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Virginia Wiseman - One of the best experts on this subject based on the ideXlab platform.
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equity in Health Care Financing in low and middle income countries a systematic review of evidence from studies using benefit and Financing incidence analyses
PLOS ONE, 2016Co-Authors: Augustine Asante, Virginia Wiseman, Jennifer Price, Andrew HayenAbstract:Introduction Health Financing reforms in low- and middle- income countries (LMICs) over the past decades have focused on achieving equity in Financing of Health Care delivery through universal Health coverage. Benefit and Financing incidence analyses are two analytical methods for comprehensively evaluating how well Health systems perform on these objectives. This systematic review assesses progress towards equity in Health Care Financing in LMICs through the use of BIA and FIA. 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.
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economics of Health Care Financing the visible hand
2004Co-Authors: Cam Donaldson, Karen Gerard, Stephen Jan, Craig Mitton, Virginia WisemanAbstract:PART 1 MARKETS AND MARKET FAILURE IN Health Care - Health Care Financing Reforms: Moving into the 1990s - Markets and Health Care - Market Failure in Health Care - PART 2 Health Care SYSTEMS AND THEIR OBJECTIVES - Alternatives for Funding Health Care - Economic Objectives of Health Care - PART 3 A REVIEW OF EMPIRICAL FINDINGS - Countering Consumer Moral Hazard - Countering Doctor Moral Hazard - Countering Moral Hazard in the Hospital Sector - Achieving Equity - PART 4 FUTURE CHALLENGES - Future Considerations: Setting the Health Care Budget - Health Care Financing Reforms: Challenges for the 1990s - References - Index
Gemini Mtei - One of the best experts on this subject based on the ideXlab platform.
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predicting consumption expenditure for the analysis of Health Care Financing equity in low income countries a comparison of approaches
Social Indicators Research, 2015Co-Authors: Gemini Mtei, Josephine Borghi, Kara HansonAbstract:The analysis of equity in the distribution of Health Care payments requires nationally representative income and expenditure surveys, containing information on Health Care payments and ability to pay. Such national household surveys in developing countries collect limited information on out-of-pocket payments for Health Care but comprehensive information on household consumption expenditure (a proxy of income). There are also limited nationally representative Health surveys to conduct equity analyses requiring an administration of small Health-specific surveys to collect detailed information on Health Care payments. However, collecting household expenditure is expensive and time . This study compares quantile regression to Ordinary Least Square in predicting consumption expenditure. Split sample method and cross validation tests are used to evaluate the prediction methodology. Unlike OLS, the quantile model does not distort the values of, the Gini index, the concentration index and the Kakwani index and is the preferred method for predicting consumption expenditure for Financing incidence analysis.
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equity in Financing and use of Health Care in ghana south africa and tanzania implications for paths to universal coverage
The Lancet, 2012Co-Authors: Anne Mills, Gemini Mtei, Suzan Makawia, John E Ataguba, James Akazili, Jo Borghi, Bertha Garshong, Bronwyn Harris, Jane Macha, Filip MeheusAbstract:Summary Background Universal coverage of Health Care is now receiving substantial worldwide and national attention, but debate continues on the best mix of Financing mechanisms, especially to protect people outside the formal employment sector. Crucial issues are the equity implications of different Financing mechanisms, and patterns of service use. We report a whole-system analysis—integrating both public and private sectors—of the equity of Health-system Financing and service use in Ghana, South Africa, and Tanzania. Methods We used primary and secondary data to calculate the progressivity of each Health-Care Financing mechanism, catastrophic spending on Health Care, and the distribution of Health-Care benefits. We collected qualitative data to inform interpretation. Findings Overall Health-Care Financing was progressive in all three countries, as were direct taxes. Indirect taxes were regressive in South Africa but progressive in Ghana and Tanzania. Out-of-pocket payments were regressive in all three countries. Health-insurance contributions by those outside the formal sector were regressive in both Ghana and Tanzania. The overall distribution of service benefits in all three countries favoured richer people, although the burden of illness was greater for lower-income groups. Access to needed, appropriate services was the biggest challenge to universal coverage in all three countries. Interpretation Analyses of the equity of Financing and service use provide guidance on which Financing mechanisms to expand, and especially raise questions over the appropriate Financing mechanism for the Health Care of people outside the formal sector. Physical and financial barriers to service access must be addressed if universal coverage is to become a reality. Funding European Union and International Development Research Centre.
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who pays and who benefits from Health Care an assessment of equity in Health Care Financing and benefit distribution in tanzania
Health Policy and Planning, 2012Co-Authors: Gemini Mtei, August Kuwawenaruwa, Suzan Makawia, Mariam Ally, Filip Meheus, Josephine BorghiAbstract:Little is known about Health system equity in Tanzania, whether in terms of distribution of the Health Care Financing burden or distribution of Health Care benefits. This study undertook a combined analysis of both Financing and benefit incidence to explore the distribution of Health Care benefits and Financing burden across socio-economic groups. A system-wide analysis of benefits was undertaken, including benefits from all providers irrespective of ownership. The analysis used the household budget survey (HBS) from 2001, the most recent nationally representative survey data publicly available at the time, to analyse the distribution of Health Care payments through user fees, Health insurance contributions [from the National Health Insurance Fund (NHIF) for the formal sector and the Community Health Fund (CHF), for the rural informal sector] and taxation. Due to lack of information on NHIF and CHF contributions in the HBS, a primary survey was administered to estimate CHF enrollment and contributions; assumptions were used to estimate NHIF contributions within the HBS. Data from the same household survey, administered to 2224 households in seven districts/councils, was used to analyse the distribution of Health Care benefits across socio-economic groups. The Health Financing system was mildly progressive overall, with income taxes and NHIF contributions being the most progressive Financing sources. Out-of-pocket payments and contributions to the CHF were regressive. The Health benefit distribution was fairly even but the poorest received a lower share of benefits relative to their share of need for Health Care. Public primary Care facility use was pro-poor, whereas higher level and higher cost facility use was generally pro-rich. We conclude that Health Financing reforms can improve equity, so long as integration of Health insurance schemes is promoted along with cross-subsidization and greater reliance on general taxation to finance Health Care for the poorest.
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methodological challenges in evaluating Health Care Financing equity in data poor contexts lessons from ghana south africa and tanzania
Advances in health economics and health services research, 2009Co-Authors: Josephine Borghi, Gemini Mtei, Filip Meheus, John E Ataguba, James Akazili, Clas Rehnberg, Di McintyreAbstract:Objective – Measurement of the incidence of Health Financing contributions across socio-economic groups has proven valuable in informing Health Care Financing reforms. However, there is little evidence as to how to carry out Financing incidence analysis (FIA) in lower income settings. We outline some of the challenges faced when carrying out a FIA in Ghana, Tanzania and South Africa and illustrate how innovative techniques were used to overcome data weaknesses in these settings. Methodology – FIA was carried out for tax, insurance and out-of-pocket (OOP) payments. The primary data sources were Living Standards Measurement Surveys (LSMS) and household surveys conducted in each of the countries; tax authorities and insurance funds also provided information. Consumption expenditure and a composite index of socio-economic status (SES) were used to assess Financing equity. Where possible conventional methods of FIA were applied. Numerous challenges were documented and solution strategies devised. Results – LSMS are likely to underestimate financial contributions to Health Care by individuals. For tax incidence analysis, reported income tax payments from secondary sources were severely under-reported. Income tax payers and shareholders could not be reliably identified. The use of income or consumption expenditure to estimate income tax contributions was found to be a more reliable method of estimating income tax incidence. Assumptions regarding corporate tax incidence had a huge effect on the progressivity of corporate tax and on overall tax progressivity. LSMS consumption categories did not always coincide with tax categories for goods subject to excise tax (e.g. wine and spirits were combined, despite differing tax rates). Tobacco companies, alcohol distributors and advertising agencies were used to provide more detailed information on consumption patterns for goods subject to excise tax by income category. There was little guidance on how to allocate fuel levies associated with ‘public transport’ use. Hence, calculations of fuel tax on public transport were based on individual expenditure on public transport, the average cost per kilometre and average rates of fuel consumption for each form of transport. For insurance contributions, employees will not report on employer contributions unless specifically requested to and are frequently unsure of their contributions. Therefore, we collected information on total Health insurance contributions from individual schemes and regulatory authorities. OOP payments are likely to be under-reported due to long recall periods; linking OOP expenditure and illness incidence questions – omitting preventive Care; and focusing on the last service used when people may have used multiple services during an illness episode. To derive more robust estimates of Financing incidence, we collected additional primary data on OOP expenditures together with insurance enrolment rates and associated payments. To link primary data to the LSMS, a composite index of SES was used in Ghana and Tanzania and non-durable expenditure was used in South Africa. Policy implications – We show how data constraints can be overcome for FIA in lower income countries and provide recommendations for future studies.
Luke B Connelly - One of the best experts on this subject based on the ideXlab platform.
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Health policy and equity of Health Care Financing in australia 1973 2010
Review of Income and Wealth, 2014Co-Authors: Mohammad Hajizadeh, Luke B Connelly, James Robert Gerard ButlerAbstract:Using data from Australian Taxation Statistics and Household Expenditure Surveys we analyze the distribution of Health Care Financing in Australia over almost four decades. We compute Kakwani Progressivity indices for four sources of Health Care Financing: general taxation, MediCare Levy payments, MediCare Levy Surcharge payments, and direct consumer payments, and estimate the effects of major policy changes on them. The results demonstrate that the first three of these sources of Health Care Financing are progressive in Australia, while the distribution of direct payments is regressive. Surprisingly, we find that neither the introduction of MediCare in Australia in 1984 nor the Extended MediCare Safety Net in 2004 had significant effects on the progressivity of Health Care Financing in Australia. By contrast, the Lifetime Cover scheme-introduced in 2000 to encourage people to buy and hold private Health insurance-had a progressive effect on Health Care Financing.
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Health policy and equity of Health Care Financing in australia 1973 2010
Review of Income and Wealth, 2014Co-Authors: Mohammad Hajizadeh, Luke B Connelly, James Robert Gerard ButlerAbstract:type="main"> Using data from Australian Taxation Statistics and Household Expenditure Surveys we analyze the distribution of Health Care Financing in Australia over almost four decades. We compute Kakwani Progressivity indices for four sources of Health Care Financing: general taxation, MediCare Levy payments, MediCare Levy Surcharge payments, and direct consumer payments, and estimate the effects of major policy changes on them. The results demonstrate that the first three of these sources of Health Care Financing are progressive in Australia, while the distribution of direct payments is regressive. Surprisingly, we find that neither the introduction of MediCare in Australia in 1984 nor the Extended MediCare Safety Net in 2004 had significant effects on the progressivity of Health Care Financing in Australia. By contrast, the Lifetime Cover scheme—introduced in 2000 to encourage people to buy and hold private Health insurance—had a progressive effect on Health Care Financing.
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equity of Health Care Financing in iran the effect of extending Health insurance to the uninsured
Oxford Development Studies, 2010Co-Authors: Mohammad Hajizadeh, Luke B ConnellyAbstract:This paper examines the progressivity of Health insurance premiums and consumer co-payments in Iran by calculating Kakwani Progressivity Indices using data from annual national household surveys between 1995/96 and 2006/07. During this period, the Urban Inpatient Insurance Scheme in 2000 and the Rural Health Insurance Scheme in 2005 extended Health insurance coverage in urban and rural areas. Unexpectedly, the results suggest that both of these initiatives had regressive impacts on the distribution of Health Care Financing in Iran, which could be explained by public sector activity having crowded out private sector charitable activity. Although this study does not address changes in the distribution of Health Care utilization, these results for Health Care Financing suggest the need for caution in the implementation of such programmes in low-income and middle-income countries. If charitable activity already results in the provision of Health Care to the poor at zero or low prices, public intervention may not improve the progressivity of Health Care Financing.
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equity of Health Care Financing in iran
MPRA Paper, 2009Co-Authors: Mohammad Hajizadeh, Luke B ConnellyAbstract:This study presents the rst analyses of the equity of Health Care Financing in Iran. Kakwani Progressivity Indices (KPIs) and concentration indices (CIs) are estimated using ten national household expenditure surveys, which were conducted in Iran from 1995/96 to 2004/05. The indices are used to analyze the progressivity of two sources of Health Care Financing: Health insurance premium payments and consumer co-payments (and the sum of these), for Iran as a whole, and for rural and urban areas of Iran, separately. The results suggest that Health insurance premium payments became more progressive over the study period; however the KPIs for consumer co-payments suggest that these are still mildly regressive or slightly progressive, depending upon whether household income or expenditure data are used to generate the indices. Interestingly, the Urban Inpatient Insurance Scheme (UIIS), which was introduced by the Iranian government in 2000 to extend insurance to uninsured urban dwellers, appears to have had a regressive impact on Health Care nancing, which is contrary to expectations. This result sounds a cautionary note about the potential for public programs to crowd out private sector, charitable activity, which was prevalent in Iran prior to the introduction of the UIIS.
Josephine Borghi - One of the best experts on this subject based on the ideXlab platform.
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predicting consumption expenditure for the analysis of Health Care Financing equity in low income countries a comparison of approaches
Social Indicators Research, 2015Co-Authors: Gemini Mtei, Josephine Borghi, Kara HansonAbstract:The analysis of equity in the distribution of Health Care payments requires nationally representative income and expenditure surveys, containing information on Health Care payments and ability to pay. Such national household surveys in developing countries collect limited information on out-of-pocket payments for Health Care but comprehensive information on household consumption expenditure (a proxy of income). There are also limited nationally representative Health surveys to conduct equity analyses requiring an administration of small Health-specific surveys to collect detailed information on Health Care payments. However, collecting household expenditure is expensive and time . This study compares quantile regression to Ordinary Least Square in predicting consumption expenditure. Split sample method and cross validation tests are used to evaluate the prediction methodology. Unlike OLS, the quantile model does not distort the values of, the Gini index, the concentration index and the Kakwani index and is the preferred method for predicting consumption expenditure for Financing incidence analysis.
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who pays and who benefits from Health Care an assessment of equity in Health Care Financing and benefit distribution in tanzania
Health Policy and Planning, 2012Co-Authors: Gemini Mtei, August Kuwawenaruwa, Suzan Makawia, Mariam Ally, Filip Meheus, Josephine BorghiAbstract:Little is known about Health system equity in Tanzania, whether in terms of distribution of the Health Care Financing burden or distribution of Health Care benefits. This study undertook a combined analysis of both Financing and benefit incidence to explore the distribution of Health Care benefits and Financing burden across socio-economic groups. A system-wide analysis of benefits was undertaken, including benefits from all providers irrespective of ownership. The analysis used the household budget survey (HBS) from 2001, the most recent nationally representative survey data publicly available at the time, to analyse the distribution of Health Care payments through user fees, Health insurance contributions [from the National Health Insurance Fund (NHIF) for the formal sector and the Community Health Fund (CHF), for the rural informal sector] and taxation. Due to lack of information on NHIF and CHF contributions in the HBS, a primary survey was administered to estimate CHF enrollment and contributions; assumptions were used to estimate NHIF contributions within the HBS. Data from the same household survey, administered to 2224 households in seven districts/councils, was used to analyse the distribution of Health Care benefits across socio-economic groups. The Health Financing system was mildly progressive overall, with income taxes and NHIF contributions being the most progressive Financing sources. Out-of-pocket payments and contributions to the CHF were regressive. The Health benefit distribution was fairly even but the poorest received a lower share of benefits relative to their share of need for Health Care. Public primary Care facility use was pro-poor, whereas higher level and higher cost facility use was generally pro-rich. We conclude that Health Financing reforms can improve equity, so long as integration of Health insurance schemes is promoted along with cross-subsidization and greater reliance on general taxation to finance Health Care for the poorest.
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methodological challenges in evaluating Health Care Financing equity in data poor contexts lessons from ghana south africa and tanzania
Advances in health economics and health services research, 2009Co-Authors: Josephine Borghi, Gemini Mtei, Filip Meheus, John E Ataguba, James Akazili, Clas Rehnberg, Di McintyreAbstract:Objective – Measurement of the incidence of Health Financing contributions across socio-economic groups has proven valuable in informing Health Care Financing reforms. However, there is little evidence as to how to carry out Financing incidence analysis (FIA) in lower income settings. We outline some of the challenges faced when carrying out a FIA in Ghana, Tanzania and South Africa and illustrate how innovative techniques were used to overcome data weaknesses in these settings. Methodology – FIA was carried out for tax, insurance and out-of-pocket (OOP) payments. The primary data sources were Living Standards Measurement Surveys (LSMS) and household surveys conducted in each of the countries; tax authorities and insurance funds also provided information. Consumption expenditure and a composite index of socio-economic status (SES) were used to assess Financing equity. Where possible conventional methods of FIA were applied. Numerous challenges were documented and solution strategies devised. Results – LSMS are likely to underestimate financial contributions to Health Care by individuals. For tax incidence analysis, reported income tax payments from secondary sources were severely under-reported. Income tax payers and shareholders could not be reliably identified. The use of income or consumption expenditure to estimate income tax contributions was found to be a more reliable method of estimating income tax incidence. Assumptions regarding corporate tax incidence had a huge effect on the progressivity of corporate tax and on overall tax progressivity. LSMS consumption categories did not always coincide with tax categories for goods subject to excise tax (e.g. wine and spirits were combined, despite differing tax rates). Tobacco companies, alcohol distributors and advertising agencies were used to provide more detailed information on consumption patterns for goods subject to excise tax by income category. There was little guidance on how to allocate fuel levies associated with ‘public transport’ use. Hence, calculations of fuel tax on public transport were based on individual expenditure on public transport, the average cost per kilometre and average rates of fuel consumption for each form of transport. For insurance contributions, employees will not report on employer contributions unless specifically requested to and are frequently unsure of their contributions. Therefore, we collected information on total Health insurance contributions from individual schemes and regulatory authorities. OOP payments are likely to be under-reported due to long recall periods; linking OOP expenditure and illness incidence questions – omitting preventive Care; and focusing on the last service used when people may have used multiple services during an illness episode. To derive more robust estimates of Financing incidence, we collected additional primary data on OOP expenditures together with insurance enrolment rates and associated payments. To link primary data to the LSMS, a composite index of SES was used in Ghana and Tanzania and non-durable expenditure was used in South Africa. Policy implications – We show how data constraints can be overcome for FIA in lower income countries and provide recommendations for future studies.
Mohammad Hajizadeh - One of the best experts on this subject based on the ideXlab platform.
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Health policy and equity of Health Care Financing in australia 1973 2010
Review of Income and Wealth, 2014Co-Authors: Mohammad Hajizadeh, Luke B Connelly, James Robert Gerard ButlerAbstract:Using data from Australian Taxation Statistics and Household Expenditure Surveys we analyze the distribution of Health Care Financing in Australia over almost four decades. We compute Kakwani Progressivity indices for four sources of Health Care Financing: general taxation, MediCare Levy payments, MediCare Levy Surcharge payments, and direct consumer payments, and estimate the effects of major policy changes on them. The results demonstrate that the first three of these sources of Health Care Financing are progressive in Australia, while the distribution of direct payments is regressive. Surprisingly, we find that neither the introduction of MediCare in Australia in 1984 nor the Extended MediCare Safety Net in 2004 had significant effects on the progressivity of Health Care Financing in Australia. By contrast, the Lifetime Cover scheme-introduced in 2000 to encourage people to buy and hold private Health insurance-had a progressive effect on Health Care Financing.
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Health policy and equity of Health Care Financing in australia 1973 2010
Review of Income and Wealth, 2014Co-Authors: Mohammad Hajizadeh, Luke B Connelly, James Robert Gerard ButlerAbstract:type="main"> Using data from Australian Taxation Statistics and Household Expenditure Surveys we analyze the distribution of Health Care Financing in Australia over almost four decades. We compute Kakwani Progressivity indices for four sources of Health Care Financing: general taxation, MediCare Levy payments, MediCare Levy Surcharge payments, and direct consumer payments, and estimate the effects of major policy changes on them. The results demonstrate that the first three of these sources of Health Care Financing are progressive in Australia, while the distribution of direct payments is regressive. Surprisingly, we find that neither the introduction of MediCare in Australia in 1984 nor the Extended MediCare Safety Net in 2004 had significant effects on the progressivity of Health Care Financing in Australia. By contrast, the Lifetime Cover scheme—introduced in 2000 to encourage people to buy and hold private Health insurance—had a progressive effect on Health Care Financing.
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equity of Health Care Financing in iran the effect of extending Health insurance to the uninsured
Oxford Development Studies, 2010Co-Authors: Mohammad Hajizadeh, Luke B ConnellyAbstract:This paper examines the progressivity of Health insurance premiums and consumer co-payments in Iran by calculating Kakwani Progressivity Indices using data from annual national household surveys between 1995/96 and 2006/07. During this period, the Urban Inpatient Insurance Scheme in 2000 and the Rural Health Insurance Scheme in 2005 extended Health insurance coverage in urban and rural areas. Unexpectedly, the results suggest that both of these initiatives had regressive impacts on the distribution of Health Care Financing in Iran, which could be explained by public sector activity having crowded out private sector charitable activity. Although this study does not address changes in the distribution of Health Care utilization, these results for Health Care Financing suggest the need for caution in the implementation of such programmes in low-income and middle-income countries. If charitable activity already results in the provision of Health Care to the poor at zero or low prices, public intervention may not improve the progressivity of Health Care Financing.
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equity of Health Care Financing in iran
MPRA Paper, 2009Co-Authors: Mohammad Hajizadeh, Luke B ConnellyAbstract:This study presents the rst analyses of the equity of Health Care Financing in Iran. Kakwani Progressivity Indices (KPIs) and concentration indices (CIs) are estimated using ten national household expenditure surveys, which were conducted in Iran from 1995/96 to 2004/05. The indices are used to analyze the progressivity of two sources of Health Care Financing: Health insurance premium payments and consumer co-payments (and the sum of these), for Iran as a whole, and for rural and urban areas of Iran, separately. The results suggest that Health insurance premium payments became more progressive over the study period; however the KPIs for consumer co-payments suggest that these are still mildly regressive or slightly progressive, depending upon whether household income or expenditure data are used to generate the indices. Interestingly, the Urban Inpatient Insurance Scheme (UIIS), which was introduced by the Iranian government in 2000 to extend insurance to uninsured urban dwellers, appears to have had a regressive impact on Health Care nancing, which is contrary to expectations. This result sounds a cautionary note about the potential for public programs to crowd out private sector, charitable activity, which was prevalent in Iran prior to the introduction of the UIIS.
