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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp012j62s7296
Title: Multi-State Markov Chain Modeling of Health Insurance Claims and Cost Prediction
Authors: Zhan, Barbara
Advisors: Wang, Mengdi
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: Health care costs have increased significantly in the past few decades due to a cost-per- service incentive structure, which compensates physicians for quantity, not quality, of treatments. Accordingly, predicting health insurance costs of multi-visit conditions with accuracy is a problem of wide-reaching importance for insurance companies. This thesis focuses on modeling health insurance claims of episodic, recurring health prob- lems as Markov Chains, estimating cycle length and cost, and then pricing associated health insurance premiums and setting forth a framework for the risk-management of a health insurance portfolio. The cost and cycle-length estimations modeled in this thesis affords health insurance companies a way to compare physician treatment effectiveness and cost effectiveness, to inform them of which physicians to cover.
Extent: 80 pages
URI: http://arks.princeton.edu/ark:/88435/dsp012j62s7296
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

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