The driving role of big data in medical insurance management has become increasingly prominent. The mining technology presents characteristics of multi-platform, multi-source data and interactive operation, and the results provide data support for the formulation and improvement of medical insurance policies. In recent years, China's National Healthcare Security Administration attaches great importance to the development and application of medical insurance big data, and carries out overall deployment in various aspects such as top-level design, information platform release, and business coding specifications. This paper analyzes the typical application cases of data mining in medical insurance management at home and abroad, summarizes international experience from aspects of medical insurance fund allocation, resource management, and fund supervision. Taking Shanghai, Chongqing, Hainan as examples, the paper reviews their organizational structure, platform construction experience, and application scenario exploration. Finally, by means of SWOT analysis, the shortcomings in the application of medical insurance big data and the challenges that will be encountered in the development of big data are put forward from the aspects of platform construction, multi-linkage, data mining and application, so as to realize more efficient medical insurance services, smarter supervision and more scientific decision-making.
Key words
big data /
medical big data /
data mining /
medical insurance management
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] MAYER-SCHÖNBERGER V, CUKIER K.Big data: a revolution that will transform how we live, work, and think[M].Houghton Mifflin Harcourt, 2013.
[2] 景玺,秦靖沂.大数据在医保管理中的应用与发展方向[J].中国医疗保险,2018,7:20-23.
[3] NHS England.Technical Guide to Allocation Formulae and Pace of Change for2019/20 to 2023/24 revenue allocations[EB/OL].(2019-05-30)[2023-02-04].https://www.england.nhs.uk/publication/technical-guide-to-allocation-formulae-and-pace-of-change-for-2019-20-to-2023-24-revenue-allocations/.
[4] The Surveillance, Epidemiology, and End Results (SEER) Program//SEER[EB/OL].[2023-02-04].https://seer.cancer.gov/about/overview.html.
[5] ADIMADHYAM S, BARRETO EF, COCOROS NM, et al.Leveraging the Capabilities of the FDA's Sentinel System To Improve Kidney Care[J].Journal of the American society of nephrology.2020,31(11):2506-2516.
[6] PLATT R, CARNAHAN RM, BROWN JS, et al.The U.S.Food and Drug Administration's Mini-Sentinel program: status and direction[J].Pharmacoepidemiol Drug Saf.2012,21 Suppl 1:1-8.
[7] ROBB MA, RACOOSIN JA, SHERMAN RE, et al.The US Food and Drug Administration's Sentinel Initiative: expanding the horizons of medical product safety[J].Pharmacoepidemiol Drug Saf.2012,21 Suppl 1:9-11.
[8] GENT K.Report to Congress Fraud Prevention System Second Implementation Year[R].CMS , 2014.
[9] 全国统一医保信息平台建成[EB/OL].(2022-05-12)[2023-02-03].http://www.gov.cn/xinwen/2022-05/12/content_5689783.html.
