Inter-hospital comparison of mortality rates

Objective, To compare crude and adjusted in-hospital mortality rates after prostatectomy between hospitals using routinely collected hospital discharg e data and to illustrate the value and limitations of using comparative mor tality rates as a surrogate measure of quality of care. Methods. Mortality rates for non-teaching hospitals (n = 21) were compared to a single notional group of teaching hospitals. Patients' age, disease (c omorbidity), length of stay, emergency admission, and hospital location wer e identified using ICD-9-CM coded Victorian hospital morbidity data from pu blic hospitals collected between 1987/88 and 1994/95. Comparisons between h ospitals were based on crude and adjusted odds ratios (OR) and 95% confiden ce intervals (CI) derived using univariate and multivariate logistic regres sion. Model tit was evaluated using receiver operating characteristic curve i.e. c statistic, Somer's D, Tau-a, and R-2. Results. The overall crude mortality rates between hospitals achieved borde rline significance (chi(2) = 31.31; d.f. = 21, P = 0.06); these differences were no longer significant after adjustment (chi(2) = 25.68; P = 0.21). On crude analysis of mortality rates, four hospitals were initially identifie d as 'low' outlier hospitals; after adjustment, none of these remained outs ide the 95% CI, whereas a new hospital emerged as a 'high' outlier (OR = 4. 56; P = 0.05). The adjusted ORs between hospitals compared to the reference varied from 0.21 to 5.54, ratio = 26.38. The model provided a good tit to the data (c = 0.89; Somer's D = 0.78; Tau-a = 0.013; R-2 = 0.24). Conclusions. Regression adjustment of routinely collected data on prostatec tomy from the Victorian Inpatient Minimum Database reduced variance associa ted with age and correlates of illness severity. Reduction of confounding i n this way is a move in the direction of exploring differences in quality o f care between hospitals. Collection of such information over time, togethe r with refinement of data collection would provide indicators of change in quality of care that could be explored in more detail as appropriate in the clinical setting.