Efficiency and productivity of health systems in prevention and control of non-communicable diseases in China, 2008-2015

This article examines the health system performance impact of China's new round of healthcare reform adopted in 2009. Specifically, we evaluated productivity and efficiency of health production pre- and post-reform period, compared the effects across all the 31 provinces of mainland China and identified potential determinants. As a major source of disability and premature mortality in China, non-communicable diseases (NCDs) had been the focus of our analysis, and the period during 2008-2015 was considered to allow enough time for the policy to have meaningful impact on the country's health system. Productivity and efficiency performance were analyzed using a bootstrapping data envelopment analysis (DEA) and the Malmquist productivity index (MPI) techniques, while a Tobit regression technique was used to identify determinants of inefficiency. We find that after the reform efficiency and productivity had declined across large number of provinces. Mean overall technical efficiency (OTE) post 2009 was about 30% lower than the potential maximum capacity, while productivity also fell at a rate of 7.57% per annum. Trends in productivity and efficiency performance were largely linked to patterns of scale of technological change observed during the study period. The findings suggest that efficiency and productivity can be improved through enhancing financial security, optimizing health resource allocation, particularly between human resources for health and hospital beds, and expanding cost-effective technology within the health sector. Better urban planning practices and investment in education were also found to contribute to improved efficiency of NCDs services.

Assessing the efficiency of health systems in achieving the universal health coverage goal: evidence from Sub-Saharan Africa

OBJECTIVE

Universal health coverage (UHC) is a major pathway to save many people from catastrophic and impoverishing healthcare spending and address the inequality in health and healthcare. The objective of this paper is to assess the efficiency with which health systems in sub-Saharan Africa (SSA) are utilizing healthcare resources to progress towards achieving the UHC goal by 2030.

METHODS

The study followed the guidelines proposed by the World Health Organization (WHO) and World Bank joint UHC monitoring framework and the computational operationalization approach proposed by Wagstaff et al. (2015) to estimate the UHC index for each of the 30 selected SSA countries. The bootstrapping output-oriented data envelopment analysis (DEA) was used to estimate the bias-corrected technical efficiency scores and examine the environmental factors that influence health system efficiency.

RESULTS

The estimated UHC levels ranged from a minimum of 52% to a maximum of 81% [Formula: see text] with a median coverage of 66%. The average bias-corrected efficiency score was 0.81 [Formula: see text]. The study found that education, governance quality, public health spending, external health funding, and prepayment arrangements that pool funds for health had a positive significant effect on health system efficiency in improving UHC, while out-of-pocket payment had a negative impact.

CONCLUSION

The results show that health systems in SSA can potentially enhance UHC levels by at least 19% with existing healthcare resources if best practices are adopted. Policymakers should aim at improving education, good governance, and healthcare financing architecture to reduce out-of-pocket payments and over-reliance on donor funding for healthcare to achieve UHC.

Efficiency evaluation of 28 health systems by MCDA and DEA

BACKGROUND

Policymakers, who are constantly discussing growing health expenditures, should know whether the health system is efficient. We can provide them with such information through international health system efficiency evaluations. The main objectives of this study are: (a) to evaluate the efficiency of health systems in 28 developed countries by multiple-criteria decision analysis (MCDA) and data envelopment analysis (DEA) and (b) to identify reasonable benchmark countries for the Czech Republic, for which we collect information on the relative importance of health system inputs and outputs.

METHODS

We used MCDA and DEA to evaluate the efficiency of the health systems of 28 developed countries. The models included four health system inputs (health expenditure as a relative share of GDP, the number of physicians, nurses, and hospital beds) and three health system outputs (life expectancy at birth, healthy life expectancy, and infant mortality rate). The sample covers 27 OECD countries and Russia, which is also included in the OECD database. To determine the input and output weights, we used a questionnaire sent to health policy experts in the Czech Republic.

RESULTS

We obtained subjective information on the relative importance of the health system inputs and outputs from 27 Czech health policy experts. We evaluated health system efficiency using four MCDA and two DEA models. According to the MCDA models, Turkey, Poland, and Israel were found to have efficient health systems. The Czech Republic ranked 16th, 19th, 15th, and 17th. The benchmark countries for the Czech Republic's health system were Israel, Estonia, Luxembourg, Italy, the UK, Spain, Slovenia, and Canada. The DEA model with the constant returns to scale identified four technically efficient health systems: Turkey, the UK, Canada, and Sweden. The Czech Republic was found to be one of the worst-performing health systems. The DEA model with the variable returns to scale identified 15 technically efficient health systems. We found that efficiency results are quite robust. With two exceptions, the Spearman rank correlations between each pair of models were statistically significant at the 0.05 level.

CONCLUSIONS

During the model formulation, we investigated the pitfalls of efficiency measurement in health care and used several practical solutions. We consider MCDA and DEA, above all, as exploratory methods, not methods providing definitive answers.

Effects of healthcare financing policy tools on health system efficiency: Evidence from sub-Saharan Africa

Background

Evidence shows high levels of catastrophic and impoverishing healthcare expenditure among households in sub-Saharan Africa (SSA). The way healthcare is financed has an impact on how well a health system performs its functions and achieves its objectives. This study aims to examine the effect of healthcare financing policy tools on health system efficiency.

Method

The study classifies 46 sub-Saharan African (SSA) countries into four groups of health systems sharing similar healthcare financing strategies. A two-stage and one-stage stochastic frontier analysis (SFA) and Tobit regression techniques were employed to assess the impact of healthcare financing policy variables on health system efficiency. Data from the selected 46 SSA countries from 2000 to 2019 was investigated.

Results

The results revealed that prepayment healthcare financing arrangements, social health insurance, mixed- and external-financing healthcare systems significantly enhance health system efficiency. Reliance on a single source for financing healthcare, particularly private out-of-pocket payment reduces health system efficiency.

Conclusion

For policy-making purposes, health care systems financed through a mix of financing arrangements comprising social health insurance, private, and public funding improve health system efficiency in delivering better health outcomes as opposed to depending on one major source of financing, particularly, private out-of-pocket payments.