METHODS AND FINDINGS: Key electronic databases including Medline, Embase, Scopus, Global Health, CinAHL, EconLit and Business Source Premier were searched. We also searched the grey literature, specifically websites of leading organizations supporting health care in LMICs. Only studies using benefit incidence analysis (BIA) and/or financing incidence analysis (FIA) as explicit methodology were included. A total of 512 records were obtained from the various sources. The full texts of 87 references were assessed against the selection criteria and 24 were judged appropriate for inclusion. Twelve of the 24 studies originated from sub-Saharan Africa, nine from the Asia-Pacific region, two from Latin America and one from the Middle East. The evidence points to a pro-rich distribution of total health care benefits and progressive financing in both sub-Saharan Africa and Asia-Pacific. In the majority of cases, the distribution of benefits at the primary health care level favoured the poor while hospital level services benefit the better-off. A few Asian countries, namely Thailand, Malaysia and Sri Lanka, maintained a pro-poor distribution of health care benefits and progressive financing.
CONCLUSION: Studies evaluated in this systematic review indicate that health care financing in LMICs benefits the rich more than the poor but the burden of financing also falls more on the rich. There is some evidence that primary health care is pro-poor suggesting a greater investment in such services and removal of barriers to care can enhance equity. The results overall suggest that there are impediments to making health care more accessible to the poor and this must be addressed if universal health coverage is to be a reality.
METHODS: We selected two medicines on the 2013 Thai national list of essential medicines (NLEM) [letrozole and imatinib] and three unlisted medicines for the same indications [trastuzumab, nilotinib and dasatinib]. We created timelines of access policies and programs for these products based on scientific and grey literature. Using IMS Health sales data, we described the trajectories of sales volumes of the study medicines between January 2001 and December 2012. We compared estimated average numbers of patients treated before and after the implementation of policies and programs for each product.
RESULTS: Different stakeholders implemented multiple interventions to increase access to the study medicines for different patient populations. During 2007-2009, the Thai Government created a special NLEM category with different coverage requirements for payers and issued compulsory licenses; payers negotiated prices with manufacturers and engaged in pooled procurement; pharmaceutical companies expanded patient assistance programs and lowered prices in different ways. Compared to before the interventions, estimated numbers of patients treated with each medicine increased significantly afterwards: for letrozole from 645 (95% CI 366-923) to 3683 (95% CI 2,748-4,618); for imatinib from 103 (95% CI 72-174) to 350 (95% CI 307-398); and for trastuzumab from 68 (95% CI 45-118) to 412 (95% CI 344-563).
CONCLUSIONS: Government, payers, and manufacturers implemented multi-pronged approaches to facilitate access to targeted cancer therapies for the Thai population, which differed by medicine. Routine monitoring is needed to assess clinical and economic impacts of these strategies in the health system.
METHODS: In this cross-sectional study, we include 196 homeless people aged above 18 years, Malaysian who were able to communicate with interviewers, and respondents who were not aggressive. These respondents were transits at Pusat Transit Gelandangan Kuala Lumpur and Anjung Singgah Kuala Lumpur and were available during interview sessions. They were selected via simple random sampling and were interviewed via face to face guided interviews using a validated structured questionnaire. Data were analysed descriptively, as well as using bivariate and multivariate analysis to explore the associated factors.
RESULTS: The study showed that 57.7% homeless utilized the health services with only 37.8% assessed government health services. Only 42.5% of the respondents use their own money and 46.9% received aids to finance their health. Major influencing factors that influence homeless people to use their own money for health services were education level, income and disability, with adjusted OR (95% CI) of 3.15 (1.07-9.25), 0.08 (0.029-3.07) and 0.05 (0.003-0.88) while p value was 0.037, health services were income and those who took drugs with adjusted OR (95% CI) of 6.50 (2.30-18.39), and 0.33 (0.11-0.95) while p value was health care accessibility in Malaysia.
STUDY DESIGN: Cost-effectiveness analysis.
SETTING: Bangladesh, Cambodia, India, Indonesia, Nepal, Pakistan, Philippines, and Sri Lanka participated in the study.
SUBJECTS AND METHODS: Costs were obtained from experts in each country with known costs and published data, with estimation when necessary. A disability-adjusted life-years model was applied with 3% discounting and 10-year length of analysis. A sensitivity analysis was performed to evaluate the effect of device cost, professional salaries, annual number of implants, and probability of device failure. Cost-effectiveness was determined with the World Health Organization standard of cost-effectiveness ratio per gross domestic product (CER/GDP) per capita <3.
RESULTS: Deaf education was cost-effective in all countries except Nepal (CER/GDP, 3.59). CI was cost-effective in all countries except Nepal (CER/GDP, 6.38) and Pakistan (CER/GDP, 3.14)-the latter of which reached borderline cost-effectiveness in the sensitivity analysis (minimum, maximum: 2.94, 3.39).
CONCLUSION: Deaf education and CI are largely cost-effective in participating Asian countries. Variation in CI maintenance and education-related costs may contribute to the range of cost-effectiveness ratios observed in this study.