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      The inclusion of diagnostics in national health insurance schemes in Cambodia, India, Indonesia, Nepal, Pakistan, Philippines and Viet Nam

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          Abstract

          The Lancet Commission on Diagnostics highlighted a huge gap in access to diagnostic testing even for basic tests, particularly at the primary care level, and emphasised the need for countries to include diagnostics as part of their universal health coverage benefits packages. Despite the poor state of diagnostic-related services in low-income and middle-income countries (LMICs), little is known about the extent to which diagnostics are included in the health benefit packages. We conducted an analysis of seven Asian LMICs—Cambodia, India, Indonesia, Nepal, Pakistan, Philippines, Viet Nam—to understand this issue. We conducted a targeted review of relevant literature and applied a health financing framework to analyse the benefit packages available in each government-sponsored scheme. We found considerable heterogeneity in country approaches to diagnostics. Of the seven countries, only India has developed a national essential diagnostics list. No country presented a clear policy rationale on the inclusion of diagnostics in their scheme and the level of detail on the specific diagnostics which are covered under the schemes was also generally lacking. Government-sponsored insurance expansion in the eligible populations has reduced the out-of-pocket health payment burden in many of the countries but overall, there is a lack of access, availability and affordability for diagnostic-related services.

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          The Lancet Commission on diagnostics: transforming access to diagnostics

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            Status and determinants of enrollment and dropout of health insurance in Nepal: an explorative study

            Background Compared to other countries in the South Asia Nepal has seen a slow progress in the coverage of health insurance. Despite of a long history of the introduction of health insurance (HI) and a high priority of the government of Nepal it has not been able to push rapidly its social health insurance to its majority of the population. There are many challenges while to achieve universal health insurance in Nepal ranging from existing policy paralysis to program operation. This study aims to identify the enrollment and dropout rates of health insurance and its determinants in selected districts of Nepal. Methods The study was conducted while using a mixed method including both quantitative and qualitative approaches. Numerical data related to enrollment and dropout rates were taken from Health Insurance Board (HIB) of Nepal. For the qualitative data, three districts, Bardiya, Chitwan, and Gorkha of Nepal were selected purposively. Enrollment assistants (EA) of social health insurance program were taken as the participants of study. Focus group discussions (FGD) were arranged with the selected EAs using specific guidelines along with unstructured questions. The results from numerical data and focus group discussions are synthesized and presented accordingly. Results The findings of the study suggested variation in enrollment and dropout of health insurance in the districts. Enrollment coverage was 13,545 (1%), 249,104 (5%), 1,159,477 (9%) and 1,676,505 (11%) from 2016 to 2019 among total population and dropout rates were 9121(67%), 110,885 (44%) and 444,967 (38%) among total enrollment from 2016 to 2018 respectively. Of total coverage, more than one-third proportion was subsidy enrollment—free enrollment for vulnerable groups. The population characteristics of unwilling and dropout in social health insurance came from relatively well-off families, government employees, businessman, migrants’ people, some local political leaders as well as the poor class families. The major determinants of poor enrollment and dropout were mainly due to unavailability of enough drugs, unfriendly behavior of health workers, and indifferent behavior of the care personnel to the insured patients in health care facilities and prefer to take health service in private clinic for their own benefits. The long maturation time to activate health service, limited health package and lack of copayment in different types of health care were the factors related to inefficient program and policy implementation. Conclusion There is a high proportion of dropout and subsidy enrollment, the key challenge for sustainability of health insurance program in Nepal. Revisiting of existing HI policy on health care packages, more choices on copayment, capacity building of enrollment assistants and better coordination between health insurance board and health care facilities can increase the enrollment and minimize the dropout.
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              Who benefits from healthcare spending in Cambodia? Evidence for a universal health coverage policy

              Abstract Cambodia’s healthcare system has seen significant improvements in the last two decades. Despite this, access to quality care remains problematic, particularly for poor rural Cambodians. The government has committed to universal health coverage (UHC) and is reforming the health financing system to align with this goal. The extent to which the reforms have impacted the poor is not always clear. Using a system-wide approach, this study assesses how benefits from healthcare spending are distributed across socioeconomic groups in Cambodia. Benefit incidence analysis was employed to assess the distribution of benefits from health spending. Primary data on the use of health services and the costs associated with it were collected through a nationally representative cross-sectional survey of 5000 households. Secondary data from the 2012–14 Cambodia National Health Accounts and other official documents were used to estimate the unit costs of services. The results indicate that benefits from health spending at the primary care level in the public sector are distributed in favour of the poor, with about 32% of health centre benefits going to the poorest population quintile. Public hospital outpatient benefits are quite evenly distributed across all wealth quintiles, although the concentration index of −0.058 suggests a moderately pro-poor distribution. Benefits for public hospital inpatient care are substantially pro-poor. The private sector was significantly skewed towards the richest quintile. Relative to health need, the distribution of total benefits in the public sector is pro-poor while the private sector is relatively pro-rich. Looking across the entire health system, health financing in Cambodia appears to benefit the poor more than the rich but a significant proportion of spending remains in the private sector which is largely pro-rich. There is the need for some government regulation of the private sector if Cambodia is to achieve its UHC goals.
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                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2023
                21 July 2023
                : 8
                : 7
                : e012512
                Affiliations
                [1 ]Ringgold_507266Research Institute of the McGill University Health Centre , Montréal, Quebec, Canada
                [2 ]McGill International TB Centre , Montréal, Quebec, Canada
                [3 ]Ringgold_91635FIND , Geneva, Switzerland
                [4 ]departmentDepartment of Epidemiology & Biostats , Ringgold_5620McGill University , Montréal, Quebec, Canada
                [5 ]departmentResearch Center for Care and Control of Infectious Diseases (RC3ID) , Ringgold_61809Universitas Padjadjaran , Bandung, Jawa Barat, Indonesia
                [6 ]Friends for International TB Relief , Ho Chi Minh City, Vietnam
                [7 ]Ringgold_609706Interactive Research & Development , Singapore
                [8 ]Family Health International (FHI360) , Manila, Philippines
                [9 ]Woolcock Institute of Medical Research , Hanoi, Viet Nam
                [10 ]departmentFaculty of Medicine and Health , The University of Sydney , Syndey, New South Wales, Australia
                [11 ]Ringgold_3489World Health Organization , Lahore, Pakistan
                [12 ]departmentSchool of Epidemiology and Public Health , Ringgold_12365University of Ottawa Faculty of Medicine , Ottawa, Ontario, Canada
                [13 ]departmentFaculty of Management Studies , Ringgold_28742University of Delhi , New Delhi, India
                [14 ]LEADERS Nepal , Kathmandu, Nepal
                [15 ]departmentTB PPM Learning Network , Institute of Public Health , Bengaluru, India
                [16 ]departmentDepartment of Health Policy , London School of Economics and Political Science , London, UK
                Author notes
                [Correspondence to ] Dr Divya Srivastava; d.srivastava@ 123456lse.ac.uk
                Author information
                http://orcid.org/0000-0003-0464-3882
                http://orcid.org/0000-0003-3667-4536
                http://orcid.org/0000-0002-2089-2902
                http://orcid.org/0000-0003-0390-7874
                http://orcid.org/0000-0001-5135-3592
                Article
                bmjgh-2023-012512
                10.1136/bmjgh-2023-012512
                10364157
                37479500
                29d54fde-0304-4eeb-bdb9-867ecc08ff6a
                © World Health Organization 2023. Licensee BMJ.

                This is an open access article distributed under the terms of the Creative Commons Attribution IGO License ( CC BY NC 3.0 IGO), which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. In any reproduction of this article there should not be any suggestion that WHO or this article endorse any specific organization or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article’s original URL.

                History
                : 05 April 2023
                : 10 June 2023
                Funding
                Funded by: FIND Diagnostics;
                Categories
                Practice
                1506
                Custom metadata
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                diagnostics and tools,health insurance,health policy

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