Hospital EMR Use and
Performance
Abby Swanson Kazley
Medical University of South Carolina
Academy of Health Annual Research Meeting
June 5, 2007
EMRs
• Use
• Expected Benefits
• Barriers to Implementation
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
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)
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
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
Hospital Performance
• Efficiency
– Data Envelopment Analysis (DEA)
– CRS input oriented model
• Quality
– Hospital Quality Alliance data (2004)
– 10 process measures of 3 clinical conditions
Quality Measures
Condition
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
Use of beta-blockers at hospital discharge
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
Quality
Low
High
Total
Efficiency Low
989
1017
2,006
High
391
494
885
Total
1380
1511
2,891
Chi-square(1d.f.)=6.456 p<.05
Hospitals with EMRs
Quality
Low
High
Total
Efficiency Low
85 (24.4%)
135 (38.8%) 220 (63.2%)
High
50 (14.4%)
78 (22.4%)
Total
135 (38.8%)
213 (61.2%) 348 (100.0%)
128 (36.8%)
Model
Biprobit (efficiency )  EMR  Size  Nonprofit  Public  SystemMembership
 teachingStatus  PayerMix  CaseMix  error
Biprobit (quality )  EMR  Size  Nonprofit  Public  SystemMembership
 teachingStatus  PayerMix  CaseMix  error
[95% Conf. Interval]
Efficiency
Coefficient
Lower
Upper
EMR
0.095
-0.060
0.250
Bed Size
0.000
0.000
0.000
Teaching Status
-0.014
-0.216
0.188
Payer Mix
-1.466***'
-2.931
-1.070
Non-profit
-0.022
-0.173
0.128
Public
-0.050
-0.239
0.139
1.100***
0.841
1.136
0.078
-0.035
0.190
-1.007**
-1.670
-0.347
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
Case Mix
System Member
Constant
Quality
Log Likelihood=-3580.786 *** p<.001, ** p<.01, * p<.05
Marginal Effects
Quality
Efficiency
Low
High
Low
(-)
NS
High
NS
(+)
Implications and Conclusions
• 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