2022 article

When History and Heterogeneity Matter: A Tutorial on the Impact of Markov Model Specifications in the Context of Colorectal Cancer Screening

Townsley, R. M., Koutouan, P. R., Mayorga, M. E., Mills, S. D., Davis, M. M., & Hasmiller Lich, K. (2022, May 11). MEDICAL DECISION MAKING.

By: R. Townsley*, P. Koutouan n, M. Mayorga n, S. Mills*, M. Davis* & K. Hasmiller Lich*

author keywords: colorectal cancer screening; markov models; microsimulation
MeSH headings : Colonoscopy; Colorectal Neoplasms / diagnosis; Colorectal Neoplasms / epidemiology; Early Detection of Cancer / methods; Humans; Mass Screening / methods; Occult Blood
TL;DR: Colorectal cancer screening trajectories and projected health outcomes were sensitive to the use of alternate Markov model specifications, demonstrating the importance of examining the memoryless assumption of the first-order Markovmodel when simulating health care utilization over time. (via Semantic Scholar)
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Source: Web Of Science
Added: May 31, 2022

Background Markov models are used in health research to simulate health care utilization and disease states over time. Health phenomena, however, are complex, and the memoryless assumption of Markov models may not appropriately represent reality. This tutorial provides guidance on the use of Markov models of different orders and stratification levels in health decision-analytic modeling. Colorectal cancer (CRC) screening is used as a case example to examine the impact of using different Markov modeling approaches on CRC outcomes.