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.

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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.

BackgroundEnsuring 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.MethodsThe 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.ResultsThe 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.ConclusionThe 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.

Background: The Republic of Mauritius had a total of 422,567 disability-adjusted life years (DALYs) from all causes in 2019. This study aimed to estimate the monetary value of DALYs lost in 2019 from all causes in Mauritius and those projected to be lost in 2030; and to estimate the monetary value of DALYs savings in 2030 if Mauritius were to attain the national targets related to five targets of the United Nations Sustainable Development Goal 3 on good health and well-being. Methods: The human capital approach was used to monetarily value DALYs lost from 157 causes in 2019. The monetary value of DALYs lost in 2019 from each cause was calculated from the product of net gross domestic product (GDP) per capita in Mauritius and the number of DALYs lost from a specific cause. The percentage reductions implied in the SDG3 targets were used to project the monetary values of DALYs expected in 2030. The potential savings equal the monetary value of DALYs lost in 2019 less the monetary value of DALYs expected in 2030. Results:  The DALYs lost in 2019 had a total monetary value of Int$ 9.46 billion and a mean value of Int$ 22,389 per DALY. Of this amount, 84.2% resulted from non-communicable diseases; 8.7% from communicable, maternal, neonatal, and nutritional diseases; and 7.1% from injuries. Full attainment of national targets related to the five SDG3 targets would avert DALYs losses to the value of Int$ 2.4 billion. Conclusions: Diseases and injuries cause a significant annual DALYs loss with substantive monetary value. Fully achieving the five SDG3 targets could save Mauritius nearly 8% of its total GDP in 2019. To achieve such savings, Mauritius needs to strengthen further the national health system, other systems that tackle the social determinants of health, and the national health research system.