Publication: Evaluation of responsiveness of health systems using fuzzy-based technique
2
Issued Date
2014-01-01
Resource Type
ISSN
10987584
Other identifier(s)
2-s2.0-84912557592
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE International Conference on Fuzzy Systems. (2014), 1618-1623
Suggested Citation
Sukanya Phongsuphap, Yongyuth Pongsupap Evaluation of responsiveness of health systems using fuzzy-based technique. IEEE International Conference on Fuzzy Systems. (2014), 1618-1623. doi:10.1109/FUZZ-IEEE.2014.6891574 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/33740
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Evaluation of responsiveness of health systems using fuzzy-based technique
Author(s)
Other Contributor(s)
Abstract
© 2014 IEEE. This paper proposes a method for evaluating responsiveness of health systems. The method is based on a fuzzy model, which can tackle uncertainty of survey data, and perform corresponding to the way that human being makes decisions and adjustments. To measure responsiveness of health systems, we have defined five fuzzy sets for two input variables: score of direct experience of using health service and score of anchoring vignette, and five fuzzy sets for one output variable: responsiveness score which is defined as the difference between score of direct experience of using health service and score of vignette. The twenty-five fuzzy rules are derived from the analysis of input and output variables association. Mamdani style inference technique is used to compute a crisp value of average responsiveness score for each component of health systems, and the overall average responsiveness score is computed by using the weight average method. The data of seven components based on WHO framework were collected from 4,446 outpatients of three schemes of health care systems in Thailand consisting of Civil Servant Medical Benefit Scheme (CSMBS), Social Security Scheme (SSS), and Universal Coverage Scheme (UCS). Results showed that CSMBS got the highest average responsiveness score followed by SSS which got a slightly higher average responsiveness score than UCS, but there are some variations in each of seven components. The proposed method of responsiveness evaluation can provide concise information both in terms of quantitative and qualitative measures, which can be used as a policy implication to assist government and health system policy makers in improving and providing the more suitable heath care services.