An assessment of the performance of the national health research system in Mauritius.

BACKGROUND: The goal of universal health coverage (UHC) is that every individual has access to high-quality health services without running the consequences of financial hardship. The World health report 2013 "Research for universal health coverage" states a performant National Health Research Systems (NHRS) can contribute by providing solutions to challenges encountered in advancing towards UHC by 2030. Pang et al. define a NHRS as the people, institutions, and activities whose primary aim is to generate and promote utilization of high-quality knowledge that can be used to promote, restore, and/or maintain the health status of populations. The WHO Regional Committee for Africa (RC) adopted a resolution in 2015 urging member states to strengthen their NHRS to facilitate production and utilization of evidence in policy development, planning, product development, innovation, and decision-making. This study aimed to calculate NHRS barometer scores for Mauritius in 2020, identify the gaps in NHRS performance, and recommend interventions for boosting the Mauritius NHRS in the pursuit of UHC. METHODS: The study used a cross-sectional survey design. A semi-structured NHRS questionnaire was administered and complemented with a review of documents archived in pertinent Mauritius Government Ministries, universities, research-oriented departments, and non-governmental organizations websites. The African NHRS barometer developed in 2016 for countries to monitor the RC resolution implementation was applied. The barometer consists of four NHRS functions (leadership and governance, developing and sustaining resources, producing and utilizing research, financing research for health [R4H]), and 17 sub-functions, e.g., existence of a national policy on research for health (R4H), presence of a Mauritius Research and Innovation Council (MRIC), existence of knowledge translation platform. RESULTS: In 2020, Mauritius had an overall average NHRS barometer score of 60.84%. The four NHRS functions average indices were 50.0% for leadership and governance, 77.0% for developing and sustaining resources, 52.0% for producing and utilizing R4H, and 58.2% for financing R4H. CONCLUSION: The performance of NHRS could be improved through the development of a national R4H policy, strategic plan, prioritized agenda, and national multi-stakeholder health research management forum. Furthermore, increased funding for the NHRS may nurture the human resources for health research capacities, hence the number of pertinent publications and health innovations.

Improving equity in the distribution and financing of health services in Mauritius, a small island state with deeply rooted welfare state standards.

BACKGROUND: Ensuring benefits of free healthcare services are accessible to those in need is essential to achieve universal health coverage (UHC). Mauritius has sustained a welfare state over four decades with free health services in all public facilities. However, paradoxically, the national UHC service coverage index stood at only 63 in 2017. An assessment of who benefits from health interventions is, therefore, vital to shape future health financing strategies. METHODS: The study applied benefit incidence analysis (BIA) to understand the distribution of healthcare utilisation and spending in comparison to income distribution. Also, a financial incidence analysis (FIA) was conducted to assess the progressivity of the health financing systems. Data from the national survey on household out-of-pocket (OOP) expenditure for health were used for the purpose of BIA and FIA. Concentration curves and concentration indices (CI) were nationally estimated and disaggregated to rural/urban levels. Kakwani index (KI) was calculated to assess the progressivity of private healthcare financing. RESULTS: The CI for outpatient, inpatient and day care within the public health sector is estimated at -0.33, -0.14 and -0.14, respectively. Overall, CI in the public sector is -0.26. Benefit distribution in the private sector is pro-rich with CI of 0.27. Healthcare financing is regressive as demonstrated by a KI of -0.004, with the poorest population groups contributing a large share, in terms of taxes and OOP, to finance the health system. CONCLUSION: The BIA posits that government spending on public healthcare has resulted in significant pro-poor services distribution. This is largely offset by pro-rich distribution in the private sector. Thus, implying health financing strategies must be reviewed to promote financial protection against catastrophic health payments and bolster efforts to improve UHC service coverage index and achieve UHC Target 3.8 under Sustainable Development Goal 3.

The Discounted Money Value of Human Life Losses Associated With COVID-19 in Mauritius.

Background: Mauritius along with other 12 countries in the African Region was identified at the early start of the COVID-19 pandemic as being at high risk due to high volume of international travel, high prevalence of non-communicable diseases and co-morbidities, high population density and significant share of population over 60 years (16%). The objective of this study was to estimate the total discounted money value of human life losses (TDMVCLMAURITIUS ) associated with COVID-19 in Mauritius. Methods: The human capital approach (HCA) was used to estimate the TDMVCLMAURITIUS of the 10 human life losses linked with COVID-19 in Mauritius as of 16 October 2020. The HCA model was estimated with the national life expectancy of 75.51 years and a discount rate of 3%. A sensitivity analysis was performed assuming (a) 5 and 10% discount rates, and (b) the average world life expectancy of 73.2 years, and the world highest life expectancy of 88.17 years. Results: The money value of human lives lost to COVID-19, at a discounted rate of 3%, had an estimated TDMVCLMAURITIUS of Int$ 3,120,689, and an average of Int$ 312,069 per human life lost. Approximately 74% of the TDMVCLMAURITIUS accrued to persons aged between 20 and 59 years. Reanalysis of the model with 5 and 10% discount rates, holding national life expectancy constant, reduced the TDMVCLMAURITIUS by 19.0 and 45.5%, respectively. Application of the average world life expectancy at 3% discount rate reduced TDMVCLMAURITIUS by 13%; and use of the world highest life expectancy at 3% discount rate increased TDMVCLMAURITIUS by 50%. Conclusions: The average discounted money value per human life loss associated with COVID-19 is 12-fold the per capita GDP for Mauritius. All measures implemented to prevent widespread community transmission of COVID-19 may have saved the country 837 human lives worth Int$258,080,991. This evidence, conjointly with human rights arguments, calls for increased investments to bridge the existing gaps for achieving universal health coverage by 2030.

Improving public hospital efficiency and fiscal space implications: the case of Mauritius.

BACKGROUND: General Government Health Expenditure (GGHE) in Mauritius accounted for only 10% of General Government Expenditure for the fiscal year 2018. This is less than the pledge taken under the Abuja 2001 Declaration to allocate at least 15% of national budget to the health sector. The latest National Health Accounts also urged for an expansion in the fiscal space for health. As public hospitals in Mauritius absorb 70% of GGHE, maximising returns of hospitals is essential to achieve Universal Health Coverage. More so, as Mauritius is bracing for its worst recession in 40 years in the aftermath of the COVID-19 pandemic public health financing will be heavily impacted. A thorough assessment of hospital efficiency and its implications on effective public health financing and fiscal space creation is, therefore, vital to inform ongoing health reform agenda. OBJECTIVES: This paper aims to examine the trend in hospital technical efficiency over the period 2001-2017, to measure the elasticity of hospital output to changes in inputs variables and to assess the impact of improved hospital technical efficiency in terms of fiscal space creation. METHODS: Annual health statistics released by the Ministry of Health and Wellness and national budget of the Ministry of Finance, Economic Planning and Development were the principal sources of data. Applying Stochastic Frontier Analysis, technical efficiency of public regional hospitals was estimated under Cobb-Douglas, Translog and Multi-output distance functions, using STATA 11. Hospital beds, doctors, nurses and non-medical staff were used as input variables. Output variable combined inpatients and outpatients seen at Accident Emergency, Sorted and Unsorted departments. Efficiency scores were used to determine potential efficiency savings and fiscal space creation. FINDINGS: Mean technical efficiency scores, using the Cobb Douglas, Translog and Multi-output functions, were estimated at 0.83, 0.84 and 0.89, respectively. Nurses and beds are the most important factors in hospital production, as a 1% increase in the number of beds and nurses, result in an increase in hospital outputs by 0.73 and 0.51%, respectively. If hospitals are to increase their inputs by 1%, their outputs will increase by 1.16%. Hospital output process has an increasing return to scale. With technical efficiencies improving to scores of 0.95 and 1.0 in 2021-2022, potential savings and fiscal space creation at hospital level, would amount to MUR 633 million (US$ 16.2 million) and MUR 1161 million (US$ 29.6 million), respectively. CONCLUSION: Fiscal space creation through full technical efficiency, is estimated to represent 8.9 and 9.2% of GGHE in fiscal year 2021-2022 and 2022-2023, respectively. This will allow without any restrictions the funding of the national response for HIV, vaccine preventable diseases as well as building a resilient health system to mitigate impact of emerging infectious diseases as experienced with COVID-19.

Impact of out of pocket payments on financial risk protection indicators in a setting with no user fees: the case of Mauritius.

BACKGROUND: Mauritius embraces principles of a welfare state with free health care at point of use in any public facilities. However, the health financing landscape changed in 2007 when Private Health Expenditure (PvtHE) surpassed General Government Health Expenditure. PvtHE is predominately out of pocket (OOP) with only 3.4% related to premiums for private insurance. In 2014, Household OOP Expenditure on health accounted for 52.8% of total health expenditure. OOP is known to be regressive and to impact negatively on households' living standards. OBJECTIVES: This paper aims to examine trends in OOP in Mauritius, to assess its impacts through an analysis of key indicators of financial protection, namely catastrophic health expenditure (CHE) and impoverishment due to OOP health expenditure. It also aims to predict core determinants of CHEs. METHODS: Household Budget Surveys (HBS) of 2001/2002, 2006/2007 and 2012 were the primary source data. CHE and impoverishment were used to assess financial hardships resulting from OOP health payments. The incidence of CHE was estimated at three threshold levels (10,25 and 40%), using the budget share and the capacity to pay approaches. Impoverishment due to OOP was measured by changes in the incidence of poverty and intensity of poverty using the US$ 3.1 international poverty line. Logistic regression analysis was used to identify determinants of CHE. FINDINGS: Household CHE increased from 5.78% in 2001/02 to 8.85% in 2012 and 0.61% in 2001/02 to 1.25% in 2012, for 10 and 40% thresholds, respectively. The incidence of CHE was significantly higher in urban areas compared to rural areas. The highest levels of CHEs were among households' heads, who are retired rising from 1.62% in 2001/02 to 3.71% in 2012, followed by households' head who are widowed from 2.29% in 2001/02 to 2.63% in 2012 and homemakers from 2.12% in 2001/02 to 2.57% in 2012 at the 40% threshold. The share of households pushed below the poverty line due to OOP dropped from 0.4% in 2001/02 to 0.2% in 2006/07 before rising to 0.34% in 2012. In 2012, poverty gap occurred only among households under poorest quintile 1 (0.24%) and quintile 2 (0.03%). Overall poverty gap dropped from 0.08% in 2001/02 to 0.05% in 2012. Logistic regression analysis revealed that the odds ratio of facing CHE were significant only among households with heads being retired and with a presence of an elderly member in the household. CONCLUSION: Despite the rise in incidence of CHE between 2001 and 2012 the impact of OOP on the level of impoverishment and poverty gap has not been significant.