The Autopsy as a Performance Measurement Tool—Diagnostic Discrepancies and UnresolvedClinical Questions

Abstract

Abstract Objective.—To develop a multi-institutional reference database for quality improvement purposes using the autopsy to define clinical diagnostic discrepancies and resolve clinical questions. Design.—Using the College of American Pathologists Q{-}Probes format, institutions prospectively assessed a maximum of 15 consecutive autopsies each, excluding forensic cases and stillborn infants, conducted over a 6-month period. They documented answers to clinical questions provided at autopsy and classified unexpected disease diagnoses according to a standardized system. Setting and Participants.—Hospital-based autopsies performed at 248 institutions participating in the 1993 College of American Pathologists Q-Probes Quality Improvement Program. Main Outcome Measures.—Percentages of clinical questions resolved by the autopsy and percentage of autopsies with unexpected findings of graded clinical impact. Results.—In the aggregate database of 6427 questions from 2479 autopsies, overall 93.0% were answered by the autopsy. The 3 most common question categories were (1) identify pathology to account for clinical signs or symptoms (28.0%); (2) establish the cause of death (21.0%); and (3) confirm a clinical diagnosis (19.0%). At least one major unexpected disease finding that contributed to the patient’s death was discovered in 39.7% of the total number of autopsies. There were no differences in the percentages of autopsies with these major unexpected findings when the data were stratified by institutional demographics or decedent characteristics. Conclusion.—This multi-institutional study underscores the clinical relevance of postmortem examination in current medical practice by consistently providing answers to unresolved clinical questions and frequently revealing major unexpected findings that contributed to the patient’s death. It is our strong belief that this postmortem-derived clinicopathologic information is a key indicator of effectiveness of care. Integration of this information into institutional quality improvement programs will improve system processes and clinician performance.