Medical assistance serves as a fundamental institutional arrangement safeguarding the basic healthcare rights of disadvantaged populations. Technologies such as big data and artificial intelligence are driving the digital and intelligent transformation of medical assistance. Drawing on case studies, this paper constructs a theoretical analytical framework centered on core elements—needs identification, service provision, and outcome feedback—to systematically elucidate the logic of how digital and intelligent technologies empower medical assistance governance. Research findings reveal that digital and intelligent empowerment has yielded significant outcomes in medical assistance governance: the policy framework has been continuously refined, digital and intelligent infrastructure development has progressed steadily, and administration services have been consistently optimized. However, challenges persist, including the digital divide and equity gaps, insufficient information sharing and institutional coordination, incomplete rules for technology integration, and underdeveloped digital governance mechanisms. Based on this analysis, the paper proposes pathways for digital and intelligent empowerment in medical assistance governance: bridging the digital divide and promoting service equity at the value level, deepening governance coordination and information sharing among stakeholders at the governance entity level, advancing the deep integration of technology and services at the governance process level, and strengthening safeguards for digital and intelligent governance mechanisms at the governance mechanism level.
Key words
digital intelligence empowerment /
medical assistance /
digital intelligence technology /
targeted governance
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] 高鹏,杨翠迎,刘言.医疗救助、健康水平改善与医疗经济负担[J]. 中国经济问题,2023(04):85-101.
[2] 周佳卉,朱铭来.医疗救助制度公平性评价[J]. 西北人口,2025,46(04):97-112.
[3] 姚宇. 精准施救是医疗救助制度托底性功能的集中体现[J]. 中国医疗保险,2021(11):41-42.
[4] 匡亚林,赵蜀蓉,孟雅琪.数字赋能社会救助高质量发展的路径选择[J]. 中国行政管理,2024,40(07):155-158.
[5] 赵秀竹,李波清,郝文祥,等.大数据赋能中国式医保现代化的逻辑机理、现实挑战与推进构想——基于“技术—制度—价值”协同演进视角[J]. 中国医疗保险,2025(06):23-28.
[6] 国家医疗保障局.国家医保局局长章轲等出席国务院新闻办公室新闻发布会——介绍“十四五”时期深化医保改革,服务经济社会发展有关情况[EB/OL]. (2025-07-24)[2025-08-25]. https://www.nhsa.gov.cn/art/2025/7/24/art_14_17369.html.
[7] 国家医疗保障局.着力构建智慧医保服务新格局——助力完善多层次医疗保障体系[EB/OL]. (2025-12-26)[2025-12-30]. https://www.nhsa.gov.cn/art/2025/12/26/art_14_19158.html.
[8] 祝建华. 智慧救助的要素驱动、运行逻辑与实践进路[J]. 社会保障评论,2022,6(02):105-121.
[9] 王秉.何为数智:数智概念的多重含义研究[J]. 情报杂志,2023,42(07):71-76.
[10] 李大宇,章昌平,许鹿.精准治理:中国场景下的政府治理范式转换[J]. 公共管理学报,2017,14(01):1-13+154.
[11] 吴玉锋. 数字技术赋能精准救助:从何以可能到何以可为[J]. 社会保障评论,2025,9(01):112-127.
[12] 周佳卉,朱铭来.分层分类模式下医疗救助支出预测与政策优化[J]. 社会保障评论,2025,9(04):105-123.
[13] 国家数据局.面向“两早双优”的医保医疗数据要素智能协同新模式探索及应用[EB/OL]. (2025-02-28)[2025-12-20]. https://www.nda.gov.cn/sjj/ywpd/zcgh/0228/20250228100148988724809_pc.html.
[14] 中华人民共和国工业和信息化部.广西壮族自治区:医疗救助返贫监测[EB/OL]. (2025-09-26)[2025-11-20]. https://www.cstc.org.cn/info/1081/256356.htm.
[15] 张梦瑶,辜翔,于淼.大数据赋能医保治理的路径与挑战[J]. 中国医疗保险,2025(06):29-36.
[16] 高静华. 数字化驱动下社会救助的多重制度逻辑与行动策略——以J县医保防贫数字化改革为例[J]. 社会保障评论,2025,9(02):63-77.
[17] 嘉兴市民政局.大救助大数据大智慧——浙江创新建设“1+8+X”大救助体系实录[EB/OL]. (2020-08-26)[2025-11-20]. https://mzj.jiaxing.gov.cn/art/2020/8/26/art_1229574837_58886694.html.
[18] 福建医疗保障.厦门医保“数字化医疗救助服务”入选省级优秀案例[EB/OL]. (2024-12-09)[2025-11-20]. https://mp.weixin.qq.com/s/PVM46KCvxdy06buB42Kqvg.
[19] 丽水市政府官网.数据赋能精准救助 “缙情帮”应用助力构建多层次医疗保障体系[EB/OL]. (2024-11-11)[2025-11-20]. https://www.lishui.gov.cn/art/2024/11/11/art_1229641802_57365723.html.
[20] 陕西省医疗保障局.汉中市汉台区医保局:创新医保监测预警机制——构建社会救助综合格局[EB/OL]. (2024-09-27)[2025-12-20]. https://ybj.shaanxi.gov.cn/sy/ybyw/sxybdt/202409/t20240927_3447731.html.
[21] 上海宝山区政府.“四步走”实现医疗救助经办全流程闭环管理[EB/OL]. (2025-03-13)[2025-12-20]. https://mp.weixin.qq.com/s/NUsC5sbyAD6DolQp5NmBQA?scene=1&click_id=31.
[22] 新华社.中共中央、国务院关于深化医疗保障制度改革的意见[EB/OL]. (2020-03-05)[2025-12-21]. https://www.gov.cn/zhengce/2020-03/05/content_5487407.htm.
[23] 中国政府网.国务院办公厅关于印发“十四五”全民医疗保障规划的通知[EB/OL]. (2021-09-23)[2025-12-21]. https://www.gov.cn/zhengce/content/2021-09/29/content_5639967.htm.
[24] 中国政府网.国家医保局办公室、民政部办公厅关于进一步做好医疗救助对象信息共享工作的通知[EB/OL]. (2024-10-31)[2025-12-21]. https://www.gov.cn/zhengce/zhengceku/202411/content_6986125.htm.
[25] 天津市人民政府.天津市人民政府办公厅关于印发天津市医疗救助办法的通知[EB/OL]. (2021-02-10)[2025-12-21]. https://www.tj.gov.cn/zwgk/szfwj/tjsrmzfbgt/202102/t20210210_5356488.html.
[26] 广东省人民政府.广东省医疗保障局、广东省民政厅、广东省财政厅、广东省卫生健康委员会、广东省乡村振兴局、广东省政务服务数据管理局关于印发《广东省医疗救助办法》的通知[EB/OL]. (2023-08-24)[2025-12-21]. https://www.gd.gov.cn/zwgk/gongbao/2023/24/content/post_4253294.html.
[27] 国家数据局.国家数据局举办“数据要素×”首场新闻发布会[EB/OL]. (2025-05-30)[2025-09-22]. https://www.nda.gov.cn/sjj/swdt/xwfb/0529/20250529231654702250601_pc.html.
[28] 新华网.“十四五”时期医保帮扶政策累计惠及农村低收入人口就医6.73亿人次[EB/OL]. (2025-07-24)[2025-12-30]. https://www.xinhuanet.com/gongyi/20250724/ca60bc136d0241c4bc00a6d6a7bf7c59/c.html.
[29] 匡亚林,蒋子恒,张帆.数字技术赋能社会救助:缘起、风险及治理[J]. 上海行政学院学报,2023,24(02):86-97.
[30] 吴娟,关信平.社会救助数字化转型:整体逻辑、现实问题与应对策略[J]. 社会保障研究,2023(06):80-91.
[31] 许小玲,张高荣.数智赋能社会救助的逻辑理路与异化风险治理——基于TOE框架的分析[J]. 人文杂志,2025(08):123-131.
