Markov model and meta-heuristics combined method for cost-effectiveness analysis

Xiuxian Wang, Na Geng, Jianxin Qiu, Zhibin Jiang () and Liping Zhou
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Xiuxian Wang: Shanghai Jiao Tong University
Na Geng: Shanghai Jiao Tong University
Jianxin Qiu: Shanghai Jiao Tong University
Zhibin Jiang: Shanghai Jiao Tong University
Liping Zhou: Shanghai Jiao Tong University

Flexible Services and Manufacturing Journal, 2020, vol. 32, issue 1, No 9, 213-235

Abstract: Abstract Cost-effectiveness analysis is an important topic in public health, which can provide valuable information for medical decisions. Several modeling methods are available for conducting cost-effectiveness analysis. However, it is difficult when the data is incomplete. To solve this problem, a Markov model is proposed to model patients’ health states transition, and two hybrid metaheuristics are proposed to estimate the transition probabilities. Based on the estimated transition probabilities, cost-effectiveness analysis is conducted to compare different medical interventions. Numerical experiments and case study validate the effectiveness and practicability of the proposed method. The case study gives the physicians effective instructions by comparing two different immunosuppressants after renal transplantation.

Keywords: Cost-effectiveness analysis; Markov model; Meta-heuristics; Renal transplantation; Transition probability (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10696-019-09369-0

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