Background: Inefficiency is a pervasive problem in health systems. The World Health Organization estimates that on average, 20%-40% of the global total health expenditure is wasted. The proportion of total health expenditure attributed to hospitals is high, which implies that improving the efficiency of hospitals will lead to more efficient health systems. This study aims to synthetize the major determinants of hospital inefficiency and to develop a framework to identify causes of inefficiency and develop multi-factor interventions to address inefficiencies.Methods: The study is based on survey of the literature on the determinants of hospital efficiency. The studies include those that employ ratio methods of efficiency analysis, data envelopment analysis and stochastic frontier models and econometric models such as the Tobit regression to assess determinants of technical efficiency. Data was extracted in a table format categorized as those that are within the hospital, outside the hospital but within the health system and those that are outside the hospital and health system in the broader macroeconomic system and analyzed.Results: Hospital efficiency is influenced by factors that may be internal to the hospital or external and thus could be wholly or partially out of the control of the hospital. Hospital-level characteristics that influence efficiency include ownership, size, specialization/scope economies, teaching status, membership of multihospital system and other factors such as case-mix and ratio of outpatients to inpatients. However, the effects of these variables are not definitive and consistent; all depends on the context. Factors out of the direct control of the hospital include geographic location, competition and reimbursement systems. The findings further elucidate that no single factor is effective in addressing hospital inefficiencies in isolation from others.Conclusion: There is no one single magic formula or intervention that can be adopted by different hospitals to improve hospital efficiencies. Multiple factors influence the efficiency of hospitals. To address hospital inefficiency multi-intervention packages focusing on the hospital and its environment should be developed.

BackgroundAchieving Universal Health Coverage and other health and health-related targets of the sustainable development goals entails curbing waste in health spending due to inefficiency. Inefficiency is a pervasive problem in health systems. The World Health Organization estimates that on average, 20-40% of the global total health expenditure is wasted. The proportion of total health expenditure attributed to hospitals is high, which implies that improving the efficiency of hospitals will lead to more efficient health systems. This study aims to synthetize the major determinants of hospital inefficiency and to develop a framework to identify causes of inefficiency and develop multi-factor interventions to address inefficiencies. MethodsThe study is based on survey of the literature on hospital efficiency and its determinants. The studies include those that employ ratio methods of efficiency analysis, data envelopment analysis and stochastic frontier models and econometric models such as the tobit regression to assess determinants of technical efficiency. Data was extracted in a table format categorized as those that are within the hospital, outside the hospital but within the health system and those that are outside the hospital and health system in the broader macroeconomic system and analyzed. ResultsHospital efficiency is influenced by factors that may be internal to the hospital or external and thus could be wholly or partially out of the control of the hospital. Hospital-level characteristics that influence efficiency include ownership, size, specialization/scope economies, teaching status, membership of multihospital system and other factors such as case-mix and ratio of outpatients to inpatients. However, the effects of these variables are not definitive and consistent; all depends on the context. Factors out of the direct control of the hospital include geographic location, competition and reimbursement systems. The findings further elucidate that no single factor is effective in addressing hospital inefficiencies in isolation from others.

Background: Inefficiency is widespread in health systems all over the world. The World Health Organization (WHO) estimates that 20%-40% of the global health spending is wasted. In African countries, inefficiency of this magnitude will seriously hamper progress towards achieving universal health coverage and other health system goals. It is thus, significant to assess the efficiency of health systems over time in order to set the ground for identifying the contextual factors leading to inefficiency and design appropriate efficiency-enhancing measures.Methods: Using panel data for the years 2000, 2005, 2010, and 2015, the study employs a time-variant stochastic frontier production function to assess efficiency. The input measure used is current expenditure per capita in purchasing power parity (Int$) terms and the measure of output is health-adjusted life expectancy (HALE). Moreover, mean years of schooling, GDP per capita in Int$, and out-of-pocket payment as a share of current expenditure on health were used as technical inefficiency effect variables. Data were analyzed using Frontier Version 4.1.Results: The mean technical efficiency scores were 79.3% in 2000, 81% in 2005, 85.6% in 2010 and 88.3% in 2015. Over the four periods of time, Cabo Verde registered the highest technical efficiency scores, while Eswatini and Sierra Leone had the lowest. The minimum technical efficiency scores were 58.7% (in 2000), 59.1% (2005), 67.4% (2010) and 71.8% (2015). These indicate that despite improvements, there is a significant degree of technical inefficiency. Most of the countries among those in the bottom 10% efficiency scores are countries in Southern Africa, which in 2015 had a very high prevalence of HIV among adults, compared to the top 10%, which had prevalence rates of less than 0.1%.The mean efficiency score increased progressively over time – a nine percentage point increase between 2000 and 2015. The elasticity of current health expenditure was positive (0.06) and statistically significant. All the technical inefficiency variables had no statistically significant effect.Conclusions: Over the period of time covered in this study, there was some improvement in the average technical efficiency scores. However, there was also marked inefficiency in many countries, which is likely to hamper their progress towards universal health coverage and other health system goals. In a context where health spending is too low to provide needed services, it is imperative to address the causes of technical inefficiency and produce more health for the money. Furthermore, low-performing health systems should learn from their relatively high-performing peers.