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Related Experiment Videos

Evaluating disease management program effectiveness: an introduction to survival analysis.

Ariel Linden1, John L Adams, Nancy Roberts

  • 1Linden Consulting Group, Portland, Oregon 97124, USA. ariellinden@yahoo.com

Disease Management : DM
|January 27, 2005
PubMed
Summary

The total population approach for evaluating disease management (DM) programs is limited. Survival analysis offers a more robust method, accounting for censored data and confounding variables for better program effectiveness evaluation.

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Area of Science:

  • Biostatistics
  • Health Services Research
  • Epidemiology

Background:

  • The total population approach is the standard for evaluating disease management (DM) program effectiveness.
  • This method, a basic pretest-posttest design, lacks a control group, introducing potential bias and confounding factors.
  • These limitations hinder accurate assessment of program impact on patient outcomes.

Purpose of the Study:

  • To review survival analysis as a superior alternative to the total population approach for DM program evaluation.
  • To highlight the advantages of survival analysis in handling censored data and incorporating independent variables.
  • To advocate for the adoption of validated survival analysis models in health services research.

Main Methods:

  • Review of existing literature on survival analysis and its application in health outcomes research.

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  • Comparison of the methodological strengths and weaknesses of survival analysis versus the total population approach.
  • Discussion on ensuring the validity of survival analysis models and research designs for DM program evaluation.

    • Main Results:

    • Survival analysis accommodates censored data, including patients who achieved outcomes, were lost to follow-up, or disenrolled.
    • This method allows for the inclusion of independent variables to explain outcome variability.
    • Survival analysis provides a more nuanced and less biased evaluation of DM program effectiveness.

    Conclusions:

    • Survival analysis is a more appropriate and statistically sound method for evaluating disease management program effectiveness.
    • It addresses key limitations of the total population approach, offering a more accurate assessment of interventions.
    • Implementing survival analysis requires careful attention to model validity and research design integrity.