Rajatanavin Nattadhanai, Witthayapipopsakul Woranan, Vongmongkol Vuthiphan, Saengruang Nithiwat, Wanwong Yaowaluk, Marshall Aniqa Islam, Patcharanarumol Walaiporn, Tangcharoensathien Viroj
Health Financing, International Health Policy Program, Muang District, Thailand
Health Financing, International Health Policy Program, Muang District, Thailand.
BMJ Open. 2022 Dec 1;12(12):e066289. doi: 10.1136/bmjopen-2022-066289.
This study assesses effective coverage of diabetes and hypertension in Thailand during 2016-2019.
Mixed method, analysis of National health insurance database 2016-2019 and in-depth interviews.
Beneficiaries of Universal Coverage Scheme residing outside Bangkok.
Quantitative analysis was performed by acquiring individual patient data of diabetes and hypertension cases in the Universal Coverage Scheme residing outside bangkok in 2016-2019. Qualitative analysis was conducted by in-depth interview of 85 multi-stakeholder key informants to identify challenges.
Estimate three indicators: detected need (diagnosed/total estimated cases), crude coverage (received health services/total estimated cases) and effective coverage (controlled/total estimated cases) were compared. Controlled diabetes was defined as haemoglobin A1C (HbA1C) below 7% and controlled hypertension as blood pressure below 140/90 mm Hg.
Estimated cases were 3.1-3.2 million for diabetes and 8.7-9.2 million for hypertension. For diabetes, all indicators have shown slow improvement between 2016 and 2019 (67.4%, 69.9%, 71.9% and 74.7% for detected need; 38.7%, 43.1%, 45.1% and 49.8% for crude coverage and 8.1%, 10.5%, 11.8% and 11.7% for effective coverage). For hypertension, the performance was poorer for detection (48.9%, 50.3%, 51.8% and 53.3%) and crude coverage (22.3%, 24.7%, 26.5% and 29.2%) but was better for effective coverage (11.3%, 13.2%, 15.1% and 15.7%) than diabetes. Results were better for the women and older age groups in both diseases. Complex interplays between supply and demand side were a key challenge. Database challenges also hamper regular assessment of effective coverage. Sensitivity analysis when using at least three annual visits shows slight improvement of effective coverage.
Effective coverage was low for both diseases, though improving in 2016-2019, especially among men and ัyounger populations. The increasing rate of effective coverage was significantly smaller than crude coverage. Health information systems limitation is a major barrier to comprehensive measurement. To maximise effective coverage, long-term actions should address primary prevention of non-communicable disease risk factors, while short-term actions focus on improving Chronic Care Model.
本研究评估了2016 - 2019年泰国糖尿病和高血压的有效覆盖率。
混合方法，对2016 - 2019年国家健康保险数据库进行分析并开展深入访谈。
曼谷以外地区全民健康保险计划的受益人群。
通过获取2016 - 2019年曼谷以外地区全民健康保险计划中糖尿病和高血压病例的个体患者数据进行定量分析。通过对85名多利益相关方关键信息提供者进行深入访谈以识别挑战，从而进行定性分析。
比较了三项指标的估计值：检测需求（确诊病例数/估计病例总数）、粗略覆盖率（接受医疗服务的病例数/估计病例总数）和有效覆盖率（病情得到控制的病例数/估计病例总数）。糖尿病病情得到控制定义为糖化血红蛋白（HbA1C）低于7%，高血压病情得到控制定义为血压低于140/90 mmHg。
糖尿病的估计病例数为310万 - 320万，高血压为870万 - 920万。对于糖尿病，2016年至2019年间所有指标均显示出缓慢改善（检测需求分别为67.4%、69.9%、71.9%和74.7%；粗略覆盖率分别为38.7%、43.1%、45.1%和49.8%；有效覆盖率分别为8.1%、10.5%、11.8%和11.7%）。对于高血压，检测（分别为48.9%、50.3%、51.8%和53.3%）和粗略覆盖率（分别为22.3%、24.7%、26.5%和29.2%）表现较差，但有效覆盖率（分别为11.3%、13.2%、15.1%和15.7%）比糖尿病情况要好。两种疾病在女性和老年人群体中的结果更好。供需双方之间复杂的相互作用是一个关键挑战。数据库方面的问题也阻碍了对有效覆盖率的定期评估。使用至少三次年度就诊进行敏感性分析时，有效覆盖率略有改善。
两种疾病的有效覆盖率都较低，尽管在2016 - 2019年有所改善，尤其是在男性和年轻人群体中。有效覆盖率的增长率明显低于粗略覆盖率。健康信息系统的局限性是全面测量的主要障碍。为了最大限度地提高有效覆盖率，长期行动应针对非传染性疾病风险因素的一级预防，而短期行动则侧重于改善慢性病照护模式。
