Developing High-Quality Microsimulation Models Using R in Health Decision Sciences

Heesun Eom, Yan Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Health decision science is a growing field that studies the use of population health data and advanced analytical tools to inform decisions. This paper describes several modeling approaches and programming languages widely used in health decision sciences. Special emphasis is put on the development of microsimulation models using R. A recent microsimulation model - Simulation for Health Improvement and Equity (SHINE) Model - is described to demonstrate the development of microsimulaiton models using R. Several practical recommendations for developing microsimulation models using R are proposed. This paper may serve as a practical guide for population health scientists and healthcare professionals to develop their own microsimulation models to inform complex health decisions.

Original languageEnglish
Title of host publicationProceedings of the 2020 Winter Simulation Conference, WSC 2020
EditorsK.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1167-1177
Number of pages11
ISBN (Electronic)9781728194998
DOIs
StatePublished - 14 Dec 2020
Event2020 Winter Simulation Conference, WSC 2020 - Orlando, United States
Duration: 14 Dec 202018 Dec 2020

Publication series

NameProceedings - Winter Simulation Conference
Volume2020-December
ISSN (Print)0891-7736

Conference

Conference2020 Winter Simulation Conference, WSC 2020
Country/TerritoryUnited States
CityOrlando
Period14/12/2018/12/20

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