Factors Associated with Willingness to Pay for Cost-Sharing under Universal Health Coverage Scheme in Yogyakarta, Indonesia: A Cross-Sectional Survey

Abstract

Background: National Health Insurance (NHI) in Indonesia requires an appropriate cost-sharing policy, particularly for diseases that require the largest financing. This study examined factors that influence willingness to pay (WTP) for cost-sharing under the universal health coverage scheme among patients with catastrophic illnesses in Yogyakarta, Indonesia. Methods: This was a cross-sectional study using structured questionnaires through direct interviews. The factors related to the WTP for cost-sharing under the NHI scheme in Indonesia were identified by a bivariable logistic regression analysis. Results: Two out of every five (41.2%) participants had willingness to pay for cost-sharing. Sex [AOR = 0.69 (0.51, 0.92)], education [AOR = 1.54 (0.67, 3.55)], family size [AOR = 1.71 (1.07, 2.73)], occupation [AOR = 1.35 (0.88, 2.07)], individual income [AOR = 1.50 (0.87, 2.61)], household income [AOR = 1.47 (0.90, 2.39)], place of treatment [AOR = 2.54 (1.44, 4.45)], a health insurance plan [AOR = 1.22 (0.87, 1.71)], and whether someone receives an inpatient or outpatient service [AOR = 0.23 (0.10, 0.51)] were found to affect the WTP for a cost-sharing scheme with p < 0.05. Conclusion: Healthcare (place of treatment, health insurance plan, and whether someone receives an inpatient or outpatient service) and individual socioeconomic (sex, educational, family size, occupational, income) factors were significantly related to the WTP for cost-sharing.

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

“…The pooled odds ratio (OR = 0.99, 95% CI: 0.75-1.23) also showed no difference between males and females in the WTP for NHI. Some studies indicated that households headed by females had a higher likelihood of WTP for NHI (85,86,90,94), whereas other studies found that males were more inclined to pay (91,97,100,101), which was similar to an original study in Burkina Faso showing that men were more willing to pay to join health insurance than women (176).…”

“…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.…”

“…A sensitivity analysis was also conducted to identify outlier studies. Accordingly, seven studies were found to be outliers (88,91,93,94,96,99,101), and the pooled estimate (effect size) was influenced by the inclusion and exclusion of these studies. Nevertheless, as shown in Figure 13, when we adjusted for outliers using a random effects model, all of the included studies (n = 15) were found not to be outliers.…”

“…Under this theme, the WTP for NHI was found to be influenced by family size, age, marital status, gender, area of residence, and level of Accordingly, some studies have reported that WTP for the scheme increased with family size (83,85,92,101), while others have found a negative relationship between household size and WTP for the scheme (84, 89,93). Other reviews and original studies conducted worldwide have also shown inconsistent findings regarding the relationship between family size and the WTP for NHI.…”

Assessing the Determinants of Compliance with Contribution Payments to the National Health Insurance Scheme among Informal Workers in Indonesia

“…As a result, many health systems in LMICs have relied heavily on out-of-pocket (OOP) spending to pay for medical care [1], which accounts for 30-85% of the entire cost of health care [2,3]. These countries are financially burdened by catastrophic illnesses as a result of high OOP charges [4]. It was reported that around 808 million people in 2010 had major health care spending [5], and this figure increased constantly from 2000 to 2017 [6].…”