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Process Improvement by
Backfilling Patient Records
In the Event of EHR System Downtime
Molly Lagermeier
Adele Golden
Cathy Olson
Bob Winston
Health Informatics Graduate Program
University of Minnesota
IPHIE
June, 2010
1
Objective
To survey and evaluate the EHR data
backfilling processes of major Minnesota
hospitals (post system downtime) and
develop recommendations for best
practices.
2
Problem Statement
With hospital clinicians using and relying
more on the information in the electronic
health records, the need exists for best
practice development in data backfilling
and clear links to scanned documents post
downtime. If not addressed, this is a
patient safety issue.
3
Background: Common Themes
Literature
Very limited research available. Data backfilling
is just beginning to be recognized for its
importance in EHR.
Topics found included:
 Downtime “kits”
 Different policies for planned and unplanned
downtime
 Policies for clinical data access during
downtime and backfilling patient information
4
Survey Methodology

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14 Multi-part Question Survey
12 major MN health care organizations
contacted
11 participated, representing 23 hospitals
In person or phone interviews conducted with
each participant
Open format responses
De-identified results to be shared with
participants
5
Survey Question Categories

System Environment:
EHR deployment stage
EHR vendor

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Cultural Environment:
Accountable role for downtime policy/procedures
Policy/procedures structure and implementation timing
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Process:
Data Backfilling (what, by whom, when, how):
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Automated feeds
Manual input of structured data
Scanning of paper documents
Prioritization (by department, data type)?
Audits?
Downtime Indicators and Scanned Document Links in EHR?
6
Stage of EHR Deployment
(Environment)
7
Vendor (Environment)
8
Ultimate Accountability
(Cultural)
* CIO Equivalent includes HIM Director, Clinical Informatics Director, IS Director.
9
Level Policies/Procedures
Kept (Cultural)
10
Post Downtime Policy Detail
(Cultural)
11
Data Backfilled From Other
Systems (Process)
12
Data Backfilling (Process)
What data will be backfilled by whom, by when, and
for what frequency and duration?
Results:
• ADT input by Admissions Dept as first priority
• If pharmacy system had also been down, getting medications dispensed
was next priority
• Lab, pharmacy, radiology all input their own data ASAP
• Nurses input data for their patients unless backup support needed for
significant downtime recovery. Timeframe of “ASAP” or by shift end.
• “Other” data backfilled included nurse initial assessment (ht/wt/allergies),
start and stop of IV and catheters, and discharge orders
13
Data Prioritization (Process)
What is the prioritization of data backfilling?
Results:
• Prioritization of data backfilling by type of data was found to be:
1) ADT, 2) Medications Ordered, 3) All Other Data Types
• Prioritization of data backfilling by a specific department was rare. All
get input ASAP.
• Quality Measures are still in their infancy in implementation in
backfilling. Only one organization had detailed quality measures included
in their backfilling procedures.
• Some hospitals chose not to input outpatient data (“we’ll catch it on their
next visit”)
• Emergency Department was least likely to have data backfilling in EHR,
especially if patient was not admitted.
14
Audits and Drills (Process)

Few organizations audit the backfilled

Downtime drills ranged in intensity

Night shift was often the only shift with experience with
“planned downtimes”

Executive sponsorship and commitment to continuous
improvement led to most effective drills
15
Common Themes…

Sometimes it takes a major downtime
incident before a hospital gets serious about
downtime recovery

Our survey prompted hospitals to internally
discuss their policy and procedures; some
immediately addressed gaps identified
16
Recommended Operational
Best Practice for Backfilling
Hours 4-6
Floor Nurses:
Input vital signs,
medications given,
I/O, catheters/IVS
added/removed,
discharge orders.
Review & approve
device data
inclusion.
Hour 1
Admissions Dept:
Inputs all
admissions,
discharges,
transfers
Hours 2-3
Pharmacy Dept:
Inputs all
medications
ordered and
dispensed (or
confirms the feed if
automatic)
Note: Hours are for example only. True hours will
vary depending upon amount of downtime, which
systems have automated feeds, and staff availability.
Ideally process will be completed within a shift from
a patient safety perspective, and teams will be “all
hands on deck” to complete the backfilling.
Hospital Unit
Coordinators
(HUCs): Input care
plan orders
Lab Dept: Inputs
lab orders and
results (or confirms
the feed if
automatic)
Radiology Dept:
Inputs radiology
orders and results
(or confirms the
feed if automatic)
Hours 7-8
Floor Nurses:
Review and
reconcile patient
records after the
admissions,
pharmacy, HUC,
lab, radiology and
their own input.
Add/validate
downtime “memory
aid” note.
Conclusions



Open response interviewing was useful in
uncovering not only the culture and readiness
for system downtime but the value placed on
data backfilling
Wide variation found in EHR adoption and
hence backfilling not only across health care
organizations but across hospitals within an
organization
Opportunities discovered for improvements in
policy/procedures, training, systems, and EHR
vendor software
18
Acknowledgements

Brian Patty, MD
Executive Sponsor, CMIO HealthEast

Skip Valusek, PhD
Champion, Director Clinical Analytics HealthEast

Survey Participants from:
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Allina Abbott Northwestern
Children’s
Fairview (8 hospitals)
HCMC
HealthEast (4 hospitals)
HealthPartners Regions
Mayo Rochester (2 hospitals)
North Memorial (2 hospitals)
Park Nicollet Methodist
St. Luke’s Duluth
VA Midwest
19
References
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1 ASTM E2682 - 09 Standard Guide for Developing a Disaster Recovery Plan for Medical Transcription
Departments and Businesses, http://www.astm.org/Standards/E2682.htm
3 Hurley, Brenda, CMT, “ASTM Introduces Disaster Recovery Standard -New standard could make HITECH compliance a little easier,” Advance For Health Information
Professionals, January 20, 2010
http://health-information.advanceweb.com/Features/Article-2/ASTM-Introduces-Disaster-RecoveryStandard.aspx
3 Certification Commission for Health Information Technology, http://www.cchit.org/about
4 Drazen, Erica, CSC (formerly First Consulting Group), Gilboard, Bethany, MPA, Massachusetts
Technology Collaborative; Metzger, Jane , CSC; Welebob, CSC; Massachusetts Technology
Collaborative / New England Healthcare institute, “Saving Lives, Saving Money In Practice: Strategies for
Computerized Physician Order Entry in Massachusetts Hospitals,” January 2009
http://web3.streamhoster.com/mtc/cpoe2009.pdf
5 McEvoy, Cheryl, “The Highs and Lows of Downtime Solutions. There's a spectrum of technology and
cost options to keep facilities afloat,” Advance For Health Information Professionals, January 2010
http://health-information.advanceweb.com/Editorial/Content/PrintFriendly.aspx?CC=213667
6 Getz, Lindsey, Dealing With Downtime — “How to Survive If Your EHR System Fails,” November 9,
2009, For The Record, Vol. 21 No. 21 P. 16
http://www.fortherecordmag.com/archives/110909p16.shtml
7 McEvoy, Cheryl, “EHR Downtime: The Aftermath What to Do Once the System Comes Back Up,”
January 18, 2010, ADVANCE, for Health Information Professionals, Vol. 20 • Issue 1 • Page 12
8 http://vitalcenter.galenhealthcare.com/
9 http://www.bostonworkstation.com/
20
Thank You
Questions?
Appendix
Project Gantt Chart
23
Stage (0-7) of the
HIMSS EMR Adoption ModelSM
(Environment)
At what stage (0-7) of the HIMSS EMR Adoption ModelSM are your cumulative capabilities? Circle stage.
(Reference http://www.himssanalytics.org/stagesGraph.html)
0 - All three ancillaries (lab, radiology, pharmacy) not installed
1 - All three ancillaries (lab, radiology, pharmacy) installed
2 - CDR; controlled medical vocabulary; CDS; may have document imaging; HIE capable
3 - Nursing/clinical document (flow sheets); Clinical Decision Support System CDSS (error checking);
PACS available outside of radiology
4 - CPOE; CDSS (clinical protocols)
5 - Closed loop medication administration
6 - Physician doc(structured templates); full CDSS (variance & compliance); full R-PACS
7 - Complete EMR; CCD transactions to share data; data warehousing; data continuity with ED, ambulatory, and OP
HIMSS EMR Adoption Stage
12
# of Hospitals
10
8
6
4
2
0
0
1
2
3
4
Stage
5
6
7
Unkno wn
24