Risk adjustment methods can affect perceptions of outcomes

UMMS Affiliation

Department of Quantitative Health Sciences

Publication Date


Document Type



Adolescent; Adult; Aged; Aged, 80 and over; *Data Interpretation, Statistical; Diagnosis-Related Groups; Hospital Mortality; Humans; Logistic Models; Medicaid; Medicare; Middle Aged; *Models, Statistical; Myocardial Infarction; *Outcome Assessment (Health Care); Predictive Value of Tests; Risk Factors; *Severity of Illness Index; United States


Biostatistics | Epidemiology | Health Services Research


When comparing outcomes of medical care, it is essential to adjust for patient risk, including severity of illness. A variety of severity measures exist, but perceptions of outcomes may differ depending on how severity is defined. We used two severity-adjustment approaches to demonstrate that comparisons of outcomes across subgroups of patients can vary dramatically depending on how severity is assessed. We studied two approaches: model 1 was the admission MedisGroups score; model 2 was computed from age and 12 chronic conditions defined by diagnosis codes. Although common summary measures of model performance (R-squared and C) both suggested that model 1 is a better predictor of in-hospital death than model 2, the weaker model consistently produced more accurate expectations by payer class and age group. Using model 1 for severity adjustment suggested that Medicare patients did substantially worse than expected and Medicaid patients substantially better. In contrast, use of model 2 found Medicare patients doing as expected, but Medicaid patients faring poorly.


Am J Med Qual. 1994 Summer;9(2):43-8. Link to article on publisher's site

Journal/Book/Conference Title

American journal of medical quality : the official journal of the American College of Medical Quality

PubMed ID


Related Resources

Link to Article in PubMed