Risk-adjusting acute myocardial infarction mortality

Are APR-DRGs the right tool?

Patrick S Romano, Benjamin K. Chan

Research output: Contribution to journalArticle

64 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)1469-1489
Number of pages21
JournalHealth Services Research
Volume34
Issue number7
StatePublished - Mar 2000

Fingerprint

Diagnosis-Related Groups
mortality
Myocardial Infarction
Mortality
Risk Adjustment
risk adjustment
International Classification of Diseases
performance
Inpatients
present
illness
Sampling Studies
Information Storage and Retrieval
Delayed Diagnosis
Hospital Mortality
Medical Records
diagnostic

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 journalArticle

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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.

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