Flaws in mortality data. The hazards of ignoring comorbid disease

Sheldon Greenfield

JAMA · 1988 · 246 citations · 0 references

Concepts

TL;DR

Recent public releases of hospital mortality data have sparked debate over methods to identify poor-quality care. We examined variations among hospitals in patient characteristics known independently to affect the risk of adverse outcomes and focused on patient comorbidity, defined as the state of health at admission apart from the primary diagnosis. We analyzed data from 2,935 incident cancer patients treated in seven Southern California hospitals, assessing age, cancer stage, and comorbidity burden. Significant hospital variation in comorbidity burden—highest hospital 17.9% versus lowest 9.3%—correlates with high‑mortality outlier status, underscoring that ignoring comorbidity can misattribute quality differences. Published in JAMA 1988;260:2253‑2255.

Abstract

Recent public releases of hospital mortality data have sparked debate over methods to identify poor-quality care. We examined variations among hospitals in patient characteristics known independently to affect the risk of adverse outcomes and focused on patient comorbidity, defined as the state of health at admission apart from the primary diagnosis. Data from a study of 2935 incident cancer patients treated in seven Southern California hospitals revealed substantial variations among hospitals in age, cancer stage, and the burden of comorbid conditions. In the highest-ranked hospital, 17.9% of patients had high levels of comorbidity, compared with 9.3% in the lowest-ranked hospital. The three hospitals with the highest comorbidity were also identified as high-mortality outliers in a recent California report on hospital mortality rates. We conclude that comorbidity must be considered in any hospital quality assessment method based on patient outcome. If it is not considered, variations in referral and admission patterns may be misinterpreted as differences in hospital quality. (<i>JAMA</i>1988;260:2253-2255)