title: Predicting in-hospital mortality. The importance of functional status information.
abstract: Monitoring risk-adjusted outcomes is the centerpiece of efforts to ensure health care quality. Because data collection is expensive, questions arise concerning what information is essential to adjust for risk. This investigation used retrospective analysis of existing, computerized clinical databases containing laboratory test results, information on chronic coexisting conditions, and nursing evaluations of functional status to predict in-hospital mortality. We studied persons admitted to one tertiary teaching hospital between 1987 and 1992 for cerebrovascular disease or pneumonia. Predictive models for each of the conditions were developed using logistic regression; the results were validated with split samples. We compared the predictive value of the nursing functional status assessments and the clinical laboratory data. For each study condition, the functional status data had as much prognostic information as the laboratory data. Specifically, a nurse's report that a patient required total assistance for bathing was the best single predictor of in-hospital mortality in the models for patients with either cerebrovascular disease or pneumonia. If hospitals admit patients with different levels of functional impairment, it is important to account for these differences before comparing outcomes across facilities. Assessments of functional status are a simple, inexpensive measure that may have considerable value.
authors.affiliation: Department of Medicine, Harvard Medical School, Boston, MA, USA.
authors.forename: R B
authors.initials: RB
authors.lastname: Davis
authors.forename: L I
authors.initials: LI
authors.lastname: Iezzoni
authors.forename: R S
authors.initials: RS
authors.lastname: Phillips
authors.forename: P
authors.initials: P
authors.lastname: Reiley
authors.forename: G A
authors.initials: GA
authors.lastname: Coffman
authors.forename: C
authors.initials: C
authors.lastname: Safran
mesh_terms: D000203:Activities of Daily Living; D000328:Adult; D001900:Boston; D002561:Cerebrovascular Disorders / Q000097:blood / Q000145:classification / Q000401:mortality; D002908:Chronic Disease; D019411:Clinical Laboratory Techniques; D005260:Female; D017052:Hospital Mortality; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009730:Nursing Assessment; D011014:Pneumonia / Q000097:blood / Q000145:classification / Q000401:mortality; D011336:Probability; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index