The impact of management practices on relative patient mortality: Evidence from public hospitals

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A small, but growing, body of empirical evidence shows that the material and persistent variation in many aspects of the performance of healthcare organisations can be related to variation in their management practices. This study uses public data on hospital patient mortality outcomes, the Summary Hospital-level Mortality Indicator (SHMI) to extend this programme of research. We assemble a five-year dataset combining SHMI with potential confounding variables for all English NHS non-specialist acute hospital trusts. The large number of providers working within a common system provides a powerful environment for such investigations. We find considerable variation in SHMI between trusts and a high degree of persistence of high- or low performance. This variation is associated with a composite metric for management practices based on the NHS National Staff Survey. We then use a machine learning technique to suggest potential clusters of individual management practices related to patient mortality performance and test some of these using traditional multivariate regression. The results support the hypothesis that such clusters do matter for patient mortality, and so we conclude that any systematic effort at improving patient mortality should consider adopting an optimal cluster of management practices.
Original languageEnglish
Pages (from-to)240-250
Number of pages11
JournalHealth Services Management Research
Issue number4
Publication statusPublished - Nov 2022


  • hospital performance
  • machine learning
  • management practices
  • mortality
  • panel data analysis
  • quality


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