Various potential measures of quality of care are being used to differentiate hospitals. Last year, on the basis of diagnostic and demographic data, the Health Care Financing Administration identified hospitals in which the actual death rate differed from the predicted rate. We have developed a similar model. To understand why there are high-outlier hospitals (in which the actual death rate is above the predicted one) and low-outlier hospitals (in which the actual death rate is below the predicted one), we reviewed 378 medical records from 12 outlier hospitals treating patients with one of three conditions: cerebrovascular accident, myocardial infarction, and pneumonia. After adjustment for the severity of illness, the death rate in the high outliers exceeded that predicted from the severity of illness alone by 3 to 10 percent, and in the low outliers, the actual death rate fell short of the severity-adjusted predictions by 10 to 15 percent (P less than 0.01). Reviews of the process of care using 125 criteria revealed no differences between the high and low outliers. However, detailed reviews by physicians of the records of patients who died during hospitalization revealed a higher rate of preventable deaths in the high outliers than in the low outliers. For the three conditions studied, we project that 5.7 percent of a standard cohort of patients admitted to the high-outlier hospitals would have preventable deaths, as compared with 3.2 percent of patients admitted to the low-outlier hospitals (P less than 0.05). A meaningful comparison of hospital death rates requires adjustment for severity of illness. Our findings indicate that high-outlier hospitals care for sicker patients. However, these same hospitals or their medical staffs may also provide poorer care. Our results need confirmation before death-rate models can be used to screen hospitals.