PREDICTING IN-HOSPITAL MORTALITY - THE IMPORTANCE OF FUNCTIONAL STATUS INFORMATION

Monitoring risk-adjusted outcomes is the centerpiece of efforts to ens ure health care quality, Because data collection is expensive, questio ns arise concerning what information is essential to adjust for risk. This investigation used retrospective analysis of existing, computeriz ed clinical databases containing laboratory test results, information on chronic coexisting conditions, and nursing evaluations of functiona l status to predict in-hospital mortality. We studied persons admitted to one tertiary teaching hospital between 1987 and 1992 for cerebrova scular disease or pneumonia. Predictive models for each of the conditi ons were developed using logistic regression; the results were validat ed with split samples. We compared the predictive value of the nursing functional status assessments and the clinical laboratory data. For e ach study condition, the functional status data had as much prognostic information as the laboratory data. Specifically, a nurse's report th at a patient required total assistance for bathing was the best single predictor of in-hospital mortality in the models for patients with ei ther cerebrovascular disease or pneumonia. If hospitals admit patients with different levels of functional impairment, it is important to ac count for these differences before comparing outcomes across facilitie s. Assessments of functional status are a simple, inexpensive measure that may have considerable value.