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Case-mix adjusted hospital mortality is a poor proxy for preventable mortality: a modelling study

Risk-adjustment schemes are used to monitor hospital performance, on the assumption that excess mortality not explained by case mix is largely attributable to suboptimal care. We have developed a model to estimate the proportion of the variation in standardised mortality ratios (SMRs) that can be ac...

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Detalles Bibliográficos
Autores principales: Girling, Alan J, Hofer, Timothy P, Wu, Jianhua, Chilton, Peter J, Nicholl, Jonathan P, Mohammed, Mohammed A, Lilford, Richard J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3551201/
https://www.ncbi.nlm.nih.gov/pubmed/23069860
http://dx.doi.org/10.1136/bmjqs-2012-001202
Descripción
Sumario:Risk-adjustment schemes are used to monitor hospital performance, on the assumption that excess mortality not explained by case mix is largely attributable to suboptimal care. We have developed a model to estimate the proportion of the variation in standardised mortality ratios (SMRs) that can be accounted for by variation in preventable mortality. The model was populated with values from the literature to estimate a predictive value of the SMR in this context—specifically the proportion of those hospitals with SMRs among the highest 2.5% that fall among the worst 2.5% for preventable mortality. The extent to which SMRs reflect preventable mortality rates is highly sensitive to the proportion of deaths that are preventable. If 6% of hospital deaths are preventable (as suggested by the literature), the predictive value of the SMR can be no greater than 9%. This value could rise to 30%, if 15% of deaths are preventable. The model offers a ‘reality check’ for case mix adjustment schemes designed to isolate the preventable component of any outcome rate.