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Health Economic Evaluation Using Markov Models in R for Microsoft Excel Users: A Tutorial.

Nathan Green1, Felicity Lamrock2, Nichola Naylor3,4

  • 1Department of Statistical Science, University College London, London, UK.

Pharmacoeconomics
|November 6, 2022
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Summary
This summary is machine-generated.

This tutorial guides health economists in using R for cost-effectiveness analysis, demonstrating Markov models. It bridges the gap from MS Excel to R, enhancing reproducibility and transparency in health economic evaluations.

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Area of Science:

  • Health Economics
  • Computational Statistics

Background:

  • Health economic evaluation (HEE) involves comparing costs and consequences of different health interventions.
  • Cost-effectiveness analysis (CEA) quantifies the cost per unit of health outcome gained.
  • Traditional CEA often uses MS Excel, but complex analyses require more robust software for reproducibility and transparency.

Purpose of the Study:

  • To provide a step-by-step guide for implementing Markov models in R for health economic evaluations.
  • To facilitate the transition for health economic modelers from MS Excel to R.
  • To enhance the reproducibility and transparency of CEA.

Main Methods:

  • Implementation of a standard Markov model for HEE in the R statistical programming language.
  • Side-by-side comparison of Markov model examples in MS Excel and R.
  • Detailed technical guidance tailored for users familiar with MS Excel.

Main Results:

  • Demonstrates the feasibility of coding complex Markov models in R.
  • Provides a clear, comparative approach to understanding R implementation from an MS Excel perspective.
  • Highlights R's advantages in handling complex data and improving analysis reproducibility.

Conclusions:

  • R offers a powerful alternative to MS Excel for advanced health economic modeling.
  • Adoption of R requires developing programming skills but offers significant benefits in transparency and reproducibility.
  • This tutorial aims to lower the learning curve for health economists transitioning to R for CEA.