A comparison of hospital performance with non-ignorable missing covariates: an application to trauma care data

Trauma is a term used in medicine for describing physical injury. The prospective evaluation of the care of injured patients aims to improve the management of a trauma system and acts as an ongoing audit of trauma care. One of the principal techniques used to evaluate the effectiveness of trauma care at different hospitals is through a comparative outcome analysis. In such an analysis, a national 'league table' can be compiled to determine which hospitals are better at managing trauma care. One of the problems with the conventional analysis is that key covariates for measuring physiological injury can often be missing. It is also hypothesized that this missingness is not missing at random (NMAR). We describe the methods used to assess the performance of hospitals in a trauma setting and implement the method of weights for generalized linear models to account for the missing covariate data, when we suspect the missing data mechanism is NMAR using a Monte Carlo EM algorithm. Through simulation work and application to the trauma data we demonstrate the affect the missing covariate data can have on the performance of hospitals and how the conclusions we draw from the analysis can differ. We highlight the differences in hospital performance and the ranking of hospitals.