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An econometric approach to aggregating multiple cardiovascular outcomes in German hospitals.

Angela MeggiolaroCarl Rudolf BlankartTom StargardtJonas Schreyögg
Published in: The European journal of health economics : HEPAC : health economics in prevention and care (2022)
The proposed approach is a new method to aggregate single hospital quality outcomes using objective, precision-based weights. Likelihood-based accelerated failure time models make use of existing data more efficiently compared to widely used models relying on dichotomized data. The main advantage of the variance-based weights approach is that the extent to which an indicator contributes to the aggregate index depends on the amount of its variance.
Keyphrases
  • electronic health record
  • healthcare
  • big data
  • type diabetes
  • data analysis
  • machine learning