Willingness to Pay for National Health Insurance: A Contingent Valuation Study Among Patients Visiting Public Hospitals in Melaka, Malaysia

Tan, Robin Tiow Heng; Rasid, Siti Zaleha Abdul; Ismail, Wan Khairuzzaman Wan; Tobechan, Janiza; Tan, Edwin Tiow Yong; Yusof, Alia Natasha; Low, Jia Hui

doi:10.1007/s40258-021-00691-z

Cited by 4 publications

(7 citation statements)

References 36 publications

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“…The other important sociodemographic variable affecting the WTP for NHI was level of education, in that in most of the included studies, participants who have higher education attainment were more likely to pay for the scheme (83,89,94,95,98), while in some of them, its influence was found to be inconclusive (90,91,101). Similar studies in Malaysia also showed that a higher education level was associated with a higher demand (156) and a higher WTP (125) for health insurance.…”

Section: Socio-demographic Factorsmentioning

confidence: 85%

“…This systematic review found that age was a consistent negative predictor of WTP for NHI (84,86,87,90,94,95,99); that is, WTP for the NHI scheme consistently decreased with increasing age. This dictates that the slightly higher WTP for NHI in Africa may be due to the continent's youngest population, with 70% of SSA under 30 years old (154).…”

Section: Socio-demographic Factorsmentioning

confidence: 92%

“…On the other hand, lack of access to information is a significant contributor to the inequality in health insurance subscriptions (190). Our review revealed that awareness level (84, 92, 94), good knowledge (87) and perception (95), insurance literacy, and access to the internet (100) were positively related to the WTP for NHI. However, some studies reported that level of awareness (98), good knowledge (95), and good perception (89) were negatively related to the WTP for the scheme.…”

Section: Information Level and Information Sourcesmentioning

confidence: 93%

“…Regarding the influence of marital status on the WTP for NHI, married households were less likely to pay compared to their single or unmarried counterparts (85,86,95). A study in SSA also revealed that married women's health insurance coverage is only 21.3%, with the highest and lowest coverage in Ghana (66.7%) and Burkina Faso (0.5%).…”

Section: Socio-demographic Factorsmentioning

confidence: 99%

“…Regarding employment status, the studies' reports were not consistent. Some studies found that those families with a formally employed head were more likely to pay (88,95,99), while others reported the opposite (101). In general, employment status can significantly influence an individual's WTP for health insurance, as higher-income individuals are more likely to afford premiums.…”

Section: Income and Economic Issuesmentioning

confidence: 99%

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Willingness to pay for National Health Insurance Services and Associated Factors in Africa and Asia: a systematic review and meta-analysis

Bayked,

Assfaw,

Toleha

et al. 2024

Front. Public Health

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BackgroundUniversal health coverage (UHC) is crucial for public health, poverty eradication, and economic growth. However, 97% of low- and middle-income countries (LMICs), particularly Africa and Asia, lack it, relying on out-of-pocket (OOP) expenditure. National Health Insurance (NHI) guarantees equity and priorities aligned with medical needs, for which we aimed to determine the pooled willingness to pay (WTP) and its influencing factors from the available literature in Africa and Asia.MethodsDatabase searches were conducted on Scopus, HINARI, PubMed, Google Scholar, and Semantic Scholar from March 31 to April 4, 2023. The Joanna Briggs Institute’s (JBI’s) tools and the “preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 statement” were used to evaluate bias and frame the review, respectively. The data were analyzed using Stata 17. To assess heterogeneity, we conducted sensitivity and subgroup analyses, calculated the Luis Furuya-Kanamori (LFK) index, and used a random model to determine the effect estimates (proportions and odds ratios) with a p value less than 0.05 and a 95% CI.ResultsNineteen studies were included in the review. The pooled WTP on the continents was 66.0% (95% CI, 54.0–77.0%) before outlier studies were not excluded, but increased to 71.0% (95% CI, 68–75%) after excluding them. The factors influencing the WTP were categorized as socio-demographic factors, income and economic issues, information level and sources, illness and illness expenditure, health service factors, factors related to financing schemes, as well as social capital and solidarity. Age has been found to be consistently and negatively related to the WTP for NHI, while income level was an almost consistent positive predictor of it.ConclusionThe WTP for NHI was moderate, while it was slightly higher in Africa than Asia and was found to be affected by various factors, with age being reported to be consistently and negatively related to it, while an increase in income level was almost a positive determinant of it.

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