Abstract
This research develops a game-theoretic agent model for stable ischemic heart disease (SIHD) clinical decisions, incorporating aspects of Bayesian game theory to model hidden information such as the patient’s true underlying medical condition(s). Preexisting observational medical data contained in the United States Department of Veterans Affairs (VA) Corporate Data Warehouse (CDW) is analyzed to obtain the required game-theoretic parameter values. Various statistical adjustments are performed to correct for bias in the preexisting treatment protocol selections and to obtain game-theoretic parameter values for contrafactual treatment protocol choices. Once the game-theoretic parameter values are determined, clinical pathways can be viewed as being mathematical strategies for playing the game and thus can be studied and evaluated using the techniques of game theory.
Original language | English |
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Place of Publication | United States |
DOIs | |
State | Published - 2018 |
Keywords
- 59 BASIC BIOLOGICAL SCIENCES