Health IT Summit in Chicago 2014 – “The EHR & Quality: The Current Evidence” with Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital Abha Agrawal, MD, FACP COO & VP of Medical Affairs Norwegian American Hospital iHT2 case studies and presentations illustrate challenges, successes and various factors in the outcomes of numerous types of health IT implementations. They are interactive and dynamic sessions providing opportunity for dialogue, debate and exchanging ideas and best practices. This session will be presented by a thought leader in the provider, payer or government space.

1. Electronic Health Record and
Quality:
The Current Evidence
Abha Agrawal, MD, FACP
Chief Operating Officer / Chief Medical Officer
Norwegian American Hospital
Adjunct Associate Professor of Medicine
Northwestern Feinberg School of Medicine
Chicago, IL
IHT2 | June 11 2014

2. Agenda
• Current state of EHR adoption
• EHR and quality benefits
• EHR and quality risks
• Socio-technical model for EHRs

3. High global EHR adoption

4. US hospitals EHR Adoption has more
than tripled since 2009
http://www.healthit.gov/sites/default/files/oncdatabrief16.pdf

5. Irrefutable Benefits of EHR versus
Paper
• Access to information – any place, any time,
multiple people
• Legibility / availability of information
• Security / privacy
• Communication / coordination
• Decision-support at the point-of-care

6. Evidence: EHR and Quality

7. Computerized Physician Order Entry
(CPOE): Medication Safety
10.7
4.69
4.86
3.99
Serious medication errors Preventable ADEs
55% decrease
5% decrease
Bates et al. JAMA. 1998; 280; 1311-16
Events
/
100
patient
days,
mean

8. 42.5
6.6
0
5
10
15
20
25
30
35
40
45
Paper Stand-alone E-Rx
E-prescribing Reduces Medical Errors
85% decrease
Kaushal et al. JGIM. 2010
%
of
Prescription
with
Error(s)

9. 11.50%
3.10%
6.80%
1.60%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
Non-timing errors Potential ADEs
Bar-coding reduces potential ADEs
41% decrease
Poon et al. NEJM. 2010
51% decrease

10. EHR and Quality Benefits (Contd.)
• Laboratory safety1
– Critical results notification: time to resolution 29%
shorter
• Smart monitoring2
– Remote monitoring in a 10-bed ICU decreased
mortality by 46-68%
• Hand-offs3
– Computerized sign-outs reduced adverse events
risk 5-fold
1. Kuperman et al. JAMIA 2010 | 2. Rosenfeld et al. Crit Care Med 2000 | 3. Petersen et
al Jt Comm Journal 1998

11. 1
0.7
0
0.2
0.4
0.6
0.8
1
1.2
Pre-EMR Post-EMR
Computerized Physician Order Entry
(CPOE): Inpatient Pediatric Mortality
20 % decrease
Longhurst et al. Pediatrics. 2010; 126; 14-21
Mean
Mortality
Rate

12. EHR’s Impact on Inpatient Outcomes
• Cross-sectional study of urban hospitals in Texas
• 41 / 72 hospitals
• Level of automation measured using a
questionnaire-based tool
• Higher automation scores associated with fewer
complications, lower mortality rates, lower costs
• 10% increase in automation score = 15%
decrease in adjusted odds of hospital deaths
Amarasingham et al. Arch Int Med. 2009:169:108-114

13. 35.1
84.2 85.1
64.8
74.2
53
48
74.2
93
32.7
90.1
87.6
78.6
65.8
51.3 52.9
90
30
40
50
60
70
80
90
100
Paper
EHR
3-13% increase
EHR and Ambulatory Care Quality
* p <0.001 Kern et al. JGIM. 2013

14. Impact of Patient Portals on Quality
• Systematic review – Nov. 2013
• Impact on
– Health outcomes - insufficient evidence
– Utilization and efficiency – mixed results
– Patient attitude / awareness – potential barrier
– Relatively few evaluation studies available yet
Goldzweig et al. Ann In Med. Nov. 2013

15. 2006 Systematic Review: Impact of HIT
• Impact on Quality
– Increased adherence to guideline-based care
– Enhanced disease surveillance
– Decreased medication errors
• Impact on Efficiency
– Decreased utilization e.g. redundant tests ordering
– Mixed results on physician time
• Cost
– Inconclusive data
Chaudhry et al. Ann Int Med. 2006: 144;742-752

16. 2006 Systematic Review (Contd.)
• Most data from 4 benchmark institutions
– Home-grown systems; highly customized
– Decades of iterating, improving EHR systems
– Local control, rapid improvement cycles
– Strong informatics departments
– Strong culture / expectation of EHR quality
improvement
• Raises concerns about generalizability of results
• Possibly, EHR impact is institution-dependent
Chaudhry et al. Ann Int Med. 2006: 144;742-752

17. Commercial / Vendor Systems
• Length of improvement cycles
• Little or no local control
• Relative immunity from consequences / “hold
harmless” clause
• No reliable / centralized way of reporting
users’ concerns / safety events.

18. Impact of EHR on Quality: Academic vs.
Non-academic hospitals
• Impact of EHR on six process measures
• Two had statistically significant improvements.
• Improvements were substantially greater in
academic hospitals vs. non-academic
– More sophisticated IT
– Different culture / leadership / priorities
– Different physician hospital relationship
– Different training model
• Possibly, EHR impact is context-dependent
McCullough et al. Health Affairs. 2010:29;647-654

19. 2012 Systematic Review
• Clinical decision support systems improved
process measures.
• Evidence for outcomes (clinical, economic,
workload) sparse.
• Positive results across diverse settings and
diverse systems!
Bright et al. Ann Int Med 2012:157;29-43

20. Office of the National Coordinator for Health IT review of 2007-2013 Health IT literature
Jones SS et al. Annals of Internal Medicine January 2014
Buntin et al. Health Affairs. 2011:30;464-471
Effect of MU functionality on quality,
safety, and efficiency

21. Value of IT investments: The VA
Experience
• Cumulative cost: $4 billion
• Benefits: $7.16 billion
– 65% or $4.6 billion – reducing unnecessary care
– 27% or $1.9 billion – eliminating redundancies
– Rest
• Reduced work
• Reduced operating expenses
• Estimated net benefit >3 billion
Byrne et al. Health Affairs 2010:29;629-638

23. EHR: Emerging Safety Concerns
“an unchecked proliferation of unproven medical
technology and sharp erosion of care standards.”

24. Unintended Consequences of HIT
“No innovation comes
without strings attached.
The more technologically
advanced an innovation,
the more likely its
introduction will produce
many consequences, both
anticipated and latent.”

25. Simulation Performance: CPOE
Metzger et al. Health Affairs 2010;29:655-653
Post-implementation or in-vivo
evaluation is important
Vendor Systems
% prevention of
“problem” orders

26. CPOE Facilitating Medication Errors
• Tertiary care teaching hospital in Pennsylvania
• Qualitative research: focus groups / interviews
of house officers
• 22 types of NEW errors
A. Information errors due to fragmentation of data
B. Human-machine interface flaws
Koppel et al. JAMA. 2005;293:1197-1203

27. 2.8
6.57
0
1
2
3
4
5
6
7
Pre-CPOE (13 months) Post-CPOE (5 months)
Increased Neonatal Mortality After
CPOE Implementation
Han et al. Pediatrics. 2005;116:1506-1512
Mean
Mortality
Rate

28. Increased Neonatal
Mortality….(Contd.)
• “Lost time” in care of critically ill children and
delays in time-sensitive therapies
– Order entry not allowed before patient physically
arrived and fully registered
• Reduced physician-nurse communication
• No visible order flagging
• Delays in medication dispensing and
administration – everything is computer-
dependent
• Too long to place orders
Han et al. Pediatrics. 2005;116:1506-1512

29. Alert Override / Fatigue
• Ambulatory care, 3000 prescribers1
– 90% of DDI alerts, 77 % of drug-allergy alerts
• 5 Ambulatory care practices2
– 90% of DDI and drug-allergy alerts
• Review article3
– 49% to 96% - override of drug alerts
1. Isac et al . Arch Int Med. 2009 | 2.Weingart et al. Arch Int Med. 2003 | 3. van der sijs
et al. JAMIA. 2006

30. EHR: Ethical and quality pitfalls
• Copying and pasting
• Ambiguities of authorship and timing
• Templated notes
• Prepopulated data
• Transformation of core purpose of EHR – from
information sharing for clinical care to
reimbursement / regulatory requirements
1. Bernat. Neurology 2013. Ethical and quality pitfalls in electronic health records.
2. Hirschtick. JAMA 2012. John Lenon’s elbow.
3. Layman. The Health Care Manager. 2008. Ethical issues and the electronic health record.

31. Physician Satisfaction with EHRs
• Physician dissatisfaction
with current EHRs
– Poor usability
– Time-consuming data
entry
– Less fulfilling work content
– Interference with face-
face care
RAND research report 2013

32. Technology meets humanity: “Bloody
Crossroads”

33. EHR and Physician-patient Communication
(“The Cost of Technology”)
Toll | JAMA June 2012 | The Cost of technology

34. People
Technology
(Hardware /
Software)
Processes
Organization
External
Environment
Socio-technical Model of HIT
Health IT and Patient Safety. Institute of Medicine. 2010

35. EHR User Experience

36. EHR’s Impact on Thinking
“Our writing equipment
takes part in the forming of
our thoughts.”
- Frederick Nietzsche

37. EHR’s Impact on Thinking
• EHR as “cognitive partner”
–Impacts our thinking patterns.
–Influences our decision making
–“Effects of” and “effects with”
technology
Horsky and Patel. J of Biomed Inf. 2005:38;264-266

38. EHR: Moving forward
• EHR user experience / usability must be
evaluated / addressed.
• Technology alone is not sufficient: workflow /
culture /environment are critical.
• Good implementation after thorough analysis
• User engagement
• Training
• Constant evaluation
• Understand and mitigate HIT-induced safety risks.
Mandl et al. NEJM. 2012:366;2240-2242

39. EHRs are essential for modern medicine.

40. Thank you
Abha Agrawal, MD, FACP
agrawal.abha@gmail.com