Eyob Zere Asbu, Aziza Musabah Al Memari, Marwan Al Naboulsi, Mohamed Abdulla Al Haj
{"title":"Technical efficiency of health production in Africa: A stochastic frontier analysis","authors":"Eyob Zere Asbu, Aziza Musabah Al Memari, Marwan Al Naboulsi, Mohamed Abdulla Al Haj","doi":"10.5430/ijh.v8n2p1","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":73454,"journal":{"name":"International journal of healthcare","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5430/ijh.v8n2p1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.
背景:低效率在世界各地的卫生系统中普遍存在。世界卫生组织(WHO)估计,全球卫生支出的20%-40%被浪费了。在非洲国家,这种严重的低效率将严重阻碍在实现全民健康覆盖和其他卫生系统目标方面取得进展。因此,随着时间的推移评估卫生系统的效率非常重要,以便为确定导致效率低下的背景因素和设计适当的提高效率措施奠定基础。方法:利用2000年、2005年、2010年和2015年的面板数据,采用时变随机前沿生产函数进行效率评价。所使用的投入计量是按购买力平价计算的人均经常支出,产出计量是经健康调整后的预期寿命。此外,平均受教育年数、以国际美元计算的人均国内生产总值和自付费用占经常保健支出的比例被用作技术效率低下的影响变量。使用Frontier Version 4.1对数据进行分析。结果:2000年平均技术效率得分为79.3%,2005年为81%,2010年为85.6%,2015年为88.3%。在四个时期内,佛得角的技术效率得分最高,而斯威士兰和塞拉利昂的技术效率得分最低。最低技术效率得分分别为58.7%(2000年)、59.1%(2005年)、67.4%(2010年)和71.8%(2015年)。这些表明,尽管有所改进,但技术效率低下的程度很大。在效率得分最低的10%的国家中,大多数是南部非洲国家。2015年,这些国家的成年人艾滋病毒感染率非常高,而排名前10%的国家的感染率不到0.1%。随着时间的推移,平均效率得分逐渐增加——在2000年至2015年期间增加了9个百分点。当前卫生支出弹性为正(0.06),具有统计学意义。各技术无效率变量均无显著影响。结论:在本研究涵盖的时间段内,平均技术效率得分有所提高。然而,许多国家也存在明显的低效率,这可能会阻碍它们在实现全民健康覆盖和其他卫生系统目标方面取得进展。在卫生支出过低,无法提供所需服务的情况下,必须解决技术效率低下的原因,用这些钱创造更多的卫生服务。此外,表现较差的卫生系统应向表现相对较好的同行学习。