Neuroeconomics of health care financing options: willingness to pay and save.
Ho-fung Leunga, H Makb, M Leungc, K L Leungd, Patrick Kwane, K S Wonga
- aDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong
- bDepartment of Diagnostic Radiology, The University of Hong Kong
- cDepartment of Economics, The Chinese University of Hong Kong
- dPrivate medical practitioner, Hong Kong
- eUniversity of Melbourne, Australia
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Abstract
In Hong Kong, the health care financing structure consists of a publicly funded service (for inpatient care, complex, and referred cases) and a privately funded service (for family medicine and a smaller proportion of hospital care). This financing structure may not be sustainable in the future if the provision of funding is purely from public funds, owing to the ageing population and the rising cost of new diagnostic methods, treatment and drugs. Health care insurance plans and savings schemes have been explored by the Government in terms of willingness-to-pay in health care insurance plans and willingness-to-save in savings schemes by means of behavioural theories.1-3 The Prospect Theory states that willingness-to-pay may not be linear across different options of risk and probability. Some options of gain may be preferred over others even if they are mathematically the same. The Hyperbolic Discounting Theory states that the notion of deferred gain may be considered with less importance compared with an immediate gain. Therefore, in two options with the same statistical risk, the one with a closer time-point of gain may be chosen over the other. These theories can be translated into the setting of health care financing. We used neuroeconomics (scans of the brain during thoughtful processes to register areas of activation) to explore willingness-to-pay in insurance plans and willingness-to-save in savings schemes and whether the two behavioural theories could Hong Kong Med J 2014;20(Suppl 3):S??-?? HHSRF project number: 06070461 H Leung *, H Mak, M Leung, KL Leung, P Kwan, KS Wong

