Technical efficiency of neonatal health services in primary health care facilities of Southwest Ethiopia: a two-stage data envelopment analysis

Technical efficiency analysis of advanced medical centers in Burkina Faso

INTRODUCTION

Burkina Faso faces many challenges in the health domain, with no real opportunity for an increase in public health expenditures. In Burkina Faso, as in all low-income countries, health spending efficiency is crucial. The objective of this paper is to assess the efficiency of Advanced Medical Centers (AMCs)-which correspond to district hospitals-in Burkina Faso over the 2017-2020 period and identify the factors that promote-or, on the contrary, limit-the efficiency of these health structures.

METHOD

We first assessed the efficiency level of the 45 AMCs running in the country between 2017 and 2020 using a bootstrap Data Envelopment Analysis (DEA) methodology. Inputs include the number of doctors, nurses, other medical staff, non-medical staff, and beds, while output variables correspond to the number of inpatients, surgeries, outpatients, and inpatient days. In a second step, determinants of AMC's efficiency levels were explored using a double-bootstrap procedure. The roles of AMCs' internal and environmental factors were both considered.

RESULTS

We found a mean efficiency score of 0.51 over the study period, indicating that AMCs could have almost doubled their healthcare production without needing additional resources. The size, education level, and health status of the covered population and the density of the healthcare supply in the district appeared to be the driving factors of AMCs' efficiency.

CONCLUSION

Our results indicate that improving the efficiency of AMCs should be a high-level priority for the Burkinabe health policy. Resources could be reallocated across AMCs to increase the overall efficiency of the health system.

Evaluating the Effectiveness of Maternal, Neonatal, and Child Healthcare in Moroccan Hospitals and SDG 3: Using Two-Stage Data Envelopment Analysis and Tobit Regression

Maternal, neonatal, and child health play crucial roles in achieving the objectives of Sustainable Development Goal (SDG) 2030, particularly in promoting health and wellbeing. However, maternal, neonatal, and child services in Moroccan public hospitals face challenges, particularly concerning mortality rates and inefficient resource allocation, which hinder optimal outcomes. This study aimed to evaluate the operational effectiveness of 76 neonatal and child health services networks (MNCSN) within Moroccan public hospitals. Using Data Envelopment Analysis (DEA), we assessed technical efficiency (TE) employing both Variable Returns to Scale for inputs (VRS-I) and outputs (VRS-O) orientation. Additionally, the Tobit method (TM) was utilized to explore factors influencing inefficiency, with hospital, doctor, and paramedical staff considered as inputs, and admissions, cesarean interventions, functional capacity, and hospitalization days as outputs. Our findings revealed that VRS-I exhibited a higher average TE score of 0.76 compared to VRS-O (0.23). Notably, the Casablanca-Anfa MNCSN received the highest referrals (30) under VRS-I, followed by the Khemisset MNCSN (24). In contrast, under VRS-O, Ben Msick, Rabat, and Mediouna MNCSN each had three peers, with 71, 22, and 17 references, respectively. Moreover, the average Malmquist Index under VRS-I indicated a 7.7% increase in productivity over the 9-year study period, while under VRS-O, the average Malmquist Index decreased by 8.7%. Furthermore, doctors and functional bed capacity received the highest Tobit model score of 0.01, followed by hospitalization days and cesarean sections. This study underscores the imperative for policymakers to strategically prioritize input factors to enhance efficiency and ensure optimal maternal, neonatal, and child healthcare outcomes.

Level of technical efficiency and associated factors among health centers in East Gojjam Zone, Northwest Ethiopia: an application of the data envelopment analysis

BACKGROUND

Besides the scarcity of resources, inefficient utilization of available health service resources has been the bottleneck to deliver quality health services in Ethiopia. However, Information regarding the efficiency of health service providers is limited in the country. Health service managers and policy makers must be well informed about the efficiency of health service providers and ways of using limited resources efficiently to make evidence-based decisions. This study aimed to assess the level of technical efficiency and associated factors among health centers in East Gojjam Zone, Northwest Ethiopia.

METHODS

A facility-based cross-sectional study was conducted among 27 randomly selected health centers in East Gojjam zone, Northwest Ethiopia, from October 30, 2022, to April 30, 2023. Using an interviewer-administered questionnaire and document review checklist, health centers' data was collected and entered to Epi-Data version 4.6. The data was exported to Microsoft office excel and Stata version 14 for analysis. A two-stage output-oriented data envelopment analysis with a variable return to scale assumption was employed to determine the level of technical efficiencies. Finally, the tobit regression model was applied to identify the associated factors at 5% level of significance.

RESULTS

In this study, 59.3% of the health centers were technically efficient. The mean technical efficiency score of the health centers was 0.899 ± 0.156. Inefficient health centers could provide more 22, 433 outpatient visits, 1,351 family planning visits, 155 referral services, 206 skilled deliveries and 385 fully vaccinations of children if they were technically efficient as their peer health centers for the same year. From the tobit regression, the catchment population and number of administrative staffs were statistically significant determinants of the technical efficiency of health centers.

CONCLUSIONS

The mean technical efficiency of the health centers in East Gojjam zone, Northwest Ethiopia was high. However, nearly half of the health centers were technically inefficient, which indicates the exitance of a space for further improvements in the productivity of these health centers. Employing excess number administrative staffs (above the optimal level) should be discouraged and selecting appropriate sites where the health centers to be constructed (to have large catchment population coverage) could improve the productivity of health centers.

The state and significant drivers of health systems efficiency in Africa: A systematic review and meta-analysis

Background

Low-and-middle-income countries, especially in Africa, lack the capacity to adequately invest in health systems to attain universal health coverage (UHC). As such, countries must improve efficiency and provide more services within the available resources. This systematic review synthesised evidence on the efficiency of health systems in the African region and its drivers.

Methods

We conducted a systematic literature review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Related studies were grouped and meta-analysed, while others were descriptively analysed. We employed a qualitative content synthesis for synthesising the drivers of efficiency.

Results

Overall, 39 studies met a predetermined inclusion criterion and were included from a possible 4 609 records retrieved through a rigorous search and selection process. Using a random effects restricted maximum likelihood method, the pooled efficiency score for the Africa region was estimated to be 0.77, implying that on the flip side, health system inefficiency across countries in the African region was approximately 23%. Across 22 studies that used data envelopment analysis to examine efficiency at the level of health facilities and sub-national entities, the efficiency level was 0.67. Facility-level studies tended to estimate low levels of efficiency compared to health system-level studies. Across the 39 studies, 21 significant drivers of inefficiency were reported, including population density of the catchment area, governance, health facility ownership, health facility staff density, national economic status, type of health facility, education index, hospital size and bed occupancy rate.

Conclusion

With approximately 23% of the inefficiency of health systems in Africa, improving efficiency alone will yield an average of 34% improvement in resource availability, assuming all countries are performing similarly to the frontier countries. However, with the low level of health expenditure per capita in Africa, the efficiency gains alone will be insufficient to meet the minimum funding requirement for UHC.

Registration

PROSPERO: CRD42022318122.

Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach

BACKGROUND

Primary health care (PHC) institutions are key to realizing the main functions of the health care system. Since the new health care reform in 2009, the Chinese government has invested heavily in PHC institutions and launched favorable initiatives to improve the efficiency of such institutions. This study is designed to gauge the efficiency of PHC institutions by using 2012-2020 panel data covering 31 provinces in China.

METHODS

This study applied an improved three-stage data envelopment analysis (DEA) model to evaluate the efficiency of PHC institutions in China. Unlike the traditional three-stage DEA model, the input-oriented global super-efficiency slack-based measurement (SBM) DEA model is used to calculate the efficiency in the first and third stages of the improved three-stage DEA model, which not only allows the effects of environmental factors and random noise to be taken into account but also deal with the problem of slack, super-efficiency and the comparability of interperiod efficiency values throughout the efficiency measurement.

RESULTS

The results show that the efficiency of PHC institutions has been overestimated due to the impact of external environmental factors and random noise. From 2012 to 2020, the efficiency of PHC institutions displayed a downward trend. Moreover, there are significant differences in the efficiency of PHC institutions between regions, with the lowest efficiency being found in the northeast region. The efficiency of PHC institutions is significantly affected by residents' annual average income, per capita GDP, population density, the percentage of the population aged 0-14, the percentage of the population aged 65 and older, the number of people with a college education and above per 100,000 residents, and the proportion of the urban population.

CONCLUSIONS

Substantial investment in PHC institutions has not led to the expected efficiency gains. Therefore, more effective measures should be taken to improve the efficiency of PHC institutions in China based on local conditions. This study provides a new analytical approach to calculating the efficiency of PHC institutions, and this approach can be applied to efficiency evaluation either in other fields or in other countries.

Technical Efficiency Evaluation of Primary Health Care Institutions in Shenzhen, China, and Its Policy Implications under the COVID-19 Pandemic

(1) Background: Primary health care institutions (PHCI) play an important role in reducing health inequities and achieving universal health coverage. However, despite the increasing inputs of healthcare resources in China, the proportion of patient visits in PHCI keeps declining. In 2020, the advent of the COVID-19 pandemic further exerted a severe stress on the operation of PHCI due to administrative orders. This study aims to evaluate the efficiency change in PHCI and provide policy recommendations for the transformation of PHCI in the post-pandemic era. (2) Methods: Data envelope analysis (DEA) and the Malmquist index model were applied to estimate the technical efficiency of PHCI in Shenzhen, China, from 2016 to 2020. The Tobit regression model was then used to analyze the influencing factors of efficiency of PHCI. (3) Results: The results of our analysis reflect considerable low levels of technical efficiency, pure technical efficiency, and scale efficiency of PHCI in Shenzhen, China, in 2017 and 2020. Compared to years before the epidemic, the productivity of PHCI decreased by 24.6% in 2020, which reached the nadir, during the COVID-19 pandemic along with the considerable reduction of technological efficiency, despite the significant inputs of health personnel and volume of health services. The growth of technical efficiency of PHCI is significantly affected by the revenue from operation, percentage of doctors and nurses in health technicians, ratio of doctors and nurses, service population, proportion of children in the service population, and numbers of PHCI within one kilometer. (4) Conclusion: The technical efficiency significantly declines along with the COVID-19 outbreak in Shenzhen, China, with the deterioration of underlying technical efficiency change and technological efficiency change, regardless of the immense inputs of health resources. Transformation of PHCI such as adopting tele-health technologies to maximize primary care delivery is needed to optimize utilization of health resource inputs. This study brings insights to improve the performances of PHCI in China in response to the current epidemiologic transition and future epidemic outbreaks more effectively, and to promote the national strategy of Healthy China 2030.

Analysis of factors influencing technical efficiency of public district hospitals in KwaZulu-Natal province, South Africa

BACKGROUND

District hospitals are crucial in supporting primary health care and serve as a gateway to more specialist care through a referral system. Majority of South Africans access health care services through the public sector district health system. Given the enormous task assigned to the public district hospital within the country, this study examined factors influencing their technical efficiency.

METHOD

Data were collected for 38 public district hospitals in KwaZulu-Natal province from 2014/15 to 2016/17. Data envelopment analysis (DEA) was used to determine the technical efficiency of the hospitals, adopting both the constant return to scale (CRS) and variable return to scale (VRS) models. Tobit regression model was used to determine factors related to the technical efficiency of the district hospitals.

RESULTS

This study showed that a significant proportion of the district hospitals were technically inefficient. The Tobit regression model identified catchment population, the proportion of inpatients treated per medical personnel, the proportion of inpatients treated per nursing personnel and expenditure per patient day equivalent as factors influencing technical efficiency of the district hospitals.

CONCLUSION

Findings from this study suggest that the technical efficiency of the district hospitals can be enhanced through an effective referral system and improved peoples' health-seeking behaviour. In addition, a standard mix of clinical staff toward efficient service delivery and periodic cost analysis of health services with the view to saving cost and maintaining the quality of health care should be considered.

Evaluating the technical efficiency of neonatal health service among primary hospitals of northwest Ethiopia: Using two-stage data envelopment analysis and Tobit regression model

INTRODUCTION

Most cases of neonatal mortality are preventable but a substantial number of cases get complicated and become irreversible not only due to scarcity but also due to inefficient utilization of available resources in the health service. However, limited evidence shows the efficiency level of health facilities in Ethiopia. Therefore, this study aimed to assess the technical efficiency of neonatal health service and its associated factors among primary hospitals in three zones of Northwest Ethiopia.

METHODS

A facility-based cross-sectional study was conducted among fifteen randomly selected primary hospitals from March 17 to April 17, 2021. Input data on non-salary recurrent costs, salary costs, and the number of beds, and output data on neonatal admissions, outpatient visits, and referrals for the 2019/20 fiscal year were collected using a document review. In the first stage of analysis, input-oriented data envelopment analysis with a variable return-to-scale assumption was employed to estimate the efficiency scores using DEAP 2.1. A Tobit regression model was fitted in the second stage to identify the associated factors with technical efficiency. Variables with a p-value <0.05 were declared as statistically associated factors.

RESULTS

In this study, 80% of the primary hospitals were pure technical efficient whereas 46.67% of the facilities were scale efficient with all of the scale inefficient hospitals operating below their scale. The mean pure technical and scale efficiency score of primary hospitals was 0.948±0.113 and 0.887±0.143, respectively. Total catchment population, incentive packages for the clinical staff, and the educational status of the manager were positively associated with the technical efficiency of hospitals. On the other hand, technical efficiency was negatively associated with the presence of a health facility that provides neonatal health services near the hospital and the distance of the manager's residence.

CONCLUSION

Though most of the primary hospitals in Northwest Ethiopia were technical efficient, more than half of them were working below their scale of operation. Our results also indicated that introducing the performance-based provision of incentive packages for clinical staff and employing master's and above-educated health professionals as a manager might improve the efficient utilization of resources in primary hospitals.

The Impact of Health Care Reform Since 2009 on the Efficiency of Primary Health Services: A Provincial Panel Data Study in China

Background: Primary health care (PHC) is an important part of health systems in the world and in China. To improve the efficiency of PHC institutions (PHCIs), many countries have implemented reforms, including China's health care reform since 2009. This study aims to evaluate the impact of this reform on the efficiency of PHCIs from the perspective of the whole health system. Methods: Data were collected from China Health Statistical Yearbooks and China Statistical Yearbooks published from 2005 to 2019. By taking the number of beds, health technicians and PHCIs as inputs and the proportion of diagnosis, treatment and admission in PHCIs as outputs, Malmquist DEA was used to evaluate the efficiency change of PHCIs, and panel data regression was performed to analyze the impact of the reform and other factors on such efficiency. The interaction between reform and economic level was also estimated. Results: The MPI in Beijing, Tianjin, Shanghai, Hunan, and Guangdong improved after the reform. The efficiency improvement in Beijing, Tianjin and Shanghai is mainly reflected in the growth of TC, whereas the efficiency improvement in Guangdong and Hunan is mainly reflected in the growth of EC. Meanwhile, the EC and TC in Hebei, Heilongjiang, Shandong, and other provinces deteriorated. The deterioration of MPI in Shanxi, Inner Mongolia and Jilin was mainly attributed to EC. while the deterioration of MPI in Liaoning, Anhui, and Fujian provinces is mainly attributed to TC. Since 2009, the reform exerted a negative impact on MPI (β = -0.06; P < 0.01), TC (β = -0.048; P < 0.01) and EC (β = -0.03; P < 0.01). And such negative impact was weaker in economically developed areas (β = 0.076; P < 0.01). Conclusions: Attention should be paid to future reforms: China should continue investing in PHCIs, establish a structurally integrated and functionally complementary delivery system and promote the coordination of reform policies to avoid the adverse impacts of other reform policies on PHCIs.