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How to Project Patient Persistency

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  • Ka Lok Lee
  • Peter Fader
  • Bruce Hardie

Abstract

Pharmaceutical companies face the problem of how to project the persistency patterns of patients who are taking their manufactured medications – i.e., how to determine the percentage of patients who will continue to refill a given prescription on a timely basis. The authors have developed a probability model with a well-grounded story for the dropout process. The model, which can be implemented in a simple Excel spreadsheet, provides remarkably accurate forecasts as well as other useful diagnostics about patient persistency. Copyright International Institute of Forecasters, 2007

Suggested Citation

  • Ka Lok Lee & Peter Fader & Bruce Hardie, 2007. "How to Project Patient Persistency," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 31-35, Fall.
    • Handle: RePEc:for:ijafaa:y:2007:i:8:p:31-35
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    Cited by:

    1. Hui Zhang & Tao Huang & Tao Yan, 2022. "A quantitative analysis of risk-sharing agreements with patient support programs for improving medication adherence," Health Care Management Science, Springer, vol. 25(2), pages 253-274, June.
    2. Bijmolt, T.H.A. & Bl, 2010. "Should they stay or should they go? Reactivation and termination of low-tier customers," Research Report 10008, University of Groningen, Research Institute SOM (Systems, Organisations and Management).

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