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arXiv · 1812.00528

Modeling disease progression in longitudinal EHR data using continuous-time hidden Markov models

Aman Verma·Guido Powell·Yu Luo·David Stephens·David L. Buckeridge
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Abstract

Modeling disease progression in healthcare administrative databases is complicated by the fact that patients are observed only at irregular intervals when they seek healthcare services. In a longitudinal cohort of 76,888 patients with chronic obstructive pulmonary disease (COPD), we used a continuous-time hidden Markov model with a generalized linear model to model healthcare utilization events. We found that the fitted model provides interpretable results suitable for summarization and hypothesis generation.

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Aman Verma, Guido Powell, Yu Luo, David Stephens, David L. Buckeridge. 2018-12-03. Modeling disease progression in longitudinal EHR data using continuous-time hidden Markov models. https://arxiv.org/abs/1812.00528

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