A new standardized mortality ratio method for hospital quality evaluation

Abstract

Evaluation of hospital quality is of great significance for the promotion of the development of medical care. Hospital standardized mortality ratio (HSMR) is the ratio of hospital observed mortality to expected mortality (O/E ratio) and is an important indicator for the evaluation of hospital performance. Given the importance of HSMR, accurate estimation of HSMR confidence intervals is essential. All existing methods assume that the distributions of the O/E ratios are close to a normal distribution. However, this assumption is not reasonable. In this article, we propose a new method for calculating the HSMR confidence intervals. We derive the confidence intervals for the O/E ratios by calculating the confidence intervals of log(O/E). Then, we use the coverage probability of the confidence intervals to compare the performance of our method with the performance of existing methods. In the scenarios with different true relative risks, if the mortality rate is less than or equal to 1%, the bias of our method is substantially lower than that of the existing methods. The simulation results show that our method provides a more accurate estimate of the confidence intervals of the O/E ratios in the case of low mortality rates than that provided by the existing methods.