{"title":"Microsimulation Modeling for Health Decision Sciences Using C++: A Tutorial.","authors":"Aku-Ville Lehtimäki, Janne Martikainen","doi":"10.1007/s40273-025-01526-8","DOIUrl":null,"url":null,"abstract":"<p><p>Microsimulation models have become increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. C++ is a programming language that has gained widespread recognition in computationally intensive fields, including systems modeling and performance-critical applications. It offers powerful tools for building high-performance microsimulation models, outpacing many traditional modeling software solutions, such as native R, in terms of speed and control over memory management. However, there is limited accessible guidance for implementing microsimulation models in C++. This tutorial offers a step-by-step approach to constructing microsimulation models in C++ and demonstrates its application through simplified but adaptable example decision models. We walk the reader through essential steps and provide generic C++ code that is flexible and suitable for adapting to a range of models. Finally, we present the standalone C++ models and their Rcpp counterparts run within R, and compare their performance to equivalent R implementations in terms of speed and memory efficiency.</p>","PeriodicalId":19807,"journal":{"name":"PharmacoEconomics","volume":" ","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PharmacoEconomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40273-025-01526-8","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Microsimulation models have become increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. C++ is a programming language that has gained widespread recognition in computationally intensive fields, including systems modeling and performance-critical applications. It offers powerful tools for building high-performance microsimulation models, outpacing many traditional modeling software solutions, such as native R, in terms of speed and control over memory management. However, there is limited accessible guidance for implementing microsimulation models in C++. This tutorial offers a step-by-step approach to constructing microsimulation models in C++ and demonstrates its application through simplified but adaptable example decision models. We walk the reader through essential steps and provide generic C++ code that is flexible and suitable for adapting to a range of models. Finally, we present the standalone C++ models and their Rcpp counterparts run within R, and compare their performance to equivalent R implementations in terms of speed and memory efficiency.
期刊介绍:
PharmacoEconomics is the benchmark journal for peer-reviewed, authoritative and practical articles on the application of pharmacoeconomics and quality-of-life assessment to optimum drug therapy and health outcomes. An invaluable source of applied pharmacoeconomic original research and educational material for the healthcare decision maker.
PharmacoEconomics is dedicated to the clear communication of complex pharmacoeconomic issues related to patient care and drug utilization.
PharmacoEconomics offers a range of additional features designed to increase the visibility, readership and educational value of the journal’s content. Each article is accompanied by a Key Points summary, giving a time-efficient overview of the content to a wide readership. Articles may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand the scientific content and overall implications of the article.