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Efficiency evaluation of public hospitals in Saudi Arabia: an application of data envelopment analysis.

ABSTRACT: OBJECTIVE:In this study, we assess the performance of public hospitals in Saudi Arabia. We detect the sources of inefficiency and estimate the optimal levels of the resources that provide the current level of health services. We enrich our analysis by employing locations and capacities of the hospitals. DESIGN:We employ data envelopment analysis (DEA) to measure the technical efficiency of 91 public hospitals. We apply the input-oriented Charnes, Cooper and Rhodes, and Banker, Charne, Cooper models under Constant and Variable Returns-to-Scale. The assessment includes four inputs, and six output variables taken from the Ministry of Health databases for 2017. We conducted the assessment via PIM-DEA V.3.2 software. SETTING:Ministry of health-affiliated hospitals in the Kingdom of Saudi Arabia. RESULTS:Findings identified 75.8% (69 of 91) of public hospitals as technically inefficient. The average efficiency score was 0.76, indicating that hospitals could have reduced their inputs by 24% without reduction in health service provision. Small hospitals (efficiency score 0.79) were more efficient than medium-sized and large hospitals. Hospitals in the central region were more efficient (efficiency score 0.83), than those located in other geographical locations. More than half of the hospitals (62.6%) were operating suboptimally in terms of the scale efficiency, implying that to improve efficiency, they need to alter their production capacity. Performance analysis identified overuse of physician's numbers and shortage of health services production, as major causes of inefficiency. CONCLUSION:Most hospitals were technically inefficient and operating at suboptimal scale size and indicate that many hospitals may improve their performance through efficient utilisation of health resources to provide the current level of health services. Changes in the production capacity are required, to facilitate optimal use of medical capacity. The inefficient hospitals could benefit from these findings to benchmarking their system and performance in light of the efficient hospital within their capacity and geographical location.

SUBMITTER: Alatawi AD

PROVIDER: S-EPMC7045210 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Efficiency evaluation of public hospitals in Saudi Arabia: an application of data envelopment analysis.

Alatawi Ahmed D AD Niessen Louis Wilhelmus LW Khan Jahangir A M JAM

BMJ open 20200112 1

<h4>Objective</h4>In this study, we assess the performance of public hospitals in Saudi Arabia. We detect the sources of inefficiency and estimate the optimal levels of the resources that provide the current level of health services. We enrich our analysis by employing locations and capacities of the hospitals.<h4>Design</h4>We employ data envelopment analysis (DEA) to measure the technical efficiency of 91 public hospitals. We apply the input-oriented Charnes, Cooper and Rhodes, and Banker, Cha ...[more]

PMID: 31932390

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Project description:BackgroundIn order to measure and analyse the technical efficiency of district hospitals in Ghana, the specific objectives of this study were to (a) estimate the relative technical and scale efficiency of government, mission, private and quasi-government district hospitals in Ghana in 2005; (b) estimate the magnitudes of output increases and/or input reductions that would have been required to make relatively inefficient hospitals more efficient; and (c) use Tobit regression analysis to estimate the impact of ownership on hospital efficiency.MethodsIn the first stage, we used data envelopment analysis (DEA) to estimate the efficiency of 128 hospitals comprising of 73 government hospitals, 42 mission hospitals, 7 quasi-government hospitals and 6 private hospitals. In the second stage, the estimated DEA efficiency scores are regressed against hospital ownership variable using a Tobit model. This was a retrospective study.ResultsIn our DEA analysis, using the variable returns to scale model, out of 128 district hospitals, 31 (24.0%) were 100% efficient, 25 (19.5%) were very close to being efficient with efficiency scores ranging from 70% to 99.9% and 71 (56.2%) had efficiency scores below 50%. The lowest-performing hospitals had efficiency scores ranging from 21% to 30%.Quasi-government hospitals had the highest mean efficiency score (83.9%) followed by public hospitals (70.4%), mission hospitals (68.6%) and private hospitals (55.8%). However, public hospitals also got the lowest mean technical efficiency scores (27.4%), implying they have some of the most inefficient hospitals.Regarding regional performance, Northern region hospitals had the highest mean efficiency score (83.0%) and Volta Region hospitals had the lowest mean score (43.0%).From our Tobit regression, we found out that while quasi-government ownership is positively associated with hospital technical efficiency, private ownership negatively affects hospital efficiency.ConclusionsIt would be prudent for policy-makers to examine the least efficient hospitals to correct widespread inefficiency. This would include reconsidering the number of hospitals and their distribution, improving efficiency and reducing duplication by closing or scaling down hospitals with efficiency scores below a certain threshold. For private hospitals with inefficiency related to large size, there is a need to break down such hospitals into manageable sizes.

Project description:ObjectiveDespite an extensive literature on efficiency, qualitative evidence on the drivers of hospital efficiency is scant. This study examined the factors that influence the efficiencies of health service provision in public hospitals in the Kingdom of Saudi Arabia (KSA) and their potential remedies.DesignWe employed a qualitative design involving semi-structured interviews conducted between July and September 2019. Participants were purposively selected and included policymakers and hospital managers drawn from districts, regional and national levels. Data were analyzed in Nvivo 12 based on a thematic approach.SettingKey informants of Ministry of health in the KSA.ResultsRespondents identified a range of different factors across the community, facility and the wider health system that influence inefficiencies in public hospitals in KSA. Ineffective hospital management, lack of strategic planning and goals, weak administrative leadership, and absence of monitoring hospital performance was noted to have a profound impact on hospital efficiency. The conditions of healthcare staff in respect to both skills, authority and psychological factors were considered to influence the efficiency level. Further, lack of appropriate data for decision making due to the absence of an appropriate health informatics system was regarded as a factor of inefficiency. At the community level, respondents described inadequate information on the healthcare needs and expectations of patients and the wider community as significant barriers to the provision of efficient services. To improve hospital efficiencies, respondents recommended that service delivery decisions are informed by data on community health needs; capacity strengthening and effective supervision of hospital staff; and judicious resource allocation.ConclusionThe study demonstrates that inefficiencies in health services remain a critical challenge in public hospitals in KSA. Extensive awareness-raising and training on efficient resource utilization among key health systems stakeholders are imperative to improving hospital performance. More research is needed to strengthen knowledge on hospital efficiency in light of the limited data on the topic in KSA and the wider Gulf region.

Project description:BackgroundThe Ministry of Health in Saudi Arabia is expanding the country's telemedicine services by using advanced technology in health services. In doing so, an e-health application (app), Seha, was introduced in 2018 that allows individuals to have face-to-face visual medical consultations with their doctors on their smartphones.ObjectiveThis study evaluated the effectiveness of the app in improving healthcare delivery by ensuring patient satisfaction with the care given, increasing access to care, and improving efficiency in the healthcare system.MethodsA cross-sectional study design was used to assess the perceptions of users of the Seha app and non-users who continued with traditional health services. The data were collected using an online survey via Google Forms between June 2020 and September 2020. Independent t tests and chi-square (χ2) tests were conducted to answer the research questions.ResultsThere was a significant difference between users and non-users in terms of ease of access to health services (t = - 9.38, p < 0.05), with app users having a higher mean score (4.19 ± 0.91) than non-users (3.41 ± 1.00); satisfaction with health services (t = - 6.33, p < 0.05), with users having a higher mean score (3.96 ± 0.91) than non-users (3.45 ± 0.94); and efficiency (only one visit needed for treatment) (t = - 3.20, p < 0.05), with users having a higher mean score (3.71 ± 0.93) than non-users (3.45 ± 0.93). There were significant associations between the use of the Seha app and age (χ2 = 8.79, p < 0.05), gender (χ2 = 22.19, p < 0.05), region (χ2 = 19.74, p < 0.05), and occupation (χ2 = 22.05, p < 0.05). There were significant relationships between the three items (on access, satisfaction, and efficiency) and experiencing technical issues (t = 4.47, t = 8.11, and t = 3.24, respectively, p < 0.05), with users who faced technical problems having significantly lower mean scores for all three items.ConclusionThis study provided evidence that the Seha app improved the delivery of healthcare in Saudi Arabia. Users of the app had a better health experience in terms of their perceived ease of access to healthcare services; their satisfaction with healthcare services; and the efficiency of the system, measured by the number of required doctor visits. Other factors that appeared to influence the use of the app included age, gender, usual source of care, and technical difficulties.

Dataset Information

Efficiency evaluation of public hospitals in Saudi Arabia: an application of data envelopment analysis.

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Efficiency evaluation of public hospitals in Saudi Arabia: an application of data envelopment analysis.

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