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eHealth Technologies
for Lithuanian Health Care
Prof. Arūnas Lukoševičius
Biomedical Engineering Institute
Kaunas University of Technology,
,
eBaltic Forum Riga 2006 04 06
Biomedical Engineering Institute
Kaunas University of Technology
Activities:
•Telemedicine support centre
•eHealth architecture and
implementation
•Clinical decision support
systems
•Signal and processing
methods and software
•Ultrasonic medical diagnostics
•Prototyping of hardware,
sensors and transducers
•Wireless technologies
Studentų street. 50, Kaunas, LT-51368, tel. 407118, ISDN: 407114-407119
http://www.bmii.ktu.lt
Topics
• Why eHealth? Lithuanian statistics and arguments
• Principles of proposed architecture: patient centered
• Principles of implementation: standard based
• Electronic Health Record
• Data mining and clinical decision support
• Building bricks: international projects
• Efficiency of eHealth: user benefits and functionalities
• Cross - boarder cooperation and networking
Why eHealth? Lithuanian
statistics and arguments
Citizens, specialists and facilities: figures
District
Klaipeda
Kaunas
Siauliai
Panevezys
Vilnius
Extrapol. Total
Total
District
Klaipeda
Kaunas
Siauliai
Panevezys
Vilnius
Extrapol. Total
Total
Citizens
486,685
880,967
544,260
478,474
1,033,757
3,424,143
3,430,600
Hospitals
27
29
21
21
54
152
181
GP
Offices
105
176
102
91
306
780
750
GPs Specialists
385
1,092
696
2,710
430
757
378
811
817
3,339
2,707
8,708
2,707
8,708
Medical
points
0
906
Total
Physicians
1,477
3,406
1,187
1,189
4,156
11,415
11,415
Ambulatory
31
52
37
45
39
204
190
Primary HC
centers,
polyclinics,
Family
medicine,
Diagnostic
centers
37
96
43
24
60
260
225
Total
Physicians
(other
source)
1,477
3,406
1,187
1,189
4,156
11,415
13,682
Private HC
providers
31
31
504
Nurses
3,866
6,649
3,651
3,500
7,567
25,233
25,233
Pharmacies
156
290
175
132
347
1100
1,100
Hospital
Beds
4,714
8,536
3,920
3,475
9,910
30,555
31,031
Pharmacists
529
958
592
521
1,125
3725
3,725
Statistics of health transactions
Events Registered
Births
PHC encounters
Emergency
GP, PC, Ambu.
Referred to SHC (Specialist)
Epicrisis from SHC SP
Hospitalised
Epicrisis from Hospitalisation
Lab test at PHC level
Results from PHC lab
Radiology at PHC level
Results from PHC Radiology
Lab test at SHC level
Results from SHC lab
Radiology at SHC level
Results from SHC radiology
Prescriptions
Sickness leave certification
Total Transactions
Per Annum
29,765
22,910,700
780,700
14,695,500
7,434,500
7,434,500
811,300
811,300
15,896,417
15,896,417
2,180,201
2,180,201
12,007,240
12,007,240
892,430
892,430
25,000,000
1,787,686
120,737,827
Per Month
2,480
1,909,225
65,058
1,224,625
619,542
619,542
67,608
67,608
1,324,701
1,324,701
181,683
181,683
1,000,603
1,000,603
74,369
74,369
2,083,333
148,974
10,061,486
Per Day
113
86,783
2,957
55,665
28,161
28,161
3,073
3,073
60,214
60,214
8,258
8,258
45,482
45,482
3,380
3,380
94,697
6,772
457,340
Network of GP offices in Lithuania
3
12
3
0
26
3
9
19
7
12
1 3
0
21
10
4
13
17
2
6
5
17
10
16
0
4
44
4
9
2
7
10 8
17
14
13
20
121
16
13
10
17
4
4
4
6 14 0
13
13
17
8
7
11
4
4
37
11
3
10
Summary of data volumes generated at
healthcare institutions
Volume*/doc
Volume from Encounters
Volume from Referrals F028a-1a (1600 characters)
Volume from Epicrisis F027a (2700 characters)
Volume from Ambulatory reports F025a-LK (1900 characters)
Volume from In-patient reports F066a-LK (1500 characters)
Volume from Prescriptions (460 characters)
Volume from lab
Sub-total Volume of data generated in documents, (kB)
Volume from radiology, (GB)
Total Volume, (GB)
Per Annum
1,6
2,7
1,9
1,5
0,5
0,5
0,075
11.895.200
20.073.150
27.921.450
1.216.950
14.928.200
6.011.568
82.046.518
67.096
67.178
Per Month
991.267
1.672.763
2.326.788
101.413
1.244.017
500.964
6.837.210
5.591
5.598
Per Day
45.058
76.035
105.763
4.610
56.546
22.771
310.782
254
254
Year 2015 USA = 100 %
”Balls” rise steadily!!
mc = management cost
Cost = demand x unit price + mc
Units = operative care,
diagnostics, medication..
Value of a unit stays
roughly equal
Unit price raises
Demand stays equal or grows due to relative aging !
ICT assistance is necessary
Proposed eHealth system
• The project submitted in 2004 by MoH of
Lithuania
• Development of the Lithuanian Electronic Health
Services Infostructure (EHSI): Implementation of an
official health and healthcare information sharing and
exchange system, to support lifelong continuity-of-care
for healthcare professionals and citizens.
(expert team lead by Dr. Dimitris Kalogeropoulos)
First part - WB financed pilot national eHealth project
2005-6
Principles of proposed architecture:
patient centered
Components of eHealth system with patient and
his EHR in the centre
Stakeholders
Contributions
Services
Person/
Machine user
interface
EHR Phase I
Passive EHR
Citizen
EHR Phase II
Active EHR

State Public Health Ins. Service

Lithuanian Health Inform. Centre

State Drug Control Service/
State Pharmacy Department

State Patient Fund

Social Ins. Fund
Government
registries – Pop Reg.
Legacy IS


Decision Support Logic
MoH
Knowledge base
Care Policy Planning
Hospitals III level
Security Layer
Hospitals II level
Statistical Information

Polyclinics
Data Processing

Pharmacy

Analytical E.H.R. (Diagnostic Service Departments)

Clinical, Management & Communication Logic

Billing
GP

E H R based billing

Core E.H.R. (Episodes of Care, Diagnosis, Services)
SPF
Middleware Layer
Continuity of Care
Patient
Electronic Health Record
Continuous episode oriented health record
1
2
3
4
5
6
recovery plan
Tertiary Care
Secondary Care
Emergency
Primary care
5
4
3
1
2
3
6
Episode of Care (PHC)
-9 months
death
Principles of implementation: standard
based
Middleware of common services
ADT, Logistics, Scheduling
other Hospital systems
EHR
Instance
Registry
Citizens
Healthcare
(Business)
Process/
Logic
Modelling
(ENV 12967,
SAMBA)
H M Ds
Information
model
Care Mandate (direct mandate, referral)
Messaging Engine
(CEN/TC251, ENV 13606-3 & 4,
13607, 12612, EN WI 130
(SSR-MES))
Consumers
Control – rules
etc.
Contributors
GPs/ FMPs Specialists
Patient Data Collection,
Ordering & Review
Decision
Support
Healthcare
Delivery &
Decision Making
Task
Domain
Development
(metadata, rules,
control)
Communication Process Modelling Swimlane
Management Process Modelling Swimlane
(healthcare mandate, decisions)
Clinical Process Modelling Swimlane
(perceived patient condition, health issues)
Semantic Relationship Modelling (EN WI 133/DOM & ENV 12967: 2003 parts 1-3)
Information Modelling (EN WI 133/DOM & ENV 12967: 2003 parts 1-3)
Continuity of Care Concepts (CEN/TC251 ENV 13940)
(Standard Controlled Medical Vocabularies, classification systems and registries)
Low Level Record Components
(Standard Controlled Medical Vocabularies, classification systems and registries – ICPC-2, ICD-10, ATC, GP registry,
Citizens registry, Institutions registry, etc.)
Primary Care
Secondary Care
Tertiary Care
Care services
Medical
Technology
Data mining and clinical decision support
• Rationale
• Technologies
Philadelphia Inquirer
September 12, 1
Helping AVOID
costly clinical erro
World population
Re-calculated statistics of deaths caused by medical
errors
(rough estimate, no direct evidence)
Country
World
Population
Deaths/year Deaths/day
6446131400
2593234
7105
298290000
120000
329
Germany
82468000
33176
91
UK
60441457
24315
67
Sweden
9001774
3621
10
Denmark
5432335
2185
6
Finland
5223442
2101
6
Estonia
1332893
536
1
Latvia
2290237
921
3
Lithuania
3596617
1447
4
US
System of Clinical Decision Support
Clinical
Workstation
Rules Engine
Alert/Reminder
beeper
fax
email
database
select patient
record observation
enter order
Trigger
Gather data
Add data
Event Monitor
Common Data
Repository
Generation of decision tree (example)
New cases with
diagnostic
parameters
Decision tree
Data with known
diagnosis
Data Mining
Diagnosis
Other medical
testing
(histology)
New data with known
diagnosis
By D.Jegelevicius, Biomedical Engineering Institute, KTU.
Example of decision tree automatically generated to support
decision about differential diagnostics of intraocular tumours
Decision support:
from the patient to knowledge bank and back
Knowledge, rule
bank
Rules
Knowledge
General
information
Personalization
Generalization
Decision support
Information
Personal
information
Data
Intervention,
Patient
Health service
Expert foresights
Gartner Group:
Predicts through 2002, >75% of healthcare
organizations will implement rule-based
technologies
Beginning in 2000, computer-based patient record
systems and data repositories that do not support
an Arden Syntax-based, user-definable rulesprocessing system will lose market share.
Vendors using Arden: Siemens
McKessonHBOC
Eclipsys
IBM
Building bricks: international projects
Kaunas eHealth cluster
• Medical Component - Kaunas Medical University,
Biomedical Research Institute, University hospital (largest in
Lithuania, 2000 beds) other Kaunas hospitals and polyclinics, Society
of GP of Lithuania
• Technological Component – Kaunas University of
Technology, (KTU), ( the greatest technical university in Baltic
countries, with 11 faculties, it’s Biomedical Engineering Institute
having Telemedicine Support Center, (TSC), Biomedical Engineering
Master Program, other Kaunas universities (5 in total);
• Industry component – SMS companies
Kardiosignalas[7], Elinta[8], Elintos prietaisai[9], Elsis[10] and other.
EU FP 5 PROJECT
TELEMEDICARE
•
•
•
•
•
•
•
"The TelemediCare system permits advanced home care with maintained medical
safety. The result is increased quality of life without increased costs."
Bo Lundell, Acting Division Manager,Astrid Lindgren Children's Hospital.
New Market Possibilities
Advances on modern information and communication technology have together with
miniaturization of health diagnostic equipment given birth to a new revolution within
health care.
Body sensor technology facilitating mobile, multi-modal and wireless functionality
will be key components to future intelligent and user friendly medical monitors.
The integration of such sensors with new wireless network technology has given life
to new possibilities for cost-efficient patient treatment.
•
Efficiency of eHealth: user benefits and
functionalities
Users (beneficiaries) of eHealth srevices
•
•
•
•
•
•
•
•
Patients
Citizens
General Practitioners (GP)
Primary Care Centers
Specialists
Polyclinics
Hospitals
Health Information Centre (HIS) under the State Public
Health Service (SPHS)
• State Patient Fund (SPF)
• Dept. of Pharmacy, State Drug Control Office (SDCO)
• Software industry
Benefits and rationale categories
• Benefits and rationale are already discussed evident
enough to be structurised and even numbered !!!
• HL7 EHR System functional Model and Standard
Release 1.0., August, 2003, Why rationale
categories, v.1.2
1 To serve:
( HL7 EHR System functional Model and Standard Release 1.0., August, 2003,
Why rationale categories, v.1.2)
1.1
Patient-centered/oriented care
1.2
Longitudinal, interdisciplinary healthcare delivery (per episode,
disease, problem)
1.3
Point of service, point of care: immediate, real-time
1.4
Multiple care settings: acute inpatient, emergent (including trauma
and mobile care, ambulance), ambulatory, long term, home,
school, occupational, military
1.5
Personal health record: per patient
1.6
Provider business record: per organization, per business unit
1.7
Practitioner service record: per caregiver
1.8
Primary and secondary record uses
2 To promote
2.1
Patient safety
2.2
Best practice - effective, efficient and timely care
2.3
Patient empowerment: participation in care, self care
2.4
Improved outcomes, patient satisfaction
2.5
Confidentiality
2.6
Personal health, wellness and preventative care
2.7
Population health, wellness and prevention
2.8
Personal security (military personnel, special agents,
government officials)
2.9
Population security (homeland security, bioterrorism, chemical
terrorism, terrorist activity)
3 To ensure and ascribe
3.1
Accountability: of organizations, of business
units, of persons
3.2
Continuous record availability and access
3.3
Integrity of clinical decision
making/Effectiveness of clinical decisions
3.4
Integrity of the health record
3.5
Integrity of the health(care) delivery process
3.6
Health record privacy, PHI protection
4 To facilitate and enable
4.1
Health(care) delivery: immediate, real-time point of service, point of care
4.2
Efficient work flow and operations performance - streamline the way people
work
4.3
Communication: inter-practitioner
4.4
Clinical decision making
4.5
Trusted record management
4.6
Trusted record/information flow
4.7
Correlated business, clinical and caregiver record
4.8/. Continuous quality improvement and monitoring, measures of quality,
9
performance and outcomes
4.10 Payment and eligibility determination
4.11 Effective communication between patient, family, caregiver and care team
5 Based on
5.1
Patient safety and best practice guidance
5.2
Legal and regulatory requirements - national and regional mandates
5.3
Accreditation and professional practice standards
Functionalities for nurses ( an example of function –
benefit relation)
ID
Function
E/D[1]
Benefits
CC1.
Clinical communication
E
1.1; 1.2; 1.3; 1.8; 2.2; 2.6; 2.7; 3.2; 3.3; 3.4; 3.5;
4.1; 4.3; 4.4; 4.6; 4.7; 4.8; 4.11; 5.1; 5.2; 5.3.
CC6.
Support for clinical guidance
E
1.1; 1.3; 2.2; 2.4; 2.7; 3.3; 5.1.
CC10.
Sharing of laboratory test results
E
1.1; 1.2; 1.3; 1.8; 2.2; 3.4; 3.5; 4.2; 4.3;
CC14.
Support for chronic disease protocols
D
1.2; 2.6; 2.3; 3.3; 4.2.
AM3.
Clinical workflow tasking, scheduling
D
1.2; 2.2; 3.3; 4.2; 4.3.
AM4.
Referrals and registration for care
E
1.2; 1.3; 2.2; 2.3; 2.4; 4.1; 4.2; 4.3.
AM8.
Claims and encounter reports for reimbursement
E
1.6; 1.7; 3.1; 4.7; 4.10.
AM11.
Report generation (EHR data extraction in accordance with analysis and reporting
requirements)
E
1.6; 3.1; 4.2; 4.8; 5.2; 5.3.
CS7.
Controlled vocabulary [2]
E
1.2; 3.2; 3.4; 3.5; 4.3; 4.4; 4.6; 5.1; 5.2; 4.11;
CS12.
Axessibility from point of care
E
1.1; 1.3; 2.4; 3.3; 3.5; 4.4; 5.1.
E - Essential function, to be implemented within present stage of project; D - Desirable function, to be implemented if possible or in the next stage of the project.
Codification and terminology vocabularies(e.g. SNOMED), Classification of diseases ICD -10, International Classification of Primary Care (ICPC – 2 ) should be app
Levels of services
• Basic services
• Integrated common services
• High level professional medical services
Registries Integration
• Population Registry (MoI)
• State Registry of Managers of Personal Data
• Drug Registry: State Drug Control Office (+ve
lists), State Pharmacy Department (prices)
• Doctor & Nurse License Identification Codes
(MoH)
• Services Codes (SPF) in ICD-10 context?
• Classification systems (SCMV) – ICPC-2 ?
Functions ensured for patient 1
• Information support of Continuity of Health Care
in time and across institutions
• Clinical communication
• Practitioner – patient relationship
• Support for preventive care and wellness
• Capture and manage patient – reported or
externally available patient clinical history
• Create and maintain patient-specific problem,
procedure and medication list
• Medication and medication management
Functions ensured for patient 2
•
•
•
•
•
•
Pharmacy communication
Sharing of laboratory test results
Support for chronic disease protocols
Identification of citizen/patient and his status
Provider/practitioner registry
Report generation (EHR data extraction in accordance
with analysis and reporting requirements)
• Secure access to the system, secure data routing,
privacy[1], authentication, role-based authorisation
• Axessibility from point of care
• Capture of insurance information from state register
reportable and traceable over time
Functions ensured for GP 1
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Clinical communication
Practitioner – patient relationship
Support for preventive care and wellness
Capture and manage patient – reported or externally available patient clinical
history
Create and maintain patient-specific problem, procedure and medication list
Support for clinical guidance
Medication and medication management
Support medication prescriptions
Pharmacy communication
Sharing of laboratory test results
ECG cardiology
Imaging
Support for chronic disease protocols
Integrate device monitoring and remote health services such as telehealth data
Present clinical guidelines
Identification of citizen/patient and his status
Provider/practitioner registry
Functions ensured for GP 2
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•
•
Clinical workflow tasking, scheduling
Referrals and registration for care
Registration of care encounters
Health service reports at the end of episode of care
Integration of clinical data with administrative and financial
data
Claims and encounter reports for reimbursement
Integrate cost management information
Data availability
Report generation (EHR data extraction in accordance with
analysis and reporting requirements)
Disease registries
Data analysis and research
Functions ensured for GP 3
•
•
•
•
•
•
•
•
•
•
•
•
•
Audit trial
Standard based interoperablity, messaging and integration[1]
Maintain and identify a single patient record for each patient.
Secure access to the system, secure data routing, privacy[2],
authentication, role-based authorisation
Authorisation of the access to the EHR
Authentication of record authorship
EHR data extraction in accordance with analysis and reporting
requirements
Controlled vocabulary [3]
Capture and creation of clinical documents and notes
Responsiveness, user response time
Axessibility from point of care
Capture demographical information from state register, reportable and
traceable over time
Capture of insurance information from state register reportable and
traceable over time
Cross - boarder cooperation and
networking
Online international teleconsultations
Video camera:
•
•
•
•
SONY DXC-950P
3CCD
750 TV lines
58dB S/N ratio
Framegrabber miroVIDEO PCTV from Pinnacle
Systems GmbH
• S-Video PAL signal from SONY DXC-950P camera
• Capture with 750X580 resolution
• Colors calibrated using test table
Databases and portals
Telemedicine network TechNetBaltic 2001
Streaming back-up
4k
38
s
bp
Codec
Kaunas
2 Mbps
384 kbps
384 kbps
384 kbps
2 Mbps
Helsingfors
Oslo
2 Mbps
Telia satellit
Internet
Stockholm
2 Mbps
384 kbps
ISDN
384 kbps
St:Petersburg
Web-enable
PC´s
Telia ISDN
2 Mbps
Technical setup
Luleå
2 Mbps
TechNet Baltic 2001
Telia Streaming
Media
SUNET
SUNET
Visby
University
2 Mbps
>10 Mbps
Router
Router
Multipoint bridge
Gate H.323 / H.320
Camera, mic, TVmonitor
Scen / studio
Codec
Codec
Kontrollrum
>2 Mbps
Streaming encoder
Real ShureStream
(modem, dual ISDN & ADSL)
Camera, mic, video- & audiomixer,
VCR, TV-monitor
8
Telemedicine network Litnet life
connections, March 15 2002
Conclusions
•
•
•
•
eHealth comes inevitably
It’s important to start from right architecture
Lithuania is taking pilot steps
Data mining and clinical decision support are
important goals
• User benefits and funcionalities are highly
evident
• R&D projects and collaboration are vital
Thanks for kind attention
[email protected]