Measuring standardised mortality ratios of hospitals: Challenges and recommendations

Objectives of this thesis

This thesis has the following objectives:
- To study the effects of ‘referral bias’ and ‘casemix and coding issues’
on the current Dutch HSMR calculation.
- To identify potential adjustments in the estimation of the HSMR to
improve its validity as a performance indicator.

Outline of this thesis

The thesis starts with investigating the theoretical method underlying the
calculation of the HSMR, the so-called indirect standardisation method. In
chapter 2, the indirect standardisation method is compared with the direct
standardisation method. Also, pitfalls of HSMR resulting from the indirect
standardisation method are discussed, and recommendations are given to
reduce the shortcomings of this method.
Subsequently, the thesis investigates potential modifications of the currently
used model for HSMR calculation. To adjust for casemix differences
between hospitals, parameters of comorbidities are included in the model
underlying the HSMR calculation. In chapter 3, the commonly used Charlson
comorbidity measure is compared with the Elixhauser comorbidity measure.
Discriminative performance of the casemix correction models based on these
two comorbidity measures is compared and their effects on the HSMRs of
individual hospitals are explored.
The Dutch HSMR is currently based on in-hospital mortality. However,
discharge patterns, average length of hospital stay, and transfers all affect inhospital
mortality. In chapter 4, effects of the inclusion of post-discharge
mortality on HSMRs are compared with those of in-hospital mortality.
In the final part of the thesis we zoom in onto the mortality ratios of specific
patient populations, rather than that of an entire hospital population. In
chapter 5, the focus is on SMRs of specific diagnosis groups requiring specialised
care offered by specialised hospitals. The SMRs of specialised and nonspecialised
hospitals are compared and the influence of referral patterns on
SMRs is investigated.
Current HSMR calculation is based on administrative databases and said to
lack important clinical predictors. In chapter 6, the casemix adjustment model
for cardiac surgery patients, based on an administrative database, is compared
with the validated clinical EuroSCORE prediction model, based on a clinical database. Also influences of the two models on eventual SMRs are compared.
Finally, in chapter 7, the results and implications of this thesis are summarised and discussed together with insights and recommendations to improve the validity and utility of HSMRs.