IDEAS home Printed from https://ideas.repec.org/p/bsl/wpaper/2018-14.html
   My bibliography  Save this paper

Estimating Survival Times Using Swiss Hospital Data

Author

Listed:
  • Kuhlmey, Florian

    () (University of Basel)

  • Minke, Matthias

    () (University of Basel)

Abstract

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
    as

    Download full text from publisher

    File URL: https://edoc.unibas.ch/64724/1/20180618101344_5b2769b860475.pdf
    Download Restriction: no

    More about this item

    Keywords

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bsl:wpaper:2018/14. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (WWZ). General contact details of provider: http://edirc.repec.org/data/wwzbsch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.