Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission

Wim F Van Den Bosch,Cordula Wagner,Johannes C Kelder

doi:10.1186/1472-6963-11-57

Abstract

BackgroundCasemix adjusted in-hospital mortality is one of the measures used to improve quality of care. The adjustment currently used does not take into account the effects of readmission, because reliable data on readmission is not readily available through routinely collected databases. We have studied the impact of readmissions by linking admissions of the same patient, and as a result were able to compare hospital mortality among frequently, as opposed to, non-frequently readmitted patients. We also formulated a method to adjust for readmission for the calculation of hospital standardised mortality ratios (HSMRs).MethodsWe conducted a longitudinal retrospective analysis of routinely collected hospital data of six large non-university teaching hospitals in the Netherlands with casemix adjusted standardised mortality ratios ranging from 65 to 114 and a combined value of 93 over a five-year period. Participants concerned 240662 patients admitted 418566 times in total during the years 2003 - 2007. Predicted deaths by the HSMR model 2008 over a five-year period were compared with observed deaths.ResultsNumbers of readmissions per patient differ substantially between the six hospitals, up to a factor of 2. A large interaction was found between numbers of admissions per patient and HSMR-predicted risks. Observed deaths for frequently admitted patients were significantly lower than HSMR-predicted deaths, which could be explained by uncorrected factors surrounding readmissions.ConclusionsPatients admitted more frequently show lower risks of dying on average per admission. This decline in risk is only partly detected by the current HSMR. Comparing frequently admitted patients to non-frequently admitted patients commits the constant risk fallacy and potentially lowers HSMRs of hospitals treating many frequently admitted patients and increases HSMRs of hospitals treating many non-frequently admitted patients. This misleading effect can only be demonstrated by an analysis over a prolonged period, but occurs, in effect, every day of the year. This finding is relevant for all countries where hospitals use HSMR for monitoring and improving hospital performance. The use of 'admission frequency' as additional adjustment variable may provide a more accurate HSMR.

Highlights

Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care
Does an admission of a patient mean the same thing to one hospital as it means to another hospital admitting ‘the same patient’? attuned to our study: are the risk conditions the same for a patient being admitted only once compared to admissions of a frequently admitted patient? In order to analyse this, we addressed the following research questions using hospital standardised mortality ratios (HSMRs) from six Dutch hospitals: 1. Are there substantial differences in the numbers of readmissions within a given time period between the six hospitals? 2
Numerous examples alike became available in our study, for example: we found 174 patients in hospital D, each of whom contributed more than 1 predicted death to the denominator of the HSMR due to various readmissions

Summary

Introduction

Casemix adjusted in-hospital mortality is one of the measures used to improve quality of care. In various countries in the world, risk adjusted in-hospital mortality ratios are currently calculated using routinely collected data. One of the findings of this Dutch study [10], not being addressed in [4], showed large differences between the hospitals with respect to numbers of readmissions per patient, if measured over a prolonged period of time. Using a limited part of the patient’s admission history, would, on average, not make a difference to the HSMR of that hospital This may suggest that adjustment for readmission would not make sense. Using this method, we question whether a period of one-year is sufficiently long to embrace all the effects of readmission and whether all the risk conditions surrounding readmissions can be properly addressed. In our publication we will share how differences in numbers of previous admissions made an impact upon the HSMRs of the hospitals and what can be done to improve the HSMR model used

Methods

Results

Conclusion