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. 2022 Dec 1;12(12):e066289.
doi: 10.1136/bmjopen-2022-066289.

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

Nattadhanai Rajatanavin  1 , Woranan Witthayapipopsakul  2 , Vuthiphan Vongmongkol  2 , Nithiwat Saengruang  2 , Yaowaluk Wanwong  2 , Aniqa Islam Marshall  2 , Walaiporn Patcharanarumol  2 , Viroj Tangcharoensathien  2
Affiliations

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

Nattadhanai Rajatanavin et al. BMJ Open. .

Abstract

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.

Keywords: general diabetes; health policy; hypertension; public health.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Effective coverage indicators for 1. diabetes and 2. hypertension 2016–2019.
Figure 2
Figure 2
Effective coverage indicators for diabetes stratified by sex and age group.
Figure 3
Figure 3
Effective coverage indicators for hypertension stratified by sex and age group.
See this image and copyright information in PMC

References

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