Abstract
Objective. To determine if a widely used proprietary risk-adjustment system, APR-DRGs, misadjusts for severity of illness and misclassifies provider performance. Data Sources. (1) Discharge abstracts for 116,174 noninstitutionalized adults with acute myocardial infarction (AMI) admitted to nonfederal California hospitals in 1991-1993; (2) inpatient medical records for a stratified probability sample of 974 patients with AMIs admitted to 30 California hospitals between July 31, 1990 and May 31, 1991. Study Design. Using the 1991-1993 data set, we evaluated the predictive performance of APR-DRGs Version 12. Using the 1990/1991 validation sample, we assessed the effect of assigning APR-DRGs based on different sources of ICD- 9-CM data. Data Collection/Extraction Methods. Trained, blinded coders reabstracted all ICD-9-CM diagnoses and procedures, and established the timing of each diagnosis. APR-DRG Risk of Mortality and Severity of Illness classes were assigned based on (1) all hospital-reported diagnoses, (2) all reabstracted diagnoses, and (3) reabstracted diagnoses present at admission. The outcome variables were 30-day mortality in the 1991-1993 data set and 30- day inpatient mortality in the 1990/1991 validation sample. Principal Findings. The APR-DRG Risk of Mortality class was a strong predictor of death (c = .831-.847), but was further enhanced by adding age and sex. Reabstracting diagnoses improved the apparent performance of APR-DRGs (c = .93 versus c = .87), while using only the diagnoses present at admission decreased apparent performance (c = .74). Reabstracting diagnoses had less effect on hospitals' expected mortality rates (r = .83-.85) than using diagnoses present at admission instead of all reabstracted diagnoses (r = .72-.77). There was fair agreement in classifying hospital performance based on these three sets of diagnostic data (κ = 0.35-0.38). Conclusions. The APR-DRG Risk of Mortality system is a powerful risk-adjustment tool, largely because it includes all relevant diagnoses, regardless of timing. Although some late diagnoses may not be preventable, APR-DRGs appear suitable only if one assumes that none is preventable.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1469-1489 |
| Number of pages | 21 |
| Journal | Health Services Research |
| Volume | 34 |
| Issue number | 7 |
| State | Published - Mar 2000 |
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Keywords
- Acute myocardial infarction
- APR-DRG
- Hospital performance
- Report card
- Risk adjustment
- Risk of mortality
- Severity of illness
ASJC Scopus subject areas
- Nursing(all)
- Health(social science)
- Health Professions(all)
- Health Policy
Cite this
Risk-adjusting acute myocardial infarction mortality : Are APR-DRGs the right tool? / Romano, Patrick S; Chan, Benjamin K.
In: Health Services Research, Vol. 34, No. 7, 03.2000, p. 1469-1489.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Risk-adjusting acute myocardial infarction mortality
T2 - Are APR-DRGs the right tool?
AU - Romano, Patrick S
AU - Chan, Benjamin K.
PY - 2000/3
Y1 - 2000/3
N2 - Objective. To determine if a widely used proprietary risk-adjustment system, APR-DRGs, misadjusts for severity of illness and misclassifies provider performance. Data Sources. (1) Discharge abstracts for 116,174 noninstitutionalized adults with acute myocardial infarction (AMI) admitted to nonfederal California hospitals in 1991-1993; (2) inpatient medical records for a stratified probability sample of 974 patients with AMIs admitted to 30 California hospitals between July 31, 1990 and May 31, 1991. Study Design. Using the 1991-1993 data set, we evaluated the predictive performance of APR-DRGs Version 12. Using the 1990/1991 validation sample, we assessed the effect of assigning APR-DRGs based on different sources of ICD- 9-CM data. Data Collection/Extraction Methods. Trained, blinded coders reabstracted all ICD-9-CM diagnoses and procedures, and established the timing of each diagnosis. APR-DRG Risk of Mortality and Severity of Illness classes were assigned based on (1) all hospital-reported diagnoses, (2) all reabstracted diagnoses, and (3) reabstracted diagnoses present at admission. The outcome variables were 30-day mortality in the 1991-1993 data set and 30- day inpatient mortality in the 1990/1991 validation sample. Principal Findings. The APR-DRG Risk of Mortality class was a strong predictor of death (c = .831-.847), but was further enhanced by adding age and sex. Reabstracting diagnoses improved the apparent performance of APR-DRGs (c = .93 versus c = .87), while using only the diagnoses present at admission decreased apparent performance (c = .74). Reabstracting diagnoses had less effect on hospitals' expected mortality rates (r = .83-.85) than using diagnoses present at admission instead of all reabstracted diagnoses (r = .72-.77). There was fair agreement in classifying hospital performance based on these three sets of diagnostic data (κ = 0.35-0.38). Conclusions. The APR-DRG Risk of Mortality system is a powerful risk-adjustment tool, largely because it includes all relevant diagnoses, regardless of timing. Although some late diagnoses may not be preventable, APR-DRGs appear suitable only if one assumes that none is preventable.
AB - Objective. To determine if a widely used proprietary risk-adjustment system, APR-DRGs, misadjusts for severity of illness and misclassifies provider performance. Data Sources. (1) Discharge abstracts for 116,174 noninstitutionalized adults with acute myocardial infarction (AMI) admitted to nonfederal California hospitals in 1991-1993; (2) inpatient medical records for a stratified probability sample of 974 patients with AMIs admitted to 30 California hospitals between July 31, 1990 and May 31, 1991. Study Design. Using the 1991-1993 data set, we evaluated the predictive performance of APR-DRGs Version 12. Using the 1990/1991 validation sample, we assessed the effect of assigning APR-DRGs based on different sources of ICD- 9-CM data. Data Collection/Extraction Methods. Trained, blinded coders reabstracted all ICD-9-CM diagnoses and procedures, and established the timing of each diagnosis. APR-DRG Risk of Mortality and Severity of Illness classes were assigned based on (1) all hospital-reported diagnoses, (2) all reabstracted diagnoses, and (3) reabstracted diagnoses present at admission. The outcome variables were 30-day mortality in the 1991-1993 data set and 30- day inpatient mortality in the 1990/1991 validation sample. Principal Findings. The APR-DRG Risk of Mortality class was a strong predictor of death (c = .831-.847), but was further enhanced by adding age and sex. Reabstracting diagnoses improved the apparent performance of APR-DRGs (c = .93 versus c = .87), while using only the diagnoses present at admission decreased apparent performance (c = .74). Reabstracting diagnoses had less effect on hospitals' expected mortality rates (r = .83-.85) than using diagnoses present at admission instead of all reabstracted diagnoses (r = .72-.77). There was fair agreement in classifying hospital performance based on these three sets of diagnostic data (κ = 0.35-0.38). Conclusions. The APR-DRG Risk of Mortality system is a powerful risk-adjustment tool, largely because it includes all relevant diagnoses, regardless of timing. Although some late diagnoses may not be preventable, APR-DRGs appear suitable only if one assumes that none is preventable.
KW - Acute myocardial infarction
KW - APR-DRG
KW - Hospital performance
KW - Report card
KW - Risk adjustment
KW - Risk of mortality
KW - Severity of illness
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UR - http://www.scopus.com/inward/citedby.url?scp=0034090810&partnerID=8YFLogxK
M3 - Article
VL - 34
SP - 1469
EP - 1489
JO - Health Services Research
JF - Health Services Research
SN - 0017-9124
IS - 7
ER -