Effective coverage of diabetes and hypertension: an analysis of Thailand's national insurance database 2016-2019.

OBJECTIVES: This study assesses effective coverage of diabetes and hypertension in Thailand during 2016-2019. DESIGN: Mixed method, analysis of National health insurance database 2016-2019 and in-depth interviews. SETTING: Beneficiaries of Universal Coverage Scheme residing outside Bangkok. PARTICIPANTS: 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. OUTCOMES: 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. RESULTS: 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. CONCLUSION: 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.

Annual prevalence of unmet healthcare need in Thailand: evidence from national household surveys between 2011 and 2019.

BACKGROUND: Extending Universal Health Coverage (UHC) requires identifying and addressing unmet healthcare need and its causes to improve access to essential health services. Unmet need is a useful monitoring indicator to verify if low incidence of catastrophic health spending is not a result of foregone services due to unmet needs. This study assesses the trend, between 2011 and 2019, of prevalence and reasons of unmet healthcare need and identifies population groups who had unmet needs. METHOD: The unmet healthcare need module in the Health and Welfare Survey (HWS) 2011-2019 was used for analysis. HWS is a nationally representative household survey conducted by the National Statistical Office biennially. There are more than 60,000 respondents in each round of survey. The Organisation for Economic Co-operation and Development (OECD) standard questions on unmet need and reasons behind were applied for outpatient (OP), inpatient (IP) and dental services in the past 12 months. Data from samples were weighted to represent the Thai population. Univariate analysis was applied to assess unmet need across socioeconomic profiles. RESULTS: The annual prevalence of unmet need between 2011 and 2019 was lower than 3%. The prevalence was 1.3-1.6% for outpatient services, 0.9% - 1.1% for dental services, and lower than 0.2% for inpatient care. A small increasing trend was observed on dental service unmet need, from 0.9% in 2011 to 1.1% in 2019. The poor, the elderly and people living in urban areas had higher unmet needs than their counterparts. Long waiting times was the main reason for unmet need, while cost of treatment was not an issue. CONCLUSION: The low level of unmet need at less than 3% was lower than OECD average (28%), and was the result of UHC since 2002. Regular monitoring using the national representative household survey to estimate annual prevalence and reasons for unmet need can guide policy to sustain and improve access by certain population groups.

School health for migrant children: a myth or a must?

BACKGROUND: School health plays a vital role in lifelong health outcomes. Migrant children are a vulnerable population that seem to have inadequate health promotion interventions, and limited studies have assessed their health status and personal hygiene at schools. This study aimed to evaluate school health promotion and health outcomes of migrant children in Thai public schools (TPSs) and migrant learning centers (MLCs). METHODS: A cross-sectional study was applied. Data were collected from questionnaires focusing on health care access, nutritional status, and personal hygiene of migrant children in two MLCs and four TPSs, along with Thai children in the same TPSs. Descriptive analysis and logistic regression model were used to compare access to health promotion and the health status of migrant children with the Thai counterparts. RESULTS: Blended school health services were generally found in TPSs, which led to indifferent vaccination rates between Thai and migrant children in TPSs (odds ratio [OR] 0.457 (0.186-1.120)). However, vaccination rates of migrant children in MLCs are noticeably around fourfold lower. Overall, migrant children received fewer dental health services than Thai children, both in TPSs (OR 0.198 (0.076,0.517)) and MLCs (OR 0.156 (0.004,0.055)). Other personal hygiene behaviors and nutritional statuses saw no significant difference between Thai children and migrant children in either TPSs or MLCs. The uninsured status among migrant children posed another challenge to health care access, as 81.7% of the migrant children in MLCs and 56.6% in TPSs were uninsured. CONCLUSION: Migrant children in MLCs received a lower rate of essential vaccinations compared to those in TPSs. Dental services appeared to be the most neglected area of care in migrant children. The findings indicate the necessity of supportive policy for MLCs, while regulating quality and standards concurrently. Multisectoral collaboration is critically needed for sustainably improving the quality of life of migrant children.

Achieving the targets for universal health coverage: how is Thailand monitoring progress?

Universal health coverage (UHC) is one of the targets within the Sustainable Development Goals that the Member States of the United Nations have pledged to achieve by 2030. Target 3.8 has two monitoring indicators: 3.8.1 for coverage of essential health services, for which a compound index from 16 tracer indicators has recently been developed; and 3.8.2 for catastrophic expenditure on health. The global baseline monitoring of these two indicators in 2017 shows that the progress in many low- and middle-income countries is unlikely to be on track and achieved by 2030. The monitoring and evaluation mechanism for UHC progress is a crucial function to hold governments accountable and guide countries along their paths towards UHC. This paper outlines key monitoring and evaluation tools that Thailand uses to track UHC progress; compares the strengths and limitations of each tool; and discusses monitoring gaps and enabling factors related to development of the tools. Thailand uses several data sources to monitor three UHC dimensions: population coverage; service coverage; and financial risk protection. The four key sources are: (i) national surveys; (ii) health facility and administrative data; (iii) specific disease registries; and (iv) research. Each source provides different advantages and is used concurrently to complement the others. Despite initially being developed to track progress for national health priorities, these tools are able to monitor most of the global UHC indicators. Key enabling factors of Thai monitoring systems are a supportive infrastructure and information system; a policy requirement for routine patient data records; ownership and commitment of the key responsible organizations; multisectoral collaboration; and sustainable in-country capacities. The areas for improvement are monitoring in the non-Thai population; tracking access to essential medicines; and maximizing the use of collected data. Lessons learnt from the Thai experience could be useful for other low- and middle-income countries in developing their UHC monitoring platforms.

Strategic purchasing and health system efficiency: A comparison of two financing schemes in Thailand.

Strategic purchasing is an essential health financing function. This paper compares the strategic purchasing practices of Thailand's two tax-financed health insurance schemes, the Universal Coverage Scheme (UCS) and the Civil Servant Medical Benefit Scheme (CSMBS), and identifies factors contributing to successful universal health coverage outcomes by analysing the relationships between the purchaser and government, providers and members. The study uses a cross-sectional mixed-methods design, including document review and interviews with 56 key informants. The Comptroller General Department (CGD) of Ministry of Finance manages CSMBS as one among civil servant welfare programmes. Their purchasing is passive. Fee for service payment for outpatient care has resulted in rapid cost escalation and overspending of their annual budget. In contrast, National Health Security Office (NHSO) manages purchasing for UCS, which undertakes a range of strategic purchasing actions, including applying closed ended provider payment, promoting primary healthcare's gate keeping functions, exercising collective purchasing power and engaging views of members in decision making process. This difference in purchasing arrangements resulted in expenditure per CSMBS member being 4 times higher than UCS in 2014. The governance of the purchaser organization, the design of the purchasing arrangements including incentives and use of information, and the institutional capacities to implement purchasing functions are essential for effective strategic purchasing which can improve health system efficiency as a whole.

Diabetes prevention and care in the universal health coverage context: The example of Thailand.

Universal health coverage (UHC) is a key policy issue in countries of the World Health Organization (WHO) South-East Asia Region. However, despite projections of significant increases in burden, there is little protection against the financial risks associated with noncommunicable diseases (NCDs), including diabetes. Thailand achieved UHC of all 67 million of the population in 2002, under three public health insurance schemes. The country therefore provides a case-study on diabetes prevention and care in the context of UHC. Although the budget for the Thai Universal Coverage (UC) scheme, which covers nearly 80% of the population, increased significantly during 2003-2013, the proportion allocated to clinical prevention and health promotion declined from 15% to 11%. The financial case for investment in diabetes prevention is made, particularly with respect to a focus on primary care and the use of community volunteers. The UC scheme can expand to nearly 100% population coverage, with a comprehensive benefit package and financial risk protection. Although the rates of complications and fatalities in patients with diabetes have improved over the last few years, achievement of well-controlled fasting blood glucose for all patients is still the main challenge for further improvement. It is recommended that, in order to improve coverage of diabetes care and prevention, it is essential for countries in the WHO South-East Asia Region to include major NCD services, in particular primary prevention, in their UHC strategies. Since a resilient health system is key to UHC delivery, strengthening of the health workforce and infrastructure should be part of any action plan to prevent and control diabetes.