefined oftheunit’sname) 41SoutheastAsian Codeindicatingthenameofthewardthatthepatientwas 42Chinese dischargedfrom. 43Indian Anyuniqueidentifieroftheclinicalserviceprovider(s) responsiblefordischargeofthepatient.Itcanbeaclinician, 44OtherAsian oragroupofclinicalproviders(egclinicianandassociated 51MiddleEastern registrars).Thisshouldbeencryptedlocallybyyourhealth service.Pleasedonotsendidentifiersthatcouldbe recognisabletocliniciansatotherfacilities. Preferredformat:dd/mm/yyyy(Ifavailable)–dateofdeath shouldbeincludedevenifnotassociatedwiththisepisodeof care. CSIROTelehealthTrialFinalReportMay2016 Page123of187 Field Format PossibleValues HospitalIdentifier A3 Mustmatchtheidentifierusedinthedemographicfile UnitRecordNumber A10 EpisodeNumber A15 Mustmatchtheunitrecordnumbersinthedemographic file Mustmatchtheepisodenumberinthedemographicfile DiagnosisCode A10(nopunctuation,left (IncludingExternal justifiedandnullfilled) CauseandMorphology codes) AlphanumericICD10code,includingExternalcauseand Morphologycodes.Thesecodesmustbelistedinsequence asenteredbycoderstopreservelinksbetweencodes.The firstdiagnosisinthesequencemustbetheprincipal diagnosis. WenolongerrequireinformationontheAdmission Diagnosisintheinpatientdataset.Ifyousubmitthe admissiondiagnosis,pleasemarkitwithpositionzero(0). Makesureyouareprovidingyourexternalcausecodes sequencedcorrectlywithyourdiagnoses.See: http://meteor.aihw.gov.au/content/index.phtml/itemId/36 1926 Conditiononsetflag N1by40fields(onefield precedingeachdiagnosis code) 1= Conditionwithonsetduringtheepisodeofadmitted patientcare 2= Conditionnotnotedasarisingduringtheepisodeof admittedpatientcare 9= Notreported DiagnosisPosition Number N2 Sequencedasper AustralianCoding Standards Sequencenumberofthediagnosis/external cause/morphologyasenteredbythecoders. CSIROTelehealthTrialFinalReportMay2016 Page124of187 Field Format PossibleValues HospitalIdentifier A3 Mustmatchtheidentifierusedinthedemographicfile UnitRecordNumber A10 Mustmatchtheunitrecordnumbersinthedemographicfile EpisodeNumber A15 Mustmatchtheepisodenumberinthedemographicfile ProcedureCode A10(nopunctuation,left justifiedandnullfilled) AlphanumericICD10codesusingACHIcoding.Thefirst procedureshouldbetheprincipalprocedurefortheepisode. ProcedurePosition Number N2 Sequencenumberoftheprocedureasenteredbythecoders. SequencedasperAustralian CodingStandards ProcedureDate including investigational procedures(e.g cardiaccathlab)and vaginaldeliveries A10 Preferredformat:dd/mm/yyyy Enterthedateonwhichtheprocedurestarted,exceptfor vaginaldeliveries,pleaseincludedateofbirthinthisfield. (Requiredforthefirstprocedure.Optionalforallother procedures) ProcedureStartTime A8 Timefrom00:00to23:59 Patiententryintotheatreisthepreferredmeasureofstart time.Ifthisisunavailablepleaseusetheclosestmeasureto this. Forvaginaldeliveries,pleaseincludetimeofbirthinthisfield. (Requiredforthefirstprocedure.Optionalforallother procedures.) ProcedureElapsed Time N3 Timeinminutesfrompatient’sentryintheatretopatient’s exitfromtheatre,ifavailable,foreachprocedure. (Requiredforthefirstprocedure.Optionalforallother procedures.Wheremultipleproceduresareperformedinthe samesession,assignthefullamountoftimetothefirst procedureonly.Donotcountthepatient’stimeinthesame theatresessionmultipletimes.) CSIROTelehealthTrialFinalReportMay2016 Page125of187 SNAPCodeDataTable MultiplephasesandSNAPv3codescanexistforPalliativecareepisodes. Field Format PossibleValues HospitalIdentifier A3 Mustmatchtheidentifierusedinthedemographicfile UnitRecordNumber A10 Mustmatchtheunitrecordnumbersinthedemographicfile EpisodeNumber A15 Mustmatchtheepisodenumberinthedemographicfile SNAPv3Code A4 TheSNAPv3codeforthisEpisodeifit’ssub-acuteierehab, palliative,GEM,psychogeriatricormaintenancecare Moreinfo: http://meteor.aihw.gov.au/content/index.phtml/itemId/4964 05 PhaseStartDate DateTime Palliativecarephasestartdate.Thecommencementdateis thedateonwhichanadmittedpalliativecarepatient commencesanewpalliativecarephasetype.Subsequent phasebegindatesareequaltothepreviousphaseenddate. http://meteor.aihw.gov.au/content/index.phtml/itemId/4458 48 PhaseEndDate DateTime Palliativecarephaseenddate.Theenddateisthedateon whichanadmittedpalliativecarepatientcompletesa palliativecarephasetype. http://meteor.aihw.gov.au/content/index.phtml/itemId/4455 98 8.3 Method2:DetailedstatisticalanalysisusingBACIandlmemodels ThestatisticalanalysispresentedintheResultsmakesanumberofsimplifyingassumptions,anddoesnot analysetheimpactonspecificparameterssuchasnumberandcostofGPvisits,numberandcostsof laboratorytestsetcchoosinginsteadtocombinealltheseindividualcostsintoasingleoveralltotalMBS cost. BACIdesignandlinearmixedeffectsmodels Let bethePBS/MBS/Hospitalcostsvalueperunittimeperiod(month)attimekduringperiodi(before oraftertheintervention),forpatientj(controlorinterventionpatient).Themodelfortheresponsevalue isgivenby: !"#$ = & + (" + )$ " + *# + (* "# + +"#$ where: • • • &istheoverallmean (" istheeffectofperiod(beforeandafter) )$ " istherepeatedmeasureswithinperiods(assumedtobearandomeffect) • *# istheeffectonjthmatchedpatients(interventionorcontrol) • • (* "# istheinteractionbetweenperiodandmatchedpatientgroups +"#$ istherandomerrortermofthemodelthatisassumedtobenormallydistributedwith homogeneousvariance. CSIROTelehealthTrialFinalReportMay2016 Page126of187 Assumptionsmade: • Logofcostplusonewillbetreatedasnormallydistributedwithlogofthenumberofdaysinthe monthastheoffset.Sometimesthesquareroottransformationisusedtostabilisethevariance. Wearehopingtherearenottoomanyzerocostperiodsorzerocounts.Ifthisfailswewillusethe zeroadjustedinverseGaussiandistributionforthemodel–fittingthemusingthegamlss(package inR)usingrandom()forincludingrandomeffects(seeStasinopoulasetal.2013). )$ " isarandomeffectintheabovemodelthatisassumedtobenormallydistributedwithmean • zeroandconstantvariance. Theassumptioninthepreviousdotpointandtheassumptionfor+"#$ inthemodelthusassumes • • • • • • • • thatmeasurementsmadeatthesametimesegments(e.g.,onthesamequarter)havethesame correlationandhomogeneousvariancesforallrepeatedmeasures. Theabovemodeltreatsthestudyasafully-designedexperimentwiththeappropriate randomisation.However,thisisseldomthecasebecausemostimpactstudiesareobservationalin nature. Theassumptionisthateachmeasurementfortheinterventionpatientsismatchedwitha measurementforoneormorecontrolpatients.Thisblockingisexpectedtocontrolforthenonrandomisationinthedesign.Somepeoplehaveanalysedthedifferencesbetweenthese measurementswhichcangreatlyreducethecomplexityoftheanalysis.Ifthematchingprocess canonlydeliveroneusefulcontrolthenthiswillbetheapproachwewillfollow. Themodelabovetestswhetherasignificantchangehasoccurredbytestingthesignificanceofthe interactiontermofthemodelforthebeforeafterindicatorvariablesandthecontrol-intervention indictorvariable.Forexampleifthecoefficientforinterventionpatientsandafterintervention durationhaslowerinsuredcoststhatbeforetheinterventionafteradjustingforcontrols,thenthe interventionhashadasignificantimpactoncosts(andhencethewell-beingofthepatient).This justprovidesevidenceforimprovementincosts. Therandomeffectstermsandrandomerrortermareassumedtobeuncorrelatedintime. Thecontrolpatientisgenerallyselectedtocontrolforallcovariates.Inthisstudythismeansthat controlpatientsshouldbeidenticaltotheinterventionpatientintermsofage,gender,SEIFAindex andmajorco-morbities. Thesamplesareselectedovertime(thereforetheyaretimeseriesratherthanrepeatedmeasures madeatthesametime).Soitmayseemunlikelythatthemodelerrorswillbeindependently distributedbuthospitalcostsaremeasuresthreemonthsapartandthisshouldbeenoughtofor theassumptionofindependencetobevalid. Theassumptionthatallrepeatedmeasureshavethesamevarianceisunlikelytobetrue.Ifthe gamlsspackageisusedthenthischangeinvariancecanbeaccountedfor.Althoughtheoretically longitudinaldatastructurescanbemodelledbyrandomeffectsingamlss(RigbyandStasinopoulos, 2005)butatpresentnocomputationallyfeasibleimplementationforlargesamplesizesand complexmodelsexists. Wemayusemeasuredvariablesonpatientsascovariatestoimprovethecorrelationbetweenintervention andtheircontrolsthusmakingbetterinference.Thisonlyhelpswhenthecovariateisnotimpactedbythe change,i.e.,nointeractionbetweenthecovariateandthebefore-and-afterindicatorvariable. Inthisstudyweused4.5yearsofdatadocumentingmonthlycostsoverthatperiodthatincludeda maximuminterventionperiodofroughly12months. CSIROTelehealthTrialFinalReportMay2016 Page127of187 Thetimevaryingaspectofthedesignneededtobeconsideredbecausethecohortconsideredwasverysick andtheirconditionwouldchangeovertime.Thereforethemodelthatfittedis: !"#$ = & + (" + )$(") + *# + ((*)"# + ((/)"$ + (*/)#$ + (*/ "#$ where: • • • &istheoverallmean (" istheeffectofperiod(beforeandafter) )$(") istherepeatedmeasureswithinperiods(assumedtobearandomeffect) • *# istheeffectonjthmatchedpatient(interventionorcontrol) • ((*)"# isthatthey-intercepttermdiffersforeachpatientbyperiodgroup "$ istheinteractionbetweenperiod(before-after)andmonth • • (/ */ • (*/ "#$ istheinteractionbetweenmatchedpatientgroups(I&C)andmonth "#$ istheinteractionbetweenperiod(before-after),matchedpatientgroups(I&C)and month ThesemodelswerefittedusingthenlmepackageinR(Pinheiro,andBates,2000andPinheiro,Bates,DebRoy &Sarkar,2011). CSIROTelehealthTrialFinalReportMay2016 Page128of187 Powercalculations Thepowerofthetestsinthelinearmixedmodelwasnoteasytocompute.Thepowerofamatchpairedttestwasestimatedassumingacorrelationofρandastandarddeviationofσforthedifferencesinmatch scores,adecisionboundaryforatestofsizeκdeparturebetweenthematchscores,andnoautocorrelation withaneffectivesamplesizeof30. ThepowercalculationsbasedonindependentobservationsandtheoutcomesofthetestaregiveninTable 68below: Taking: 0 = κ/(σ 2(1 − 7 8 ) Table68PowerCalculations Outcomemeasureallon themonthlyscale Effective sample size? Assumednormaldistribution Shift amount (K) Power PBSBenefit 30 Log(PBSBenefit+1) 1 0.90 PBSTotalcost 30 Log(PBSTotalcost+1) 1 1.00 MBSoutofhospitalcosts 30 Log(MBSoutofhospitalcosts+1) 1 1.00 MBSinhospitalcosts 30 Log(MBSinhospitalcosts+1) 1 0.84 Numberofhospital admissions 30 Squarerootthenumberofhospital admissions 0.5 0.99 NumberofGPvisits duringworkinghours 30 SquarerootofnumberofGPvisitsduring workinghours 0.5 0.89 NumberofGPvisits outsideofworkinghours 30 SquarerootofnumberofGPvisitsoutside ofworkinghours 0.1 0.50 TotalnumberofGPvisits 30 SquarerootoftotalnumberofGPvisits 1 0.97 Totalnumberofeither Specialist,Psychiatric, AlliedHealthvisitsand Procedures 30 Squarerootoftotalnumberofeither Specialist,Psychiatric,AlliedHealthvisits andProcedures 1 0.77 Totalnumberof Laboratorytests 30 SquarerootoftotalnumberofLaboratory tests 1 0.97 NumberofLaboratory Tests 30 SquarerootofnumberofLaboratoryTests 1 0.96 Theactualresultsweremuchmorecomplicatedthanthisbecausethedifferencesbetweentheoutcome variablesmaybeautocorrelated.Thiswasparticularlytrueifthecontrolpatientandmatchtestpatient outcomemeasureshaddifferenttimeseriestrends.Howeverpriortothestudythiswasnotthoughtofas anoption.Testingofwhetherthematcheddifferenceswereautocorrelatedhadnotbeencarriedoutas thiswasnotexpectedtobeaproblempriortodoingthestudy.Thishoweverprovedtobeanissuewhen thedatawassubsequentlyanalysed. CSIROTelehealthTrialFinalReportMay2016 Page129of187 FinalLinearMixedEffectsModelsforMBS AlthoughwearecarryingoutaBACIdesignwewishedtoalsoestimatethetemporaltrendandthe seasonalinfluenceonthePBSscores.Wefittedthemodelsusingthelmerfunctioninthelme4Package (LinearMixed-EffectsModelsusing'Eigen'andS4(Bates,Maechler,Bolker,Walker,Christensen, Singmann,Dai,Grothendieck,2015)[ctb]inR.(seehttps://cran.r-project.org/web/packages/lme4/lme4.pdf) Thesemodelsattemptedtomodelrandomeffectsaswellasbeforeandaftereffectsforsitespecific behaviouraswellasseasonalvariationswhichweremodelledassineandcosinefunctionswithfixed periodsandvariablegains. MBSdatawasnormalisedbyapplyingthesqrtfunction.Theresultantfittedmodelwasasfollows: Linear mixed model fit by REML Formula: sqrt(1 + MBS.mcost) ~ Before.After * TC * time + sin(2 * pi * time/365.25)) Data: MBS ['lmerMod'] Sex + time + Site * Before.After * TC + period.From + (cos(2 * pi * time/365.25) + + (1 | OCID) + (1 | period.From) REML criterion at convergence: 81634.8 Scaled residuals: Min 1Q Median -2.8949 -0.6529 -0.0537 3Q 0.5252 Max 8.8885 Random effects: Groups Name Variance Std.Dev. period.From (Intercept) 0.00 0.000 OCID (Intercept) 9.56 3.092 Residual 62.64 7.915 Number of obs: 11661, groups: period.From, 1554; OCID, 99 Fixed effects: Estimate Std. Error t value (Intercept) 20.997630 3.751492 5.597 SexM -0.386103 0.353766 -1.091 time -0.005304 0.002096 -2.531 SiteTAS 0.513259 1.422100 0.361 SiteVIC 1.148710 1.440379 0.798 SiteQLD 0.221124 1.468597 0.151 SiteARV 2.945891 1.661437 1.773 Before.Afterbefore -12.909972 3.661388 -3.526 TCC -1.627148 4.783918 -0.340 cos(2 * pi * time/365.25) -0.106738 0.103674 -1.030 sin(2 * pi * time/365.25) -0.161461 0.106141 -1.521 SiteTAS:Before.Afterbefore 1.160280 1.033905 1.122 SiteVIC:Before.Afterbefore -0.272779 1.051010 -0.260 SiteQLD:Before.Afterbefore 0.854250 1.079519 0.791 SiteARV:Before.Afterbefore 0.578611 1.237747 0.467 SiteTAS:TCC -1.635062 1.215462 -1.345 SiteVIC:TCC -1.500712 1.262479 -1.189 SiteQLD:TCC -3.965552 1.327268 -2.988 SiteARV:TCC -4.875014 1.537341 -3.171 Before.Afterbefore:TCC 5.695121 4.809290 1.184 time:Before.Afterbefore 0.008837 0.002111 4.186 time:TCC 0.003614 0.002748 1.315 SiteTAS:Before.Afterbefore:TCC 0.260020 1.322369 0.197 SiteVIC:Before.Afterbefore:TCC 0.847063 1.364968 0.621 SiteQLD:Before.Afterbefore:TCC 0.685571 1.426746 0.481 SiteARV:Before.Afterbefore:TCC -0.905815 1.633601 -0.554 time:Before.Afterbefore:TCC -0.004608 0.002775 -1.661 CSIROTelehealthTrialFinalReportMay2016 Page130of187 Thesignificantinterpretationofthismodelisasfollows: 1. TheoveralltimetrendissignificantlynegativeintermsofMBScostswhichindicatesapotentially positiveresultifthisisdrivenbytheintervention. 2. ARVhassignificantlyhigherMBScoststoACTpatients. 3. BeforeMBScostsaresignificantlylowerthantheafter. 4. Seasonalinfluencesarenotindependentlysignificantlybutarejointlyjustsignificant. 5. QLDcontrolpatientshavesignificantlylowerMBScoststhanACTcontrolpatients. 6. HoweverontheotherhandbeforeMBScostsaresignificantlowerbeforetheintervention 7. ThebeforeperiodhasasignificantlyhigherrateofincreaseinMBScoststhantheafterperiod. 8. Thebeforeinterventioncontrolpatientshavealowertrendovertime–thissuggeststhatthe interventionissignificantandaclearindicationthattheinterventionreducedMBScosts significantly. CSIROTelehealthTrialFinalReportMay2016 Page131of187 TASMANIA Figure37TimecourseofMBScostsforTASpatients Figure38TimecourseofMBScostsforTASpatientswithstartmonthsynchronised. Theplotabovecombinessubjectswhosestartperiodwasinthesamemonth.Thisdoesnotidentifythe exactstartdatebuttidiesupthevisualimageproducedbytheparallelboxplotsinFigure37.Forexample thetrendchangeinthecontrolsisclearerandthedropoffinMBScostsforthetestpatientsintheafter periodisclearinFigure38. TheTASTestpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$118.40permonthon June2010whichincreasedtoanaveragecostofroughly$175.80byApril2014beforereducingtoan averagecostofroughly$136.60byDecember2014. TheTASControlpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$170.80permonth onJune2010whichincreasedtoanaveragecostofroughly231.30byApril2014beforereducingtoan averagecostofroughly$228.40byDecember2014. CSIROTelehealthTrialFinalReportMay2016 Page132of187 VICTORIA Figure39TimecourseofMBScostsforVICpatients Figure40TimecourseofMBScostsforVICpatientswithstartmonthsynchronised TheVIC(Figure39,Figure40)Testpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$ 102.30permonthonJune2010whichincreasedtoanaveragecostofroughly$188.90byApril2014 beforereducingtoanaveragecostofroughly$166.50byDecember2014. TheVICControlpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$193.8permonth onJune2010whichincreasedtoanaveragecostofroughly$259.9byApril2014beforereducingslightlyto anaveragecostofroughly$255.60byDecember2014. CSIROTelehealthTrialFinalReportMay2016 Page133of187 QUEENSLAND Figure41:PredictedMBScostsforQLDpatients Figure42TimecourseofMBScostsforQLDpatientswithstartmonthsynchronised TheQLD(Figure41,Figure42)Testpatientsatstartthestudyperiodhadanaveragecostofroughlyabout $113.90permonthonJune2010whichincreasedtoanaveragecostofroughly$179.00byApril2014 beforereducingtoanaveragecostofroughly$148.00byDecember2014. TheQLDControlpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$158.70permonth onJune2010whichincreasedtoanaveragecostofroughly$194.90byApril2014beforereducingslightly toanaveragecostofroughly$182.7byDecember2014. CSIROTelehealthTrialFinalReportMay2016 Page134of187 NEWSOUTHWALES Figure43PredictedMBScostsforNSWpatients Figure44TimecourseofMBScostsforNSWpatientswithstartmonthsynchronised TheNSW(Figure43,Figure44)Testpatientsatstartthestudyperiodhadanaveragecostofroughlyabout $163.70permonthonJune2010whichincreasedtoanaveragecostofroughly$260.40byApril2014 beforereducingtoanaveragecostofroughly$181.90byDecember2014. TheNSWControlpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$111.50per monthonJune2010whichincreasedtoanaveragecostofroughly$180.50byApril2014beforeincreasing slightlytoanaveragecostofroughly$188.90byDecember2014. CSIROTelehealthTrialFinalReportMay2016 Page135of187 AUSTRALIANCAPITALTERRITORY Figure45Figure10:PredictedMBScostsforACTpatients Figure46TimecourseofMBScostsforACTpatientswithstartmonthsynchronised TheACTFigure45,Figure46)Testpatientsatstartthestudyperiodhadanaveragecostofroughlyabout $100permonthonJune2010whichincreasedtoanaveragecostofroughly$172.8byApril2014before reducingtoanaveragecostofroughly$129.60byDecember2014. TheACTControlpatientsatstartthestudyperiodhadanaveragecostofroughlyabout$159.30permonth onJune2010whichincreasedtoanaveragecostofroughly$242.30byApril2014beforeincreasingtoan averagecostofroughly$258.6byDecember2014. CSIROTelehealthTrialFinalReportMay2016 Page136of187 FinalLinearMixedEffectsModelsforPBS AsbeforeinourBACIdesignwewishedtoalsoestimatethetemporaltrendandtheseasonalinfluenceon thePBSscores.Wefittedthemodelsusingthelmerfunctioninthelme4Package(LinearMixed-Effects Modelsusing'Eigen'andS4(Bates,Maechler,Bolker,Walker,Christensen,Singmann,Dai,Grothendieck,2015)[ctb]in R.(seehttps://cran.r-project.org/web/packages/lme4/lme4.pdf) Thesemodelsattemptedtomodelrandomeffectsaswellasbeforeandaftereffectsforsitespecific behaviouraswellasseasonalvariationswhichweremodelledassineandcosinefunctionswithfixed periodsandvariablegains. TheresultantfittedmodelforthesqrtofPBScostsisasfollows: Linear mixed model fit by REML ['lmerMod'] Formula: sqrt(1 + PBS.mcost) ~ Sex + Before.After * TC * time + Before.After * TC * Site + period.From + (cos(2 * pi * time/365.25) + sin(2 * pi * time/365.25)) + (1 | OCID) + (1 | period.From) Data: PBS REML criterion at convergence: 119725 Scaled residuals: Min 1Q Median -3.4905 -0.5733 -0.0434 3Q Max 0.4820 12.1889 Random effects: Groups Name Variance Std.Dev. period.From (Intercept) 2.159 1.469 OCID (Intercept) 15.267 3.907 Residual 43.491 6.595 Number of obs: 17950, groups: period.From, 1554; OCID, 99 Fixed effects: (Intercept) SexM Before.Afterbefore TCC time SiteTAS SiteVIC SiteQLD SiteARV cos(2 * pi * time/365.25) sin(2 * pi * time/365.25) Before.Afterbefore:TCC Before.Afterbefore:time TCC:time Before.Afterbefore:SiteTAS Before.Afterbefore:SiteVIC Before.Afterbefore:SiteQLD Before.Afterbefore:SiteARV TCC:SiteTAS TCC:SiteVIC TCC:SiteQLD TCC:SiteARV Before.Afterbefore:TCC:time Before.Afterbefore:TCC:SiteTAS Before.Afterbefore:TCC:SiteVIC Before.Afterbefore:TCC:SiteQLD Before.Afterbefore:TCC:SiteARV Estimate Std. Error t value 1.543e+01 3.374e+00 4.573 -1.933e+00 2.536e-01 -7.623 -1.837e+00 3.209e+00 -0.572 1.153e+01 3.543e+00 3.254 -4.843e-04 1.846e-03 -0.262 3.124e+00 1.560e+00 2.003 2.646e+00 1.578e+00 1.677 9.799e-01 1.600e+00 0.612 8.768e-01 1.797e+00 0.488 1.488e-01 9.187e-02 1.620 -5.023e-01 9.431e-02 -5.326 -1.219e+01 3.561e+00 -3.424 2.456e-03 1.868e-03 1.315 -5.360e-03 2.034e-03 -2.635 -1.651e+00 8.740e-01 -1.889 -2.050e+00 8.910e-01 -2.301 -8.087e-01 9.139e-01 -0.885 -8.068e-01 1.049e+00 -0.769 -1.923e+00 9.116e-01 -2.109 -1.362e+00 9.410e-01 -1.448 -4.194e+00 9.865e-01 -4.251 -3.706e+00 1.141e+00 -3.249 6.038e-03 2.054e-03 2.940 3.006e+00 9.904e-01 3.035 2.624e+00 1.016e+00 2.583 2.314e+00 1.059e+00 2.186 1.718e+00 1.210e+00 1.420 CSIROTelehealthTrialFinalReportMay2016 Page137of187 Thesignificantinterpretationofthismodelisasfollows: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. MalesPBScostsaresignificantlylowerformalesrelativetofemales(themostsignificantvariable) ThecontrolpatientshavesignificantlyhigherPBScostsaftercorrectingforallotherfactors. TasmanianandVictorianpatientshavesignificantlyhigherPBScoststhanACTpatients Therearesignificantseasonalinfluencesonpharmaceuticalcosts(thisishighlysignificant) Thereisasignificantinteractionbetweenthebefore-afterindicatorvariableandthetest-control indicatorvariablethisindicatesthatthebeforecontrolpatientshaveasignificantlylowerPBScost thanothercombinations–thisprovidessomeevidencethattheinterventionmayhaveworkedbut mustbecontrastedwith8below. Thereisasignificantinteractionbetweentimeandcontrolpatientswhichmeansthattherateof increaseincostsissignificantlylowerforthecontrolpatientscomparedtothetestpatients. Thebefore-afterdifferencesaresignificantlygreaterinTasmania&Victoriathaninotherstates. ThecontrolpatientPBScostsinstatesTasmania,QueenslandandARVdiffersignificantlytothose onACTpatients. Thebeforeinterventioncontrolpatientshaveahighertrendovertime–thissuggeststhatthe interventionalbeitsignificantiscomplicated–onitsownthissuggeststhattheinterventionhas reducedthecostsforcontrolsaftertheintervention,butthisneedstobebalancedwiththe interpretationgiveninnumber4. Thebeforeandaftercontrolpatientinteractioninfluencesdiffersignificantlyfromstatetostate, andthissuggeststhattheinfluenceoftheinterventionissignificantdifferenceforTasmania, VictoriaandQueenslandthanACT(theimpactisloweratthesesitesrelativetoNSW). CSIROTelehealthTrialFinalReportMay2016 Page138of187 TASMANIA Figure47PredictedPBScostsforTasmanianpatients Figure48TimecourseofMBScostsforTASpatientswithstartmonthsynchronised ForTASpatientsPBScostsforbothTestandControlpatientsweresimilaranddidnotchangesubstantially aftertheintervention(Figure47,Figure48). CSIROTelehealthTrialFinalReportMay2016 Page139of187 VICTORIA Figure49PredictedPBScostsforVICpatients Figure50TimecourseofMBScostsforVICpatientswithstartmonthsynchronised Theseplots(Figure49,Figure50)indicatethattherewasnoevidenceofabenefitfromtheinterventionin VIC. CSIROTelehealthTrialFinalReportMay2016 Page140of187 QUEENSLAND Figure51PBSPredictedcostsforpatientsinQLD Figure52TimecourseofMBScostsforQLDpatientswithstartmonthsynchronised TherewasnosignificanteffectoftheinterventiononPBScostsinQLDasseeninFigure51andFigure52. CSIROTelehealthTrialFinalReportMay2016 Page141of187 AUSTRALIANCAPITALTERRITORY Figure53PBSPredictedcostsforpatientsinACT Figure54TimecourseofMBScostsforACTpatientswithstartmonthsynchronised TheACTpatientsdifferedfortheControlpatientsfromTAS,VICandQLDwherethePBScostskeptonrising aswewouldhaveanticipatedpriortothestudy,andtheTestpatientscostdroppedoffafterthestartof theintervention(Figure53,Figure54).TherewasevidenceoftheTestpatientsbenefittingfromthe interventionrelativetotheircontrolsinACT. CSIROTelehealthTrialFinalReportMay2016 Page142of187 NEWSOUTHWALES Figure55PredictedPBScostsforNSWpatients Figure56TimecourseofMBScostsforNSWpatientswithstartmonthsynchronised ThesepatientsweresimilartotheTASpatientswithachangeinPBScosttrendfortheControlsafterthe intervention,buttheTestpatientshowedadropoffinPBScostsaftertheinterventionperiod(Figure55, Figure56). TheconclusionwithrespecttotheeffectofthetelemonitoringinterventiononPBScostsfromthefivesites differ.InTAS,ACTandNSWthereweresignsofpotentialbenefitbutthemessagewasfarfromclear,while inVICandQLDtherewasnoobviousbenefit–infacttheControlsseemedtohavereducedtheircosts moreaftertheinterventionperiod. CSIROTelehealthTrialFinalReportMay2016 Page143of187 8.4 Method3:Monitoringcumulativesumofdifferencesincostsovertime Inthisanalysiswetooktheaverage30daycostsfortheControlpatientswhenthereweretwomatches andthenweexaminedthedifferences(Test-Controls)inthe30daycostsforeachTestpapientandtheir controls.IftherewasonlyonematchedControlpatientforaTestpatientwetookthedifferencesbetween thematchedTestandControlpatients’30daycosts.Thesedifferencesshouldberandomlydistributed aroundzeroiftherewasnochangeinthecostdistributionbetweenthematchedTestandControlpatients’ respectivecosts.Thesedifferencesin30dayaveragesremovethetemporaltrendsoftimeandseasonal influencesaswellasanylocalinfluencesintime–thisisthemajoradvantageofthisapproachbesidesits simplicity. ThefirstplotlooksattheaccumaltivesumofthedifferencesbetweenthematchedcostsfortheTest patietsandtheaveagescostsoftheControlpatients.Thisplotcanbeinterpretedintermsoftherateof changeovertime(slopeoftheCUSUM): 1. IftheCUSUMtracksdownwardsthenthetestpatienthaslowercoststhanthecontrols.Ifittracks upwardsthenthereverseistrue. 2. IftheCUSUMchangesitstrendovertime(rateofchange)andthiscorrespondstowhenthe interventionstartedthenthisindicatesachangethatislikelytobearesultoftheintervention.Ifit reducesslopeaftertheinterventionthenthissuggeststhatthetestpatientshavereducedtheir costscomparedtowhatwasexpected.Iftheslopeincreasesaftertheinterventionthenthetest patientscosthaveincreasedandtheinterventionhashadtheoppositieeffecttoexpected. 3. Iftheslopeisincreasingovertimebeforetheinterventiondatethenthetestpatientsappeartobe deterioratingmorethantheircontrolswithtimeasmeasuredbytheircosts. CumulativesumofdifferencesininGPCostsovertime (a)Bluebeforecirclesplottedlast. b)Bluebeforecirclesplottedfirst Figure57CUSUMdifferencesinmatchedtestandcontrolpatients’GPcosts Figure57indicatesthetrendinthedifferencesbetweenthematchTestandControlsGPcosts.Fromthe startofthestudyitisclearthatthecostsfortheTestpatientsincreasedmorebeforetheintervention. Notethatthebluecirclesindicatethedifferencesafterinterventionandtheblackcirclesindicatethose differencesthatoccuredbeforetheintervention.WeplottedthebluecirclesinFigure57aandtheblack circlesinFigure57b,becausesomeTestpatientsstartedtheirinterventioninthesame30dayperiod. ThereisalsoevidencethattheCUSUMreduceditsslopeaftersomepatientsstartedtheinterventionwhich providessomeevidencethattheinterventionwassuccessfulinreducingGPcosts.Itisalsoclearthatas CSIROTelehealthTrialFinalReportMay2016 Page144of187 moreandmoreTestpatientsstarttheinterventiontheslopeofthelinekeepsreducingitsgradienthence providingreasonableevidencethattheinterventionreducedGPcostsmathematically. Figure57aisthesameasFigure57bbutitillustratesthosetestpatientsthatstartedtheinterventionlater thanmostothers,whileFigure57billustratesthosethatstartedearly.Theblueverticallineindicatesthe medianstartingdateoftheintervention.InFigure57aandFigure57bwedon’tplotthefull‘before’period toavoidthislongerperioddominatingthegraph. Figure58TheEWMAofthematcheddifferencesin(average)30daycostsbetweenthetestandcontrolpatients Figure58istheexponentiallyweightedmovingaverages(EWMA)ofthematchdifferencesinthenonoverlapping30dayperiodtotalGPcosts.Theseareinterpretedasfollows: 1. Ifthereisnodifferenceinthesecoststhenthesedifferencesshouldremainclosetozeroby followingarandomwalkaroundzero. 2. Ifthesedifferencestrendawayfromzerothenthisestimatesthelocaldifferences(intime) betweenthecostsofthetestsandcontrols. 3. Thetrendsinthesecostsindicatethedirectionthesecostsareheadinginovertime,e.g.,positive differencesindicatethatthelocalcostsfortestpatientsarehigherthanforcontrolpatients. InFigure58thelocalaveragecostsnearlyalwayswasgreaterfortheTestpatientsthantheControlsbefore theintervention.Figure58indicatesthattheTestpatientsGPcoststrendeduptoonaverage$15higher fortheTestpatientsper30daybythebeginningof2013.AftersomeTestpatientshadstartedthe interventionthisstablisedataboutanincreaseof$10per30day,butafternearlyallTestpatientshad movedtoontotheinterventionthiswastrendingtoaboutTestpatientsonlypayingonaverage$5per30 dayindicatingapotentialgainonaverageofabout$10per30dayperiod.Thereissomeevidencethatif thetrialhadlastedalittlelongerandthistrendcontinuedthentherewouldbenodifferenceinGPcostsor evenbettertheTestpatients’GPcostswouldbelowerthantheControlpatients’GPcosts. CSIROTelehealthTrialFinalReportMay2016 Page145of187 Cumulativesumofdifferencesinspecialistcostsovertime (a)beforecirclesplottedlast (b)beforecirclesplottedfirst Figure59CUSUMdifferencesinmatchedtestandcontrolpatients’specialistcosts Thefactthatthecumulativesumofthematcheddifferencesin(average)specialistcostsbeforethe interventionincreasedatarapidratefromthestartinFigure59indicatesthatthespecialistcostswere higherfortheTestpatientsthanfortheControlpatients.Thereductionintheslopeaftertheintervention startedindicatesthatthisgapbetweentheTestandControlcostsclosedalittleaftertheintervention. WhenthecumulativesumstartstrendingdownwardsthentheTestpatientsnowhavelowercoststhanthe Controlpatients.SoFigure59suggeststhattherewasacontinuedimprovementintheTestpatients’ specialistcoststothelevelattheendofthestudywheretheTestpatientshadlowerspecialistcosts(after startingwithhighercosts).Thisdoessuggestthatwestoppedthestudytoosoontorealisethefullbenefit oftheintervention(butthisisahunchratherthanafact–wecan’texplolatewhatwouldhavehappened beyondtheenddateofthetrial). Figure60TheEWMAofthematcheddifferencesin(average)30dayspecialistcostsbetweenthetestand controlpatients InFigure60itisclearthatoncenearlyallTestpatientshavestartedtheinterventionthenthetrendinthe costdifferencesstartedtrendingdownwardswhichclearlysuggeststheinterventionworkedinreducing Testpatients’specialistcostsrelativetotheirControlpatients. ThefiguresaboveplotthetimesseriestrendintheEWMAsmoothedspecialistcosts.Thesesmoothed differenceswereonaveragemostlygreaterthanzerobeforetheinterventionindicatingthattheTest patientgenerallyhadhigher30daycoststhantheControlpatients.Thesevaluestrendedupwardswhen theseTestpatientcostsstartedincreasingrelativetotheControlpatientsandtrendeddownwardswhen theystarteddecreasing.NotethattowardstheendofthestudytheTestpatients’specialistcosts CSIROTelehealthTrialFinalReportMay2016 Page146of187 appearedtobeloweronaveragethantheControlpatients.Thissuggeststhattheinterventionmayhave hadalong-termbenefitforthepatientsinreducingspecialistcosts. Cumulativesumofdifferencesinlaboratorycostsovertime a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure61CUSUMdifferencesinmatchedtestandcontrolpatients’laboratorycosts Figure61a.demonstratesthatthelaboratorycostsforTestpatientsappearedtoincreasesoonafterthe intervention,butthesestartreducingtowardstheendofthestudy.Unfortunatelywecan’ttellwhether thislatereductioninlaboratorycostsweregoingtopersistbeyondthestudyperiod.Thisevidence suggeststhatalthoughTestpatientlaboratorycostsappearedtoincreaseattheinitialstagesofthestudy, bytheendofthestudythistrendwasreversed. Figure61b.suggeststhatoncetheTestpatientswerealmostallenteredtheafterperiod(theintervention hasstarted)thenthe(cumulativesumofthedifferences)CUSUMtrendchangedtoalowerslopeindicating thattherelativecostsstartedtoreduce,withachangeindirectionlaterinthestudyperiodindicatingthat bytheendofthestudyperiodthelaboratorycostsforTestpatientswereonaveragelowerthanthe Controlpatients. Figure62ThetimeseriestrendinEWMAsmoothedmatcheddifferencesin(average)30daylaboratorycosts betweenthetestandcontrolpatients Figure62examinesthetimeseriestrendinEWMAsmoothedmatcheddifferencesinlaboratorycosts.This indicatesthatbeforetheinterventiontheTestpatientsgenerallyhadhigherlaboratorycoststhanthe Controlpatients.Thereisevidencethataftertheinterventionthetestpatients’laboratorycoststrended highermorethantheControlpatientsbuttowardstheendofthestudyperiodthistrendwasdownwards inthedirectionoflowerdifferencesinlaboratorycosts. CSIROTelehealthTrialFinalReportMay2016 Page147of187 Cumulativesumofdifferencesofprocedurecosts (a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure63CUSUMdifferencesinmatchedtestandcontrolpatients’procedurecosts Figure63presentsthetimeseriesplotoftheCUSUMforthedifferencesinprocedurecosts.Thereisstrong evidencefromFigure63a.thatbeforetheinterventiontheTestpatients’procedurecostswereincreasing atarapidraterelativetotheControlpatients.ThisisevidentbytheincreasingtrendintheCUSUMfor mostof2013.Thistrendstartsturningaroundatthestartoftheintervention.BythetimenearlyallTest patientshavestartedtheinterventionthetrendintheCUSUMisdownwardsindicatingthattheTest patientprocedurecostsarenowlowerthantheControlpatients’procedurecosts. Figure63b.makestheevidenceofthechangepointsindifferencesinprocedurecostsmoreevidentand clearlyprovidingmoreevidenceonthereasonsforchangeinthedifferencesinprocedurecosts. Figure64TheEWMAofthematcheddifferencesin(average)30dayprocedurecostsbetweenthetestand controlpatients Figure64presentsthetimeseriestrendfortheEWMAsmoothers30daydifferencesintheprocedure costs.BeforetheinterventiontheseEWMAvaluesarenearlyalwaysabovezeroindicatingthattheTest patientprocedurecostswerenearlyalwayshigherfortheTestpatient.However,aftertheintervention thereisevidencethattheseEWMAdifferencestrendsbelowzeronowsuggestingthatafterthe interventiontheTestpatientprocedurecostswerelowerthattheirmatchedControlpatient.Thisturn aroundappearstobeduetotheintervention. CSIROTelehealthTrialFinalReportMay2016 Page148of187 CumulativesumofdifferencesofnumberofGPvisits ThediscussionforthenumberofGPvisits,specialistconsultations,laboratorytestsandprocedureswillbe commentedoninlessdetailbecausethesehavealreadybeenappropriatelyanalysedusingtheBACI design.Howeverthisanalysisgivesgreaterinsightintothechangingtrendswhichareassumedtobelinear intheBACIanalysis. (a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure65CUSUMdifferencesinmatchedtestandcontrolpatients’numberofGPvisits Figure65presentstheCUSUMofthematcheddifferencesinthenumberofGPvisits.Thisindicatesthat theCUSUMstartswithaslightlyincreasingtrendinlate2012.TheCUSUMincreasednoticeablyinslopein early2013indicatinganincreaseinthenumberofGPvisitsfortheTestpatientsrelativetotheControl patients.Howeveraftertheinterventionthereisevidenceofthisslopefirstreducingandthentowardsthe endstartingtoreverseintrend.Ifthistrendpersistedinadownwardtrendaftertheendofthestudy periodthenitisclearthatthenumberofGPvisitswouldhavereducedsignificantlyfortheTestpatients relativetotheirControls. Figure65b.illustratesthechangepointsclearlycorrespondtothestartoftheinterventionindicatingthatit hasthedesiredimpactonthenumberofGPvisits. Figure66presentsthetimeseriesplotoftheEWMAsmoothedmatcheddifferencesinGPnumberofvisits in30dayperiods.ThisindicatesanincreaseintheTestpatientnumberofvisitsbeforetheintervention date,butachangeinthistrendaftertheinterventionstarted.Itisclearthatthedifferencesweretrending towardszeroaftertheinterventionwhichprovidesreasonableevidencethattheinterventionmayhave realizedasignificantresultforthenumberofGPvisitsifthetrialwasrunforalongerduration. Figure66TheEWMAofthematcheddifferencesin(average)30daynumberofGPvisitsbetweenthetestand controlpatients CSIROTelehealthTrialFinalReportMay2016 Page149of187 Cumulativesumofdifferencesofnumberofspecialistconsultations (a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure67CUSUMdifferencesinmatchedtestandcontrolpatients’specialistconsultations Figure67providesthetimeseriesplotsfortheCUSUMmatcheddifferencesinthenumberofspecialist consultations.TheseplotsindicatethatthenumberofspecialistconsultationsfortheTestpatients increasedrelativetotheControlbeforetheintervention.Aftertheinterventionthereisevidencethatafter theinterventionstartedthenumberofspecialistvisitsfortheTestpatientstartedtoreducerelativetothe Controlpatients.Theimpactseemedtobedelayedoratleasttheimpactseemedtobelongertermrather thanimmediate. Figure68TheEWMAofthematcheddifferencesin(average)30dayspecialistconsultationsbetweenthetest andcontrolpatients ThetimeseriestrendintheEWMAsmoothedmatcheddifferencesinthenumberofspecialistvisitsin Figure68indicatesthatthenumberofspecialistvisitspriortotheinterventionwasonaverageabout0.2 moreperTestpatientthanControlpatients,butaftertheinterventionthisappearedtotrenddowntoless thanzero(i.e.,Controlpatientshadmore30dayvisitstothespecialistthanTestpatients). CSIROTelehealthTrialFinalReportMay2016 Page150of187 Cumulativesumofdifferencesofnumberoflaboratorytests (a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure69CUSUMdifferencesinmatchedtestandcontrolpatients’numberoflaboratorytests Figure69presentsthetimeseriesplotsoftheCUSUMmatcheddifferenceinthenumberoflaboratory tests.ThisprovidesevidencethatthenumberoflaboratorytestsincreaseddramaticallyintheTestpatients relativetheControlpatientsuntilneartheendofthestudywherethistrendisreversed.Howeverthe studyappearedtonotrunlongenoughtofullyrealisethisrelativebenefit. Figure70TheEWMAofthematcheddifferencesin(average)30daynumberoflaboratorytestsbetweenthe testandcontrolpatients Figure70providessimilarevidenceasFigure69. CSIROTelehealthTrialFinalReportMay2016 Page151of187 Cumulativesumofdifferencesofnumberofprocedures (a)aftercirclesplottedlast (b)aftercirclesplottedfirst Figure71CUSUMdifferencesinmatchedtestandcontrolpatients’numberofprocedures ThetimeseriestrendsinFigure71indicateanincreaseintheCUSUMovertime,buttherateofthis increaselowerswiththestartoftheintervention.Thisindicatesthatthehighernumberofproceduresin TestpatientscomparedtoControlpatientspersistedforthedurationofthestudy,butthedifference betweenthesetwogroupswasreducedbytheintervention,suggestingasignificantimpactofthe intervention. Figure72TheEWMAofthematcheddifferencesin(average)30daynumberofproceduresbetweenthetestand controlpatients Figure72Figure72confirmstheinformationfoundinFigure71. CSIROTelehealthTrialFinalReportMay2016 Page152of187 8.5 DevelopmentofaWebRTCVideoConferencingService VideoconferencingforpatientsinthisTelehealthTrialwasmadeavailablethroughtheTelemedcare telehealthdevicein-buildvideoconferencingcapabilityasdiscussedbelow.However,tofulfilthe requirementofdeliveringvideoconferencingathighdefinitionat720p(1280x720pixels)25fps,aselection processwascarriedouttodetermineanappropriatetabletsuitableforthispurposeconsideringuser aspectsappropriateforanelderlypatient.TheSamsungGalaxyNote8inchandNote10inchtableswere selectedbothwithfrontcamerascapableofcapturingvideoatgreaterthan720p(1280x720pixels)for furtherassessment. Initialtestingdemonstratedthatneitherthe8inchnorthe10inchtabletcansend720pat25fpsvideo usingthefrontcamera,butcanreceiveanddisplay720pvideoat30fps.Thisdownscalingofupstream videoisanAndroidoperatingsystem/Chromefeaturewhichcan’tbecontrolled.Theseconclusionswere confirmedbytwoexternalorganisationsAttendAnywhereandMedtechGlobal,bothofwhomare experiencedinprovidingvideoconferencingservices. Followingtheresultofthisinitialtesting,additionalresearchwasundertakentofindanappropriatevideo conferencingplatformtodeliverthisserviceviathetablet.Afterreviewingseveralavailableplatforms, WebRCT(WebReal-TimeCommunication)wasselected,togetherwiththenew2014versionofthe SamsungGalaxyNote10inchtablet.UsingWebRCTastandards-basedvideoconferencingsystemwas developedandtestedfortheTelehealthTrial. TelemedcareVideoConferencing VideoconferencingwithapatientusingTelemedcaretelehealthdevicewasquitesimpleandcouldbe initiatedbytheCCCviatheirremoteclinicalmonitoringsoftware.CCCswhohadthisfeatureenabledwere requiredtoactivatethevideoconferencebuttononthescreenafterselectingthepatient’sname. Belowisabriefdescriptionofoperationsofthisvideoconferencingfeature: TheCCCisrequiredtoselectapatientfromtheirlisttowhomtheywanttovideoconferenceasshownin Figure73below. Figure73SelectingpatientsfromtheTMCClinicianinterface A‘videochat’buttonisvisiblenearthetopofthepage;ifthe'VideoChat'buttonisgreyedout,the selectedpatientisnotonlineandtheCCCcannotinitiatethevideochat.Thismaybeduetothe monitoringunitnotbeingturnedon,orthepatienthavingdisconnectedthemonitoringunitfroman internetconnection.Ifthepatientisconnectedtotheinternet,the'VideoChat'buttonontheclinician’s webpagewillbecomeenabled.TheCCCcantheninitiatethevideochatbyselectingthevideochatbutton. Oncevideochathasbeenselected,amessagewillindicatethatthevideoconferenceisstartingup,and waitfortheclienttoaccepttheconferenceontheirremoteunit. CSIROTelehealthTrialFinalReportMay2016 Page153of187 Ifthepatientdoesnotwanttoaccepttheconference,he/shecanrejectthis,andtheconferenceclinician willreceivethefollowingmessage: Ifthepatientacceptstheconferenceinvitation,animageoftheuserwhoinitiatedtheconferencewill appearontheirhealthmonitor.TheCCCwillalsobeabletoviewthepersontheyhavecalled,aswellas seeingasmallimageofwhatisbeingsent. Thevolumeofthevideochatcanbeadjustedtolow,mediumorhigh,aswellasusingtheusualwindows volumecontrol. Whentheconferenceisfinishedtheusercanpressthedisconnectbutton. Ifthepatientfinishestheconferencefirstbydisconnecting,thefollowingmessageisdisplayed. NOTE:VideoconferencingcanonlybeinitiatedfromtheCCC(Carer/Clinician)onthewebinterface.The patientcannotinitiatevideocallstotheirclinician. Thisvideoconferencingservicewasavailableforusebutwasnotwidelyusedbecauseoffrequent dropouts,particularlywhentheClinicianwasbehindahospitalfirewallorthepatientwasnotconnectedto theNBN. CSIROTelehealthTrialFinalReportMay2016 Page154of187 WebRTCPrototypeImplementation Inthissection,aprototypeimplementationisusedtoillustratehowsomeofthedesignideasdescribed earlierhavebeenrealizedinthevideoconferencingsystemusingWebRTC. EnvironmentSetup: ThoughtheWebRTCisstillatadraftstage,therearenumberofopensourceprojectsandcommercial platformsavailablewiththepromisetoassistinthefastandeffectivedevelopmentofWebRTCbasedvideo conferencingapplicationswiththeminimumeffortsfromthedevelopers.Amongthose,EasyRTC,afullstackopensourceWebRTCtoolkitthatsupportsthebuildingofsecureWebRTCapplicationswasselected. EasyRTCisabundleofwebapplications,codesnippets,clientlibrariesandservercomponentswrittenand documentedtoworkoutofthebox.EasyRTCAPIsandJavaScriptsareusedtoaccessthefunctionsof WebRTCenginesalreadyimplementedinmanybrowsers.AstheChromebrowsercomespre-installedin theSamsungGalaxyNotes,thiswasused.Node.js,whichisaJavaScriptbasedruntimeplatform,wasused asawebservertodevelopourwebapplications. AcquiringAudioandVideoStreams: Inpractice,thecomplexityofrepresentingthevideoandaudiostreamsandspecifyingtheconstraintsof themediastreamsareallhiddenfromthedevelopers.Thefollowingcodesnippetsillustratehoweasyitis todefinealocalstream(i.e.,gettingavideoandaudiostreamfromthelocalmachine). easyrtc.initMediaSource( function(){ varselfVideo=document.getElementById("me"); easyrtc.setVideoObjectSrc(selfVideo,easyrtc.getLocalStream()); easyrtc.connect("VCtest",connectSuccess,connectFailure); }, connectFailure ); Itisimportanttonotethecalltoeasyrtc.getLocalStreamandeasyrtc.setVideoObjectSrc.Theformergetsa videoandanaudiostreamfromthelocalcameraandmicrophone,oncethecalltoeasyrtc.initMediaSource succeeds.Thelattertiesavideotagtoamediastreamobject.Invokingthismethodwillcausetheuser’s browsertoaskforpermissiontoaccesstherequestedlocalcameraandmicrophoneasseeninFigure74. Oncethepermissionbuttonisclicked,theusersseetheirownimagesonthescreen. Figure74Browserasksforapermissiontoaccessthelocalcameraandmicrophone CSIROTelehealthTrialFinalReportMay2016 Page155of187 Obtainingaremotepeer’smediastreamisalsostraightforwardbyusingacallbackmethod.Thecallback methodtiesthevideotagtotheincomingstream.Whentheremotepeerhangsup,thecallbackclearsthe videotag. easyrtc.setStreamAcceptor( function(callerEasyrtcid,stream){ varvideo=document.getElementById('caller'); easyrtc.setVideoObjectSrc(video,stream); }); easyrtc.setOnStreamClosed( function(callerEasyrtcid){ easyrtc.setVideoObjectSrc(document.getElementById('caller'),""); }); Inaddition,EasyRTCprovidesanumberoffunctionsfordeveloperstosetupmediaconstrains.For example,callingeasyrtc.setVideoBandwidth()allowstosetthebandwidthusedtosendandreceive SignallingandPeerConnection Asignallingprocessassiststhefindingofpeersandestablishingcommunicationamongpeersby exchangingdatathroughdedicatedchannels.Thededicatedchannelallowstheprivacyandsecurityofthe datafromtheinterferenceofconcurrentlyrunningprocesses.Theimplementationofsignallingprocesscan varydependingontherequirementsofeachapplicationandtheenvironmenttheapplicationrunson.For example,ifanapplicationonlyrequirescommunicationamongpeerswithinthesamenetwork,itis relativelystraightforwardtoobtainpublicIPaddressesofthepeersandmaketheconnections.However,a signallingprocessbecomescomplexifpeers’publicIPaddressesandportinformationarehiddenaway frompeersastheyarelocatedbehindtheirownprivatenetwork.Asaresult,neitherpeerisdirectly reachablebyeachother.Toinitiateasession,onemustfirstgatherthepossibleIPaddressesandport candidatesforeachpeer,traversetheNATs,andthenruntheconnectivitycheckstofindtheonesthat work. ThePeerConnectionAPIintheWebRTCisresponsibleformanagingthefulllifecycleofeachpeer-to-peer connectionbyencapsulatingalltheconnectionsetup,management,andstatewithinasingleinterface. However,beforetheapplicationdeveloperdivesintothedetailsofeachconfigurationoptionoftheAPI, oneneedstounderstandtheinteractionsamongpeersbeforechoosingarightsignallingprocess.Figure75 illustratesoursignallingrequirementsandinteractionsrequiredbetweenpeers. CSIROTelehealthTrialFinalReportMay2016 Page156of187 browser1 Signal Server Browser2 (at care coordinator) (EasyRTC/No de.js) (at patient side) Obtain and display local media stream(1) Obtain and display local media stream(1) Session Request (2) Session Established (3) Create and Send a Call Offer using SDP (4) Generate & Send a Call Answer using SDP (5) Create and Send a ICE CandidateA (6) Check ICE CandidateB(8 ) Create and Send a ICE CandidateB (7) Exchange Media Streams (9) Obtain and display remote media stream(10) Obtain and display remote media stream(10) Figure75SignallingandInteractions 1. Whenacarecoordinatorclicksa“connect”button,thecarecoordinator’sbrowserobtainsand displaysthelocalmediastream. 2. (Wethenneedassistancefromasignalservertocreateasecurechannelbetweenthecare coordinator’sbrowser(browser1)andthepatient’sbrowser(browser2)whichisrequestinga particularvideoconferencingsession. 3. Asessionisestablished. 4. Thebrowser1usesSessionDescriptionProtocol(SDP)todescribethesessionprofilewhich containsinformationsuchastypesofmediatobeexchanged,codecsandtheirsettings,and bandwidthinformation.TheSDPisusedtomakeanoffertothebrowser2.Atthisstage,actual mediaitselfisnotattachedtotheoffer. 5. Uponreceivingtheoffer,thebrowser2createsananswerthatitiswillingtoconnecttothe browser1andalsosendsitscorrespondingsessionprofileusingSDP.Nowthebrowser1knows thatthebrowser2isreadytorunapeertopeercommunication. 6. Aftergettingananswerfromthebrowser2,browser1createsanInteractiveConnectivity Establishment(ICE)agent(ICEA).TheICEagentgatherslocalIPaddressandporttupleandqueries anexternalSTUNservertoretrievethepublicIPandporttupleofthepeer. 7. UponreceivingtheICEA,thebrowser2performsthesameoperationasbrowser1tocreateand sendICEagent(ICEB). 8. Browser2checksthatthepublicaddressreceivedinICEBmatcheswiththeinformationreceived earlier(i.e.,thebrowser2sendsthisinformationwhenthepatientclicksvideoconference reservationrequest).Atthispoint,ifthebrowser1andbrowser2cannotestablishaconnection directlyasP2Pfashion,theTURNserverisusedasaproxytorelaytraffic. 9. Browser1sendsthemediastreamtobrowser2.Likewise,browser2sendsitslocalmediastreams tobrowser1afterobtainingthepublicIPaddressesandportnumbertuplesfromtheICEA receivedearlier. CSIROTelehealthTrialFinalReportMay2016 Page157of187 Atthisstage,bothbrowsersstartdisplayingmediacontentsandthevideoconferencingisinoperation. TheabovementionedinteractionsclearlydemonstrateaneedforSTUN/TURNserversandasignalserver thatcanhandleasmallnumberofparticipants.EasyRTCsupportsasignallingserverthatfitsour requirements.Thoughtheinteractionsinourcaselooklengthyandintricate,thecomplexityisactuallyall wrappedtogetherbythesignallingprocess.AllthatwasrequiredwastodefineaSTUN/TURNserverandto addafewlinesofJavaScriptcode. TheenabledSTUN/TURNserverenforcestheEasyRTCtogothroughtheexternalSTUN/TURNservertoget publicIPaddressesandportsofthepeersthatinteractinourapplication.Ifthissetupisomitted,the EasyRTCwillonlyattemptthedirectpeertopeerconnectionwithinthesamenetworkusingthelocalIP addresses.ThefollowingcodeexcerptillustrateshowtospecifySTUN/TURNserverinthecodeanddirect theEasyRTCtousetheconfiguration. varonGetIceConfig=function(connectionObj,callback){ varmyIceServers=[ {url:'stun:stun.l.google.com:19302'}, {url:'stun:stun1.l.google.com:19302'}, {url:'stun:stun2.l.google.com:19302'}, {url:'stun:stun3.l.google.com:19302'}, {url:'turn:[email protected]:3478?transport=tcp', credential:'test', username:'test'} ]; } easyrtc.on("getIceConfig",onGetIceConfig); ThefollowingJavaScriptisaddedtomakepeertopeerconnections.WiththeSTUN/TURNserverenabled, EasyRTCmakesanumberofdecisionsonourbehalf.Inthebackground,itinitializesthePeerConnection withapublicSTUN/TURNserverforNATtraversalbycreatingICEagents,requestsaudioandvideostreams withgetUserMedia,andinitiatesaWebSocketconnectiontoestablishasessionwithitsownEasyRTC signalingserverandpassesthemediastreamsbetweenthepeers. functionperformCall(easyrtcid){ easyrtc.call(easyrtcid, function(easyrtcid){ console.log("completedcallto"+me);}, function(errorMessage){ console.log("err:"+errorMessage);}, function(accepted,peers){ console.log( (accepted?"accepted":"rejected")+"by"+peers);});} CSIROTelehealthTrialFinalReportMay2016 Page158of187 ChatRooms: RoomsareacompartmentalizingfeatureofEasyRTCthatareusedtocreatechatservices.Thechatservice allowsacarecoordinatorandapatienttoexchangetextmessagesinadditiontotheonlinemeetingthey areconducting.Tocreateachatservice,bothclientandservercodesneedtobeimplemented.Onthe clientside,firsttheclientconnectstoasocket.ioservertogetachatchannel.Onceconnectionis established,theclientsendsachatmessage. //connectiontosocket.ioserver varchat=io.connect(window.location.protocol+'//'+window.location.host+'/appointments); //sendingachatmessage functionsendChatMessage(val){ //sendingmessagetotheserver chat.emit("chatmessage",{text:val}); } Oncetheserverreceivesthe‘chatmessage’fromtheclient,itwillfirethe‘chatmessage’inthecurrent roomtoeveryjoinedparticipant. varchat=socketServer.of('/appointments').on('connection',function(socket){ socket.on('subscribe',function(data){ socket.join(data.room); roomName=data.room; }); socket.on('chatmessage',function(data){ chat.in(roomName).emit('chatmessage', {'text':txt,'from':userName,'userId':userId}); }); }); Uponreceivingthe‘chatmessage’byclientsfromtheserver,theclientparsestheincomingdataand displaysthetextinthechatlog. functioninitChatRoom(appointmentID) { //jointhechatroom chat.emit("subscribe",{'room':appointmentID}); //receivethechatmessagesentbythepeer(sentviatheserver) chat.on("chatmessage",function(data){ chatlog.append(data.from+":"+data.text+"\n"); }); } CSIROTelehealthTrialFinalReportMay2016 Page159of187 LaboratoryTestofWebRTCVideoConferencingSystem Laboratorytestingwasperformedofthedevelopedvideoconferencingsystemtoidentifywhetherthe systemcansupporttwowayHDquality(i.e.,720p25framespersecond)videoconferencingbetween patientandclinicalnursecoordinatorusingSamsungGalaxyNote10”tablet. Inourtestenvironment,thepatientisuppliedwithaSamsung10”tabletwithasimpleWebRTCvideo conferencingapplicationinstalled.ThepatientisconnectedtolocalWifinetworkwithacapacity27MB/s. TheCCCisprovidedwithastandardDelllaptopconnectedto100MB/sLAN. Thebasicstatisticsofthesystemwerecapturedusingachromebrowserprovidedtoolchrome://webrtcinternals.ThecapturedstatisticsareshownintheFigure76below. Figure76Signallingandinteractiondata Theframewidth,framelengthandframerateareshownintheboxedpicturesabove.Itclearlyshowsthat theframewidthandframelengthsatisfytheHDquality(1280x720).However,theframerate,although satisfyingtheHDimagequalityrequirements,fluctuatesduringthevideoconference.Thereareanumber offactorsthatmayinfluencethesefluctuationsuchasCPUperformance,networkcongestion,etc. Identifyingsuchfactorswasoutofthescopeofthetest. ThesendingandreceivingframewidthandheightwerealsocapturedonscreenasshowninFigure77 belowforaSamsungtablet.Thelocalreferstothevideocapturedbythepatientsidetabletcamera,and theremoteindicatesthevideoreceivedbythetabletfromCCC.BothshowthatHDqualityframesare correctlyexchangedinourWebRTCbasedvideoconferencingsystem. CSIROTelehealthTrialFinalReportMay2016 Page160of187 Figure77Demonstrationoftwowayhighdefinition720pvideoconferencing 8.6 ImplementationoftelehealthreportuploadtoPCEHR AnoriginalstatedprojectgoalwastodemonstrateconnectivitytoPCEHRdevelopmentsinGreater WesternSydneywiththesupportoftheNSWDept.ofHealth.However,thisprovedunachievableandin ordertode-risktheprojectandgiventhatMBS&PBSdatawasbeingsupplieddirectlyfromMedicare,the projectteamde-prioritised,slippedandre-scopedPCEHRconnectivityactivitiestolaterintheproject schedule. There-scopedgoalsforPCEHRconnectivitywere; • • Describehowintegrationwasachievedbytheprojectanddemonstratethedeliveryofvitalsigns monitoringreportstothePCEHR’sSoftwareVendorTest(SVT)environment. Describetelehealth/PCEHRintegrationapproachesforproductionenvironments. TheClinicalInformationSystemmentionedatstep3insection4.12.1abovewasimplementedasaweb application.Figure78showstheuserinterfaceofthatwebapplicationwithaselectionofSVTtestpatient records.SometestpatientshaveaPCEHRandallbutonehaveavitalsignsreportavailableforupload. Figure78VitalSignsMonitoringReportPCEHRUploadDemonstration CSIROTelehealthTrialFinalReportMay2016 Page161of187 TheprojectteamdeterminedthemostappropriatePCEHRclinicaldocumenttypecurrentlyavailableto holdvitalsignsmonitoringreportwasEventSummary.InthePCEHRanEventSummaryisusedtocapture keyhealthinformationaboutsignificanthealthcareeventsthatarerelevanttotheongoingcareofan individual. ProjectPCEHRIntegration Figure79belowshowsahighlevelcontextualviewoftherelationshipbetweenvariousproject componentsandthePCEHRSoftwareVendorTest(SVT)environment. 1 2 TeleMedCareServer NBN/TMCenabled patientresidence CSIROTelehealth ProjectServer 3 4 Consumer Portal 5 Provider Portal PCEHRB2B Gateway Patient Clinical CareTeam PCEHRSVT environment Figure79OverviewofPCEHRintegration Thefollowinglabelledinteractionsbetweensystemusersandcomponentsareshown: 1. ThetrialparticipantusestheTMCdeviceintheirhome.Thedevicesendsvitalsignsandotherdata toTMC’sservers. 2. OnaperiodicbasisTMCsendsvitalsignsmonitoringreportstoCSIRO’sprojectserver. 3. CSIROsoftware,actingintheroleofaPCEHRClinicalInformationSystemwithintheSoftware VendorTest(SVT)environment.Thissoftwarepackagesthevitalsignsmonitoringreportintoan EventSummaryXMLdocument,thenuploadstheXMLdocumenttothePCEHRviatheBusiness-tobusiness(B2B)gateway. 4. Studyteammembers,actingaspatients,demonstratehowpatientsviewvitalsignsmonitoring reportsasEventSummaryrecordsusingthePCEHRconsumerportal. 5. Studyteammembers,actingasmembersofthepatient’scareteam,demonstratehowhealthcare providersviewvitalsignsmonitoringreportsasEventSummaryrecordsusingthePCEHRprovider portal. Thisschemawasimplementedasatestenvironmentasdescribedbelow. CSIROTelehealthTrialFinalReportMay2016 Page162of187 ExampleofautomaticallygeneratedtelehealthReportsuitableforuploadingtoPCEHR ThevitalsignsmonitoringreportshownbelowwasdevelopedincollaborationwithTMC.Thisexample consistsofathree-pagePDFdocument. CSIROTelehealthTrialFinalReportMay2016 Page163of187 CSIROTelehealthTrialFinalReportMay2016 Page164of187 ThepatientreportprovidedbyTelemedcarefocusesalmostentirelyonthereportingoflongitudinalvital signsdataandTelemedcareacknowledgesthatasignificantvisualredesignandanupgradingofthe contentisrequiredinorderforthisreporttobeacceptabletoclinicians. Basedonitsexperience,andunderstandingofthePCEHRarchitectureandoperationalenvironments, suggeststhatPCEHRintegrationfortelehealthvendorssuchasTMCisviable.Vendorswillneedtochoose themostappropriatePCEHRsystemrolefromanumberofpossiblealternatives(ClinicalInformation SystemoraContractServiceProvider). AnenhancementtothePCEHRidentifiedbythisstudyandinthePCEHRreview20isthedevelopmentofa newclinicaldocumenttypeforclinicalmeasurementsthatwouldallowclinicalmeasurementstobe inserteddirectlytoElectronicHealthRecordsandGPmanagementsystems.ThePCEHRintegrationwork conductedforthisstudywouldhaveutilisedaclinicalmeasurementsdocumenttypeinpreferencetoEvent Summary,haditbeenavailable,asamoreappropriatemeansofstoringvitalsignsmonitoringdata. 8.7 RiskStratificationSystem–Prototypedevelopment Theprototypepatientriskstratificationreports(alsocalledthepatientwell-beingreports)discussedinthis sectionweresuppliedtoClinicalCareCoordinators(CCC)toassistthemmanagethewell-beingofpatients undertheircare.Thesereportscouldalsobeusedbycarersanddoctors.Patientwell-beingreportsare meanttobeusedasanaidtoCCCs(notasafinaldecisiontool)andaremeanttobeusedinconjunction withthenurses’clinicalexperienceandbackgroundknowledgeofthepatient. Thisreporttriestoflagstatisticallysignificantdeparturesfromthebaselinemeasuresmadeonthepatient atthestartofthestudy.Choosingthebaselinemeasuresasthefirst30daysofthepatientstudyperiodfor thecomparisonpointmaynotbeagoodideabutitisselectedasthestartpointuntilwehavethenurse feedbackonwhatisappropriate. Definitionofterms 1. Baseline:Inthisreportthebaselinelevelisalwaystakenasthefirst30daysaveragemeasurement. Futuremeasuresarecomparedtothisbaseline. 2. Localintime:Measurementschangeasthewell-beingofthemonitoredpatientaltersovertime, andifthemeasurementisrepeateddirectlyafteritismeasureitisneverthesamesoweare interestedinmakingareasonableestimateofthepatientswell-beingnowgiventhismeasurement uncertainty,thisisachievedbytakinganaverageofthemostrecentobservations(calledamoving average). 3. Level:Levelisdefinedastheaveragemeasurement.Forexamplethelocallevelistakenasthe movingaveragevaluewhichisregardastheestimateofthelocalexpectedmeasurementforthe patient. 4. Scale:Scaleisusedtogaugethenaturalvariationinthepatientmeasures,forexamplehowmuch doweexpectapatientmeasuretodifferinabsolutemagnitudeonaveragefromdaytodayiftheir well-beingdidnotchange.Instatisticsthisissometimesreferredtoasvarianceorstandard deviation. 5. Achangeisstatisticallysignificant:Thismeansthatthechangeislargeenoughtobeconsidered veryunusual.Measuresvarynaturally(theydifferfromtimetotime)andthetrendsfromthe baselinelevelneedstobelargeenoughrelativetothisnaturalvariationtobeconsideredunusual. 20 http://www.health.gov.au/internet/main/publishing.nsf/Content/PCEHR-Review CSIROTelehealthTrialFinalReportMay2016 Page165of187 6. Achangeisclinicallysignificant:Ifthismeasurementshiftsfarenoughtoconsiderthatthe person’swell-beingisindanger.Forexampleifsomeonebody’stemperatureshiftstoalevelof 39oCthenthisismathematicallyhighenoughtobeofconcern. 7. In-control:Ifapatient’smeasuresarepredictablewithintheirnormalrangethenwesaythatthe patient’swell-beingiswithinstatisticalcontrol.Thisisawayofdescribingthatthepatientwellbeingisstableandnotwanderingallovertheplace. 8. Trend:Ifameasurementremainsonaverageunchanged,i.e.,theyarerandomlydistributed aroundafixedlevelthenwesaythereisnotrendinthemeasurements.Howeverifthelevelstarts movingtolower/highervaluesinapersistentwaythenwesaythatthismeasureisexhibitinga trend. 9. Changepoint:Thechangepointisthedeterminationofthedatewhenthepatient’smeasurement changessignificantly.Twochangesareconsidered.Thefirstarechangesinlevel,forexamplea bodytemperatureshiftfrom36.5oCto39oC.Thechangepointisthedaywhenthemeasurement startedtochangefromanaverageof36.5oCtoanaverageof39oC.Thesecondisthechangein uncertaintyorstandarddeviationwhichisameasureoftheday-to-dayvariabilityinthe measurements. 10. Changeinmagnitude:Thisreportassumesastepchangeandestimatesthemagnitudeofthese changesonlyiftheyarestatisticallysignificant,i.e.,itestimateswhatthemeasurechangesfrom andwhereitmovesto. 11. Stationary:Althoughstationary,inmostcircumstances,meansthatitdoesnotmove–inthis reportwerefertoitasnotmovingbeyondcertainbounds.Ifwerefertoaprocessmeasurebeing stationarywemeanthatitcanwanderaroundalittlebutitalwayswandersbacktoaglobal averagevalue.Inotherwords,althoughthemeasurewandersinawaythatneighbouring measuresarecorrelated,itdoesnotwanderoffto-wardsinfinity.Mostofthemeasuresarelike thiswhenin-control.Theonlymeasurethatexhibitsnaturalwanderingbehavioursuchthat neighbouringmeasuresarepositivelycorrelatedisbodyweightandintheorythesemeasures,if yousurvive,areexpectedtowanderwithinbounds. Allthestatisticalteststhatfollowestablishsignificantdepartureinwell-beingrelativethebaseline measures.Theexpectedmeasureistakenasthemeanandstandarddeviationforthefirst30daysofthe patientstudyperiod(andthisiscalledthebaseline). ThereportconsistsoffollowinggraphicaltoolstoassistClinicalCareCoordinators: 1. TheOveriewplot(Figure80)whichuses“traffic”lightstoflagwhatmeasurestolookatforthe CCC.EachCCChas25testpatientstocareforandthereareeightmeasurespatientscantakedaily. Thisintotal,amountstoapotential200(25x8)measure-patientcombinationstoexamine.This overviewplotprovidestheCCCwithasnapshotofwhatmeasure-patientcombinationstofollowupon(i.e.,onlylookatthosewithredsignalsshouldbefollowedupfirst,becausetheyindicate significantdeparturesfrombaselinemeasure). 2. TheTrendplot(Figure82)indicatestherawmeasurement,theaveragetrendintheseandflags whetherthisaveragetrendhasdepartedfromtheaveragemeasureduringthebaselineperiod (first30daysofmonitoring). 3. TheChangePointplotforLevel(Figure84)indicatestheestimatedtimepointwherethelevelof themeasurechangedandestimatesthemagnitudeofthischange.Thisonlyconsidersstep changesandnotgradualchanges.Whatwearelookingforarerapidlargechangesinmeasures. Pleasenotethatthisapproachwillregardallchangesasstepchangesandthereforeagradual CSIROTelehealthTrialFinalReportMay2016 Page166of187 changewilleitherbereflectedasalevelchangeatsomestage,butinitiallyitwillberegardedasa changeinuncertainty(scale).Ifthechangepointlineishorizontalwithoutachangethenthis indicatesthattherehasnotbeenachangeinthelevelofthemeasurethroughoutthecurrent studyperiod.Identifyingthechangepointandthenatureofthechangeisatoughappliedproblem thathasnotbeencompletelysolvedintheliterature.Westartwiththesimplestchangepoint technology.Thechangepointisimportantinidentifyingthehazardeventthatfacilitatedthe change–identifyingthesehazardsareimportantformanagingapatientwell-beingrisk. 4. TheChangePointplotforScale(Figure84)indicateswhethertheestimatedtimepointwherethe uncertainty(scaleorvarianceorstandarddeviation)ofthemeasurehaschangedandestimatesthe magnitudeofthischange.Thisonlyconsidersstepchangesandnotgradualchanges.Changesin uncertaintycouldhavetwocauses.Firstlyitcouldbecausedbygreaterorlessermeasurement error.Secondlyitwouldbeduetothepatiententeringintoaperiodofunstablewell-being. ExamplesofplotsandtheirinterpretationsareillustratedinFigures81-88. Notethattrendplotsandchangepointplotsareonlyproducediftheoverviewplothasaredtrafficlight. Overviewplot Theoverviewplotoffersaviewofallpatientmeasuresinatrafficlightmatrixform.Thematrixhasthe numberofrowsequaltothenumberofpatientsandthenumberofcolumnsisthefullnumberof measures..AnexampleforTasmania’spatientsonthe17MarchisreportedinFigure81. Notethefollowingrules: • • • • Thesolidgreencirclestrafficlightsindicatewhenthelocalmeasurementsdonotsignificantly departfromthebaselineaveragemeasurements,e.g.,patient53andsystolicbloodpressure(SBP). Redindicatesthatthelocaltrendhasdepartedstatisticallysignificantlyfromthebaselineaverage measurements,e.g.,patient2andmeasurementbodytemperature. Apositiveredsignindicatesasignificantdepartureonthehigh-side,thatisthemorerecent measurementsarestatisticallysignificantlyhigherthatbaselineaveragelevel. Anegativeredsignindicatesasignificantdepartureonthelow-side,thatisthemorerecent measurementsarestatisticallysignificantlylowerthatbaselineaveragelevel. Notethatthereisafalsediscoveryrateof1in100dayswhichmeansthatafalsesignificantchangeis flaggedonaverageeveryonehundreddays. • • • Ifaspecificmeasurementisnottakenbyapatientthenasolidblackcircleappearsforthepatientmeasurecombination,e.g.patient2andmeasureSBP. Ifaspecificmeasurementisnevertakenbyapatientthenthepatient-measurecombinationspace isleftblank.,e.g.patient11hasonlymeasuredbodyweightinthepast Ifameasurementisexcludedasextremelyunusualbythemeasurementqualityassuranceprocess thenitappearsasasolidorangecircle. Thisallowsthenursetoquicklyobservewhatmeasurementsthepatientistakingandwhatisunusual relativetothebaselineaveragemeasureandhowitisunusual,e.g.,onthelow-sideoronthehigh-side CSIROTelehealthTrialFinalReportMay2016 Page167of187 Figure80AnexampleofanoverviewplotforTasmanianpatients Patient2inFigure80onlymeasuredBT,SpO2andBWonthe17March2014.OftheseonlyBTandBW flaggedastatisticallysignificantchangeinlevelfromthebaselineaveragevalue.Thispatienthasnever measuredPEF,FEV1andFVChencethesefieldsareleftblank. Ideallyyouwouldwanttofollowthetrendsinthetrafficlightsignalsfromonedaytothenextto understandwhattrendsareemerginginthesuiteofmeasurements. AWithinPatientOverviewPlot: Interpretingapatientstabilityofwellbeingoverthepast7days The“parallelcoordinateplot”isusedtodisplaytrendoverthemostrecentpast7daysforallmeasuresso thatclinicianscangetanoverallprespectiveonthepatient’scurrentwellbeingrelativetothebaseline period.Thisplotattemptstodisplaywhetherthepatientswellnesschangesrecentlyfromthebenchmark. Thetrendsinallmeasurementsareusedtoflaganoverallhealthconcernortoflagtheneedtocelebratea majorimprovement.Thisplotisonlyproducedinthereportforpatientswiththreeormoreunusual flaggedtrendsduringthelastday.Itisdesignedtohighlightpatientthatareeitherdoingpersistently betterthanbaselineorunusuallybadlyrelativetobaseline.Theparallelcoordinateplotisdesignedforthe nursetoviewtheoveralltrendsinwellnessacrossallthemeasures–itmaytaketimegettingusedtothe plotbutonceusergetthehangofit,theplotmayproveuseful. CSIROTelehealthTrialFinalReportMay2016 Page168of187 AnexampleoftheparallelcoorinateplotispresentedbelowinFigure81 Figure81Parallelcoordinateplotsindicatingmultivariatetrendsinapatient’smeasurement Figure81indicatesthatpatient7onlymeasuresbloodpressure,bodytemperature(BT),SpO2andBody weight.Thegreyregionindicateswhetherthemeasurementwouldexpecttobe(giventhecurrent variationinvalues)inthelevelwasequivalenttothebaseline.Figure81clearlyindicatesthatoverthe pastsevendaysthat: • • • • • SystolicBloodPressure(SBP)hasbeenveryconsistentlybelowthebaselineaverage. DiastolicBloodPressure(DBP)hasnotdepartedfromthebaselinelevel. BodyTemperature(BT)hasbeenconsistentlyabovethebaselinevaluebutnot mathematically(clinically)highenoughtobeaconcern. SpO2hasbeenconsistentlyhigherthanthebaseline. Bodyweight(BW)inthepastweekhasnotdepartedfromthebaselineaveragevalue. Thefactthattherearetimeswhenthelinescannotbeseparatedshouldnotbeaconcernasthisisinfact information.Itsuggeststhatthemeasurementsareveryconsistentfromdaytoday.Weonlywanttolook atthisifseveralmeasuresaretrendingawayfrombaseline.Thisplotiscurrentlyonlyproducedforpatient with3ormoresignificanttrendsjustasawayofrestrictingtheinformationdumponthecliniciansand nursingstaff. Trendplot Theflaggedchangesinlevelofmeasuresforapatientintheoverviewplotareindicatedbyredsolid circles.Wheneverthisoccursintheoverviewplotthenthereportdeliversthreegraphs.Thefirstgraphis labelledthetrendplot.Thisisdesignedtoindicatethenatureofthischangeintrendandhowfarithas departedfromthebaselineaveragemeasure,e.g.,Patient2inFigure82whosetemperatureshowsa significantincreasebutnottothelevelthatwouldbeaconcern(e.g.,above37.5oC).Fortechnicaldetails seeMontgomery(2005). CSIROTelehealthTrialFinalReportMay2016 Page169of187 Thefollowinginformationisincludedonthetrendplot: • • • • • • Thegreenlineontheplotindicatestheaveragemeasureduringthebaselineperiod(baselineis takenasthefirstmonthinthereport). Theregionbetweenthereddashedlinesindicateswheretrendplotlinesshouldremainifitisnot significantlydifferentfromthebaselinedistributionofmeasures. ThetrendintheaverageBTvaluesistheblacklineinFigure82whichisthemovingaverageofthe measuredvalues. Thegreyregionindicatestheconfidenceintervalforthesmoothedestimateofthelocaltrend. Iftheblacklinetrendremainswithinthegreyshadedregionthenthetrendismorebelievable. Ifthegreyregionliesoutsidetheregionspannedbythereddashedlinesthenwearealmost certainthepatientconditionfromthismeasurediffersfromthebaseline. 30 days baseline period Flagging a significant increase in BT Figure82Anexampleofthetrendplotforpatient2fromTasmania Changepointplots Theremainingtwoplotsarechangepointidentificationplots(labelledchangepoint&magnitudeforlevel orchangepoint&magnitudeforscaleplots).Thischangepointistestedoverthewholehistoryofthe patientmeasurementprocess.Ifasignificantchangepointisdetectedthenthechangepointsare estimatedtogetherwiththemagnitudeofthechangeandthenthechangeisplottedinagraph.Twotypes ofchangesaredetected(seeCapizziandMasarotto,2010): CSIROTelehealthTrialFinalReportMay2016 Page170of187 a)Changepoint&magnitudeforlevel Thechangepointandmagnitudeforlevelplotflagsastepchangeinthetrendofthemeasures.Thestep changetrendplotconfirmswhatthetrendplotindicates,butchangepointplotdoessoassumingthat thereisastepchangeratherthanacontinuouschangeinlevelasinthetrendplot.Theextrainformation thisplotoffersonthetrendplotistheestimateofthedateofthechangeandanestimateofitsmagnitude. Figure83indicatesastepchangeinlevelofSystolicBloodPressure(SBP)tolowervaluesthatoccurredin September2013butsincethenthemeasurementlevelstabilisedatjustbelow80.Thep-valueinthe bracketsoftheplottitleisthelevelofsignificanceofthechangepoint,e.g.,withp=0thisindicatesahighly significantchangepoint. Figure83Anexampleofstepchangeinthetrend b)Changepoint&magnitudeforscale Thestepchangeinthevarianceofthemeasuresisthelastplotdisplayed.Thischangeinvarianceisoften referredtoasameasureoftheuncertaintyinthelevelofthemeasurement.Uncertaintyhereisboththe smallday-to-daymovementsinlevelofameasureandtheinabilitytoreproducethesamemeasurementif thesameentityismeasuredagain.Thistestswhethertheuncertaintyinmeasureshas increased/decreasedsignificantly. Figure84indicatesseveralstepchangesinthescaleofSystolicBloodPressure(SBP)butthesechanges bouncearoundthe2standarddeviationmark.Recentlythereisgreateruncertaintyinthemeasures(e.g., nearlyastandarddeviationof3).Itisoftendifficulttointerpretthisplotbutwearelargelyinterestedin grosschangesinuncertaintynotmoderatechangesthatarerecordedabove.Thep-valueinthebracketsof theplottitleisthelevelofsignificanceofthechangepoint,e.g.,withp=0thisindicateshighlysignificant changepointsthetimeseriesplotofstandarddeviations. Figure84Anexampleofachangepoint&magnitudeforscaleplot. Figure84showsastepchangeinthescale(uncertainty)ofthemeasures. CSIROTelehealthTrialFinalReportMay2016 Page171of187 Whatdoesatrendplotlooklikewhenitfailstoflagasignificanttrend? Sinceaplotisnotproducedifthepatient-measurecombinationdoesnotflagasignificantdeparturefrom thebaseline,theCCCwouldnothavetheknowledgeofwhattheplotshouldlooklikewhentherewasno changeinthemeasuresfromthebaseline.Thefollowingplotillustratesanexampleofmeasuresthathave notchangedsignificantlyfromthebaseline. Figure85Anexampleofmeasuresthathavenotchangedsignificantlyfromthebaseline. InFigure85abovethetrendplotindicatesthatthelocalaverageBThasnotmovedsufficientlytoindicatea significantdepartureinthemeasuredistributionforthefirstmonth.Althoughthelevelchangeindicatesa significantincreaseinbodytemperatureneartheendofNovember2013inthelevelchangepointanalysis, thischangeissosmallinmagnitudethatitisofnoconcernandthereforeunimportant.Themeasurement uncertaintyislessthan0.1whichindicatesahighdegreeofcertaintyinthemeasurementprocess. Statisticallyspeakingwenormallyrefertothispatientasin-control. CSIROTelehealthTrialFinalReportMay2016 Page172of187 Appendix:Exampleofplotsandtheirinterpretations Example1 Historyofbodytemperatureforpatient1inTasmaniacanbeobservedinFigure86below.Thispatient startedwithanaveragetemperatureof36.5oCandthereisevidencethatthetemperatureincreased significantlyfromthisbaselineontwooccasions.Althoughthetemperaturehasincreasedsignificantly;itis stillwellbelow37.5oCandthereforeisnotmathematicallyhighenoughtobeaconcern. Thechangepointinbodytemperatureisverysoonafterthefirstmonthbutalthoughthereareother changesinlevelofbodytemperature,italwaysremainswithinthenormalrangeforBT. Thechangeinscalehappenedlaterbutagaintherearenoconcerns. Figure86Bodytemperaturevaluesforpatient1 CSIROTelehealthTrialFinalReportMay2016 Page173of187 Example2 SpO2valuesforpatient6inTasmaniacanbeobservedforthefullstudyperiodinFigure87below.This patientstartedwithanaveragebloodoximetrylevelof99.6%inthefirstmonthandthereisevidencethat thishasdecreasedsignificantlyfromthisbaselineinrecentmonths.Althoughthebloodoximetrylevelhas decreasedsignificantlyfromthestartitisstillcloseto99%andthereforeisnotmathematicallylowenough tobeaconcern. Thechangepointinbloodoximetrylevelhasbeenobservedinthelastfewmonthsbutthischangeis mathematicallynegligible. Thechangeinscalehappenedearlierafterthefirstmonthbutthechangeinmagnitudeofthelevelis mathematicallyverysmallalbeitstatisticallysignificant. Thereisalsoanincreaseintheuncertaintyofthemeasureswhichmayneedaninvestigation. Theadvicetothenurseistomonitorthispatientcloselyoverthenextmonthtoseeifthisdowntrend persistsorstabilisesatalevelthatremainswelloutoftheconcernedregion. Figure87SpO2valuesforpatient6 CSIROTelehealthTrialFinalReportMay2016 Page174of187 Example3 WecanexaminetheSBPforpatient7inTasmaniainFigure88below.Thispatientstartedwithanaverage SBPofabout144inthefirstmonthandthereisevidencethatthishasdecreasingsignificantlyafterthefirst monthofmonitoring.AlthoughtheSBPlevelhasdecreasedsignificantlyfromthestartitseemstohave stabilisedcloseto130onaverage.Thislevelchangehasbeeninthedirectionofsaferlevelsandnowthe SBPisnotmathematicallyhighenoughtobeaconcern. ThechangepointinSBPlevelhasstabilisedafterthefirstfewmonths. TheuncertaintyintheSBPmeasure(scale)haschangedseveraltimesbutonthewholeseemstobe reducingslightlyovertime. ThispatientshouldbecongratulatedformanagingtheirSBPhealthwell. Figure88SBPvaluesforpatient6 CSIROTelehealthTrialFinalReportMay2016 Page175of187 Example4 Bodyweightforpatient9inTasmaniaisreportedinFigure89below.Bodyweightishandleddifferentlyto allothervariablesbecauseitistheonemeasurementthatusuallyiscorrelatedovertime,e.g.,thelast measurementishighlyrelatedtopreviousmeasurement.Thereforeitisassumedtowandernaturallyand weallowthismeasuretohavea“stationary”trendbutwetrytodetermineifthistrendisunusuallyhigh. Thegreenlinehereistheonestepaheadforecastedbodyweightwhichestimatestheamountitis expectedtowanderusingpastdata.Wearelookingatwhethertheblacklinedecreases/increasesfaster thantheforecastvalue. Thispatientstartedwithaforecastbodyweightofabout112.5kgandwithinthreemonthsthisincreased atanunusualratetonearly125kg.ThereisevidenceofarapidreductioninweightinearlyNovemberand thereafterthechartflagsthisasanunusualdecreaseinJanuaryandFebruary2014.However,recentlythis weightisincreasingagain.Theremaybetimeswherethispatientwaslosingweighttoofastandgaining weighttoofast.Itseemsthatthispatienthasdifficultycontrollinghis/herweight. Thechangepointcharttestsarebasedontheassumptionthatthedataareuncorrelated,andsincethisis nottrue,thechangepointanalysisforweightshouldonlybeviewedasaroughguide. Figure89Bodyweightvaluesforpatient9 CSIROTelehealthTrialFinalReportMay2016 Page176of187 Example5 Bodyweightforpatient28inTasmaniaisreportedinFigure90below.Thispatientstartedwithaforecast bodyweightofabout69kgandwithinthreemonthsthiswasverystableatthislevel.Frommid-February thishassteadilyincreasedwithseveralflaggedincreases.Thechangepointalsoindicatesachangeby assumingthatthisrampingupisastepchangeandindicatesthatthechangepointislaterthanmidFebruary.Inaddition,theuncertaintyinBWhasalsochangedinmid-February.Thisindicatesthatthe chartssuggestaperiodofunstableBWpriortotheupwardtrend. Figure90Bodyweightvaluesforpatient28 CSIROTelehealthTrialFinalReportMay2016 Page177of187 Lookingatthewell-beingofasinglepatientononeparticularday Wheninvestigatingthewell-beingofapatientweshouldexamineallflaggedstatisticalsignificantchanges andtrytointerpretthepatientoverallwell-beingusingalltheavailableinformation. Wenowinvestigatepatient2onadaywherethefollowingmeasuresareflaggedashavinganunusual change:bodytemperature,bodyweight,heartrateanddiastolicbloodpressure.Theseplotsarenow exploredandinterpreted. Figure91BodytemperatureofPatient2untiltheendofMarch2014 Thebodytemperaturehasincreased(Figure91)butnottothelevelwheretherewouldbeaconcern–the smoothestimatesofthelocalaveragemeasurementarewithinthenormalrange,i.e.,lessthan37oC.The uncertaintyinthemeasuresmovesaroundbutthetrendistowardslessuncertainty. CSIROTelehealthTrialFinalReportMay2016 Page178of187 Figure92BodyweightofPatient2untiltheendofMarch2014 Althoughpatient2haslostastatisticallysignificantamountofweightrecently,mathematicallythese changesarenothigh(seeFigure92),i.e.,lessthan3kgs.Thecurrentaverageweightiswithinthehistorical rangeexperiencedinthepast.Thecarerwouldwanttowatchwhetherthistrendpersistsinthenextfew daysorweeksandifitdoes,thenconcernswouldberaisedparticularlyifthepatientisnottryingtolose weight. Figure93HeartrateofPatient2untiltheendofMarch2014 CSIROTelehealthTrialFinalReportMay2016 Page179of187 TheheartrateinFigure93hasdroppedsignificantlytoalevelofabout80beatsperminutebutthisiswell withinthenormalrangeandsotherearenoconcernshere,particularlywithitprogressingslowlybackup tothelevelofthebaseline. Figure94Systolicbloodpressure(SBP)ofPatient2untiltheendofMarch2014 TheSBPhasdroppedsignificantlyfromalevelofabout140toalevelofabout125andithasmovedwithin thelimitsofthenormalrange(Figure94).Thechangepointplotisnotgoodatidentifyingwhenthis changeoccurred.ItsuggeststhechangeoccurrednearJanuary2014howeverthetrendplotclearly suggeststhatthechangeoccurredaroundmid-August2013.Thetrendupwardsinearly2014andlate 2013confusesthechangepointestimationprocess. Insummarythispatientseemstohaveimprovedhis/herhealthoutcomewheremostmeasuresthat flaggedsignificantchangesweretrackinginthedirectionofbetterhealth–maybethispatientshould celebratehis/hersuccess. Someusefulrulesformonitoring 1. Don’toverexertyourselfrespondingtoday-to-dayvariation.Onlyrespondtotrendsthatmatterin amagnitudesense(i.e.,thatclinicallyraiseaconcern). 2. Statisticalsignificanceisaguidetowhatisconsideredunusual.Generallyweonlyconsider respondingwhentrendsarebothunusualandlargeenoughinmagnitudetobeaclinicalconcern. 3. Levelchangepointsideallyshouldbematchtoeitheracriticaleventoranassignablecause– monitoringismostlyaboutunderstandingvariationandlearningfrompastcriticaleventsor assignablecauses.Thisunderstandingleadstobettercontrolofthepatientwell-being. 4. Changepointsinuncertaintyaregenerallylessimportantthantrendsinlevel,butoftenarehelpful inmanagingmeasurementerror.Itisimportanttodistinguishbetweenmeasurementuncertainty duetoerrorsanduncertaintyinpatientwell-being. CSIROTelehealthTrialFinalReportMay2016 Page180of187 Technicaldetails Sometestsarebasedonthemeasuresbeingnormallydistributedandothersarebasedondistributionfree tests.Thetrendplotassumesthatthemeasuresarenormallydistributedtotestwhetherthetrendinthe localaveragehasshiftedenoughtoflagasignificantdeparturefromthebaselineaveragevalue.Sincethis testisonthelocalaverageitgenerallywillnothavethesamepowerasthechangepointtestforfinding changepoints,howeverontheotherhandthetrendplotisnotrestrictedtostepchangesandconsiders generalchangesintrend.Soifthetrendisnotastepchangethetrendplotmayofferbetterinferential judgements(e.g.,Figure93). Inthechangepointplotweonlycheckforastepchangeusingadistributionfreetest,andweonlyestimate thechangepointifthischangeissignificant.Thisistestedatthelevelofsignificanceof0.05.Thep-value indicatesthelevelofsignificanceofthetest–thesmallerthisisthemoresignificantthechangeis(i.e.,the morecertainwearethatitisarealchangeandnotafalsediscoveredchangehasoccurred). References 1. GCapizziandG.Masarotto(2010).PhaseIDistribution-FreeAnalysisofUnivariateData.Journalof QualityTechnology,Vol.45,No.3,pp.273-284. 2. Montgomery,Douglas(2005).IntroductiontoStatisticalQualityControl.Hoboken,NewJersey: JohnWiley&Sons,Inc CSIROTelehealthTrialFinalReportMay2016 Page181of187 8.8 ReflectionsofaProjectOfficer BeforecommencingtheprojectIcouldenvisagemanybenefitsofthetelehealthhomemonitoringmodel withpatientswithchronicdisease.Thesebenefitsincludedimprovedclinicalmanagementofpatientsina primaryhealthsetting,aswellaseconomicandefficiencybenefitstothehealthsystem. Iperceivedtheimprovedclinicalmanagementbenefitstoincludefeweracuteexacerbationsthroughearly detectionandfewersubsequenthospitalisations.Thisshouldleadtopatientsreceivingtherightcarein therightplace.Itshouldalsoimprovelongtermhealthoutcomesforthepatients. Benefitstothehealthsystemincludereducingtheburdenonhighdemand,highcostacutehospitalbeds. ItalsohasthepotentialtoreducetheburdenonsectionsofprimaryhealthcarebypotentiallyreducingGP visits.GPvisitscouldpotentiallybemoreproductivebyprovisionofpatienttrenddataenablinggood clinicalmanagementdecisionmaking. Atthisprojectsite,theprojecthasbeenverysuccessfulinachievingalloftheseoutcomestovarying degrees. Theprojecthasachievedsomelevelofintegrationacrossanumberofhealthsectors,includingacutecare, primarycareandgeneralpractice.Themodelhasbeenverywellembracedinsomeareas,tothepoint whereGP’sarereviewingtheirpatientsdataonlineduringconsultations,andevensomeGP’sare monitoringtheirpatientsinbetweenconsultations. Whathassurprisedmeisanumberofunforeseenordiscountedbenefits(onmypart).Themodelhas providedanaddedlayerofsupporttopatientswithchronicdisease.Patientshavecommentedontheir addedfeelingsofsecuritybyknowingthattheirconditioniscontinuallymonitored. Themostsurprisingoutcometomehasbeenthelevelofempowermentandknowledgethehome monitoringhasgiventhepatientsintheirself-management,aswellasdiscussingandmanagingtheir condition(s)withtheirGP’sandhealthcarepractitioners. Allinalltheprojecthasshownsignificantqualityoflifebenefitstopatientsaswellasbenefitstothehealth caresystemoverall. SharonWilliamsRN TelehealthHomeMonitoringProjectOfficer TasmanianHealthOrganisation–North 24thSeptember,2014 CSIROTelehealthTrialFinalReportMay2016 Page182of187 9. Publications 9.1 RefereedJournalPublications 1. Sparks,R.,Celler,B.,Okugami,C.,Jayasena,R.,&Varnfield,M.(2016)TelehealthMonitoringof PatientsintheCommunity.JournalofIntelligentSystems,25(1):37-53.DOI10.1515/jisys-2014-0123. 2. Jang-Jaccard,J.,Nepal,S.,Celler,B&Yan,BO.(2016).WebRTC-basedvideoconferencingservicefor telehealth.Computing,98(1-2):169-193. 3. Celler,B.G.,&Sparks,R.S.(2015).HomeTelemonitoringofVitalSigns—TechnicalChallengesand FutureDirections.IEEEJournalofBiomedicalandHealthInformatics,19(1),pp.82-91. 4. Celler,B.G.,Sparks,R.,Nepal,S.,Alem,L.,Varnfield,M.,Li,JJang-Jaccard,J,McBride,SJ&Jayasena,R. (2014).Designofamulti-sitemulti-stateclinicaltrialofhomemonitoringofchronicdiseaseinthe communityinAustralia.BMCpublichealth,14(1),1270. 9.2 ConferenceProceedings 5. Celler,B.G.,Sparks,R.,Alem,L.,Nepal,S.,Varnfield,M.,Sparks,R.,Li,J.,Jang-Jaccard,J.,McBride,S& Jayasena,R.G.etal.,(2015).“OptimizingPointofCareEngagement.TelehealthPOCTechnologiesto EnableAssimilation/adoptionintheAging,ChronicallyIllCommunity.”Mini-Symposia:37thAnnual InternationalConferenceoftheIEEEEngineeringinMedicineandBiologySociety.Milan,Italy,2015. 6. CellerB.G.,&Sparks,R.(2015),“ModelBasedMethodsfortheAnalysisofNon-stationaryEffectsof TelemonitoringasanInterventionfortheManagementofChronicConditionsatHome”,37thAnnual InternationalConferenceoftheIEEEEngineeringinMedicineandBiologySociety,Milan,Italy,August 25-29,2015. 7. CellerB.G.Basilakis,J.,Goozee,K.,Ambikairajah,E.(2015),“Non-Invasivemeasurementofblood pressure-WhyweshouldlookatBPtracesratherthanlistentoKorotkoffsounds”,37thAnnual InternationalConferenceoftheIEEEEngineeringinMedicineandBiologySociety,Milan,Italy,August 25-29,2015. 8. Nepal,S.,Jang-Jaccard,J.,Jayasena,R.,Cellar,B.,Sparks,R.,Varnfield,M.&LiJ(2015),“ASecureData ArchitectureforTelehealthTrial“,HISA,HealthInformaticsConference,Brisbane,3-5August2015. 9. JayasenaR,VarnfieldM,LiJ,CellarB,SparksR,NepalS.(2015),“Organisationalchallengesandmoving towardsanationaldeploymentmodelforchronicdiseasemanagementinthehomeusingTelehealth“, HISAHealthInformaticsConference,Brisbane,3-5August2015. 10. Sparks,R.,Okugami,C.,Good,N.,Jayasena,R.,Cellar,B.,VarnfieldM.&Nepal,S.etal.,(2015),“Telemonitoringofchronicallysickpatients.”,HISAHealthInformaticsConference,Brisbane,3-5August 2015. 11. Varnfield,M.,Li,J.,Jayasena,R.,Celler,B.(2015),“Astudyonthequalityoflifeandpsychological outcomesinelderlypatientsinhometelemonitoring.”HISAHealthInformaticsConference,Brisbane,35August2015. 12. Li,J.,Alem,L.,Varnfield,M.&Celler,B.(2014).“Astudyontheimplementationoflarge-scalehome telemonitoringservice”.InProceedingsofthecompanionpublicationofthe17thACMconferenceon ComputerSupportedCooperativeWork&SocialComputing,ACM,pp.193-196. 13. Celler,B.,Alem,L.,Nepal,S.,Varnfield,M.,Sparks,R.,Li,J.,McBride,SJ,&Jayasena,R.(2014), “Integratingcareforthechronicallyillusingathometelehealthmonitoring.”InternationalJournalof IntegratedCare.2014;14(9). 14. Celler,B.,&Sparks,R.(2014),“Improvingtheclinicalvalueofathometelehealth.”InternationalJournal ofIntegratedCare.2014;14(9). 15. Nepal,S.,Jang-Jaccard,J.,Celler,B.,Yan,B.,&Alem,L.(2013).“Dataarchitecturefortelehealthservices research:Acasestudyofhometele-monitoring”.The9thInternationalConferenceonCollaborative Computing:Networking,ApplicationsandWorksharing(Collaboratecom2013),IEEE,pp.458-467. CSIROTelehealthTrialFinalReportMay2016 Page183of187 9.3 ConferencePresentations 16. Celler,B.G.,Varnfield,M.,Li,J.,Jayasena,R.,Sparks,R.,Nepal,S.,&McBride.S.(2016)“Resultsofthe AustralianCSIRONationalMulti-sitetrialofathometelemonitoring”,TheEighthInternational ConferenceoneHealth,Telemedicine,andSocialMedicine,VeniceItalyIARIAeTelemed,April2428,2016. 17. Jayasena,R.,Celler,B.,Sparks,R,Varnfield,M.,Li,J.&Nepal,S.(2016).“MonitoringofChronicDisease inthecommunity:AustralianTelehealthStudyonOrganisationalChallengesandEconomicImpact”. DigitalHealthandCareCongress,May23-25th2016,Barcelona,Spain. 18. 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