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

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

Background

Universal 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.

Methods

Database 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.

Results

Nineteen 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.

Conclusion

The 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.

Determining the Willingness to Pay for Innovative Oncology Medicines in Malaysia

OBJECTIVES

Early access to innovative oncology medicine is crucial to provide better treatment alternatives to patients with cancer. However, innovative oncology medicines often come at higher prices, thus limiting the government's ability for its universal coverage. Hence an alternative paying mechanism is needed. This study is intended to determine the willingness to pay (WTP) for innovative oncology medicines among Malaysians.

METHODS

A cross-sectional contingent valuation study on 571 Malaysians was conducted to elicit respondents' WTP value via bidding game approach. A double-bounded dichotomous choice was used in 3 hypothetical scenarios: innovative diabetes medicine, innovative oncology medicine one-off (IOMO), and innovative oncology medicine insurance. Univariate logistic regression was used to determine the factors affecting respondent's WTP, whereas the mean WTP value and the factors affecting amount to WTP was determined using a parametric 2-part model.

RESULTS

This study received 95% response rate. The mean age of the respondents is 48 years (SD 17) with majority of the respondents female (60.3%) and from ethnic Malay (62%). About 343 (64.7%) of the respondents expressed WTP for IOMO. Those in higher income bracket were willing to pay more for the access of IOMO than the overall WTP mean value (P = .046, coefficient 351.57).

CONCLUSIONS

More than half of Malaysian are willing to pay for IOMO at mean value of Malaysian Ringgit 279.10 (US dollar 66.77). Collaborative funding mechanisms and appropriate financial screening among the stakeholders could be introduced as methods to expedite the access of innovative oncology medicine among patients with cancer in Malaysia.

Characterization of cancer subtypes associated with clinical outcomes by multi-omics integrative clustering

Cancer patients show heterogeneous phenotypes and very different outcomes and responses even to common treatments, such as standard chemotherapy. This state-of-affairs has motivated the need for the comprehensive characterization of cancer phenotypes and fueled the generation of large omics datasets, comprising multiple omics data reported for the same patients, which might now allow us to start deciphering cancer heterogeneity and implement personalized therapeutic strategies. In this work, we performed the analysis of four cancer types obtained from the latest efforts by The Cancer Genome Atlas, for which seven distinct omics data were available for each patient, in addition to curated clinical outcomes. We performed a uniform pipeline for raw data preprocessing and adopted the Cancer Integration via MultIkernel LeaRning (CIMLR) integrative clustering method to extract cancer subtypes. We then systematically review the discovered clusters for the considered cancer types, highlighting novel associations between the different omics and prognosis.