EMRs
Hospital EMR Use and
Performance
• Use
• Expected Benefits
• Barriers to Implementation
Abby Swanson Kazley
Medical University of South Carolina
Academy of Health Annual Research Meeting
June 5, 2007
The Promise of EMRs in the
United States
• Medicals errors often lead to the escalation of
health care costs while decreasing the quality of
care (Zwillich 2005)
• Questions of duplication and appropriateness of
health care services
• Geographic variation in care may decrease with
standardized clinical protocol (Hannan 1999)
• Natural Disasters such as Hurricane Katrina
Hospital EMR Use
• HIMSS Definition
– “Comprehensive database system used to
store and access patients’ health care
information electronically. The computerbased patient record replaces the paper
medical record as the primary source of
information for health care meeting all clinical,
legal, and administrative requirements…”
• Automated, Contracted, or Not Automated
Theoretical Framework
• Donabedian’s Structure, Process,
Outcome Model
Structure
(EMR
adoption
and years
of use)
Overall
Process
(Efficiency
as
measured
through
DEA
score)
Outcome
(Quality)
Methods
• Unit of analysis: Individual acute care hospital
• Population: all general medical and surgical acute
care non-federal hospitals in the United States
• Includes 4,606 hospitals.
• Of these, 479 hospitals used EMRs in 2004
• There is some limitation with regard to quality
comparisons based on the number of stable
measures in the data. For this analysis, n=2,891.
• Observation takes place in 2004 for this
retrospective cross sectional study
• Bivariate Probit with Marginal Effects
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Hospital Performance
Quality Measures
• Efficiency
Condition
– Data Envelopment Analysis (DEA)
– CRS input oriented model
Measures
Acute Myocardial Infarction
Use of aspirin within 24 hours of arrival at hospital
Use of aspirin at discharge
Use of beta-blockers within 24 hours of hospital admission
• Quality
Use of beta-blockers at hospital discharge
– Hospital Quality Alliance data (2004)
– 10 process measures of 3 clinical conditions
Use of angiotensin-converting-enzyme inhibitor
Congestive Heart Failure
Assessment of left ventricular function
Use of angiotensin-converting-enzyme inhibitor
Pneumonia
Time of antibiotic therapy
Availability of pneumoncoccal vaccine
Assessment of Oxygenation
Performance Classification
Scheme
Hospitals with EMRs
Quality
Quality
Low
High
Total
Low
High
Total
Efficiency Low
989
1017
2,006
Efficiency Low
85 (24.4%)
135 (38.8%) 220 (63.2%)
High
391
494
885
High
50 (14.4%)
78 (22.4%)
Total
1380
1511
2,891
Total
135 (38.8%)
213 (61.2%) 348 (100.0%)
128 (36.8%)
Chi-square(1d.f.)=6.456 p<.05
[95% Conf. Interval]
Efficiency
Model
+ teachingStatus + PayerMix + CaseMix + error
Lower
Upper
EMR
0.095
-0.060
Bed Size
0.000
0.000
0.000
Teaching Status
-0.014
-0.216
0.188
-2.931
-1.070
Payer Mix
Biprobit (efficiency) = EMR + Size + Nonprofit + Public + SystemMembership
Coefficient
-1.466***'
0.250
Non-profit
-0.022
-0.173
0.128
Public
-0.050
-0.239
0.139
1.100***
0.841
1.136
Case Mix
System Member
Constant
0.078
-0.035
0.190
-1.007**
-1.670
-0.347
Quality
Biprobit (quality ) = EMR + Size + Nonprofit + Public + SystemMembership
+ teachingStatus + PayerMix + CaseMix + error
EMR
0.178*
0.027
0.328
Bed Size
0.000
-0.001
0.000
Teaching Status
0.309**
-0.618
-0.104
Payer Mix
-0.643**
-1.285
-0.269
Non-profit
0.413***
0.271
0.555
Public
0.239**
0.062
0.415
Case Mix
.644***
0.390
0.898
System Member
0.077
-0.028
0.181
Constant
-0.087
-0.735
0.562
Log Likelihood=-3580.786 *** p<.001, ** p<.01, * p<.05
Wald chi2(16)=386 13
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Marginal Effects
Implications and Conclusions
Quality
Efficiency
Low
High
Low
(-)
NS
High
NS
(+)
• EMRs are associated with greater quality
of care in hospitals
• There is no clear relationship between
EMR use and efficiency performance in
hospitals
• EMRs may influence the structure,
process, and outcomes of care
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