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            Chapter Value-Based Evaluation of Chinese Provincial Health Insurance Policy Schemes

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            Author(s)
            Hu, Shanlian
            Holtorf, Anke-Peggy
            Wijaya, Kalman
            He, Jiangjiang
            Brixner, Diana
            Language
            English
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            Abstract
            Since 2011, an international group of health policy experts has been working on a value-framework to be used for pharmaceutical policy decisions based on multicriteria decision analysis (MCDA). This tool can be easily adapted to a local decision-making context through a facilitated workshop format. Several workshops have been conducted in emerging markets to test the acceptance and feasibility of using MCDA in local decision-making. In China, national policy goals for expanding health-care coverage pressure the provincial governments to implement more comprehensive coverage schemes. This chapter demonstrates the adaptation of a global value-framework to the local policy environment. In September 2018, nine leaders from provincial health insurance bureaus responsible for the urban employee basic medical insurance (UEBMI) participated in a 1-day workshop to build a consensus on the most important objectives for the health-care reform and to translate these into measurable criteria. The participants ranked the criteria by importance and MCDA methodology was used for weighing the importance of each criterion in the final decision. The model driving this process will be presented and discussed by comparing two policy options for health-care reform.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/189203
            Keywords
            China, multicriteria decision analysis, MCDA, insurance policy, decision-making, stakeholder engagement, medical savings account; thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBN Public health and preventive medicine::MBNH Personal and public health / health education::MBNH9 Health psychology
            DOI
            10.5772/intechopen.84373
            Publisher
            InTechOpen
            Publication date and place
            2020
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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