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Estimating Survival Times Using Swiss Hospital Data


  • Kuhlmey, Florian

    () (University of Basel)

  • Minke, Matthias

    () (University of Basel)


We compare and evaluate two different approaches to estimate overall survival curvesfrom censored data of recurrent events: (1) standard survival time analysis, and (2) a multistate framework that explicitly estimates the mortality rate during censored periods. With both models, we estimate disease-specific survival curves with data from the Swiss Federal Statistical Office's medical statistics on hospitals (MedStat). Using cancer registry data as a benchmark for overall survival, we find that the accuracy of survival time estimates based on the multistate model are not superior to the simpler single-risk model. Although the computationally demanding multistate model is less accurate in predicting survival times, it may nevertheless be useful if intermediate transitions are the targeted issues.

Suggested Citation

  • Kuhlmey, Florian & Minke, Matthias, 2018. "Estimating Survival Times Using Swiss Hospital Data," Working papers 2018/14, Faculty of Business and Economics - University of Basel.
  • Handle: RePEc:bsl:wpaper:2018/14

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    More about this item


    Survival analysis; multistate-model; data simulation; hospital discharge data;

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior


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