Systematic Review: Penilaian Efisiensi Rumah Sakit dengan Metode Data Envelopment Analysis (DEA)

Dalam sistem kesehatan yang berkembang saat ini, efisiensi merupakan hal yang utama. Pengukuran efisiensi bermanfaat untuk pemerintah maupun swasta untuk dapat mengambil keputusan yang berhubungan dengan tinggi rendahnya biaya perawatan di rumah sakit. Penelitian ini bertujuan untuk mengkaji metode Data Envelopment Analysis (DEA) yang digunakan dalam berbagai penelitian dalam pengukuran efisiensi rumah sakit. Desain penelitian yang digunakan adalah dengan sistematic review dengan metode PRISMA tanpa meta analisis. Sumber data didapatkan dari Proquest, Sciencedirect dan Pubmed pada tahun 2019 hingga 2020. Pencarian data dilakukan pada bulan Oktober 2020 dengan kata kunci Hospital Efficiency dan Data Envelopment Analysis. Hasilnya adalah penilaian efisiensi rumah sakit menggunakan metode DEA lebih banyak dilakukan dengan analisa dua tahap menggunakan tobit regression atau truncated regression. Perhitungan index malmquist juga banyak digunakan setelah perhitungan DEA dilakukan untuk melihat efisiensi rumah sakit dalam periode waktu tertentu.

Efficiency of Iranian Hospitals Before and After Health Sector Evolution Plan: A Systematic Review and Meta-Analysis Study

Purpose: Aging, chronic diseases, and development of expensive and advanced technologies has increased hospitals costs which have necessitated their efficiency in utilization of resources. This systematic review and meta-analysis study has assessed the efficiency of Iranian hospitals before and after the 2011 Health Sector Evolution Plan (HSEP).Methods: Internal and external databases were searched using specified keywords without considering time limitations. The retrieved articles were entered into EndNote considering inclusion and exclusion criteria, and the final analysis was performed after removing duplicates. Heterogeneity between the studies was assessed using Q and I2 tests. A forest plot with 95% confidence intervals (CI) was used to calculate different types of efficiency. The data were analyzed using STATA 14.Results: Random pooled estimation of hospitals technical, managerial, and scale efficiencies were 0.84 (95%CI = 0.78, 0.52), 0.9 (95%CI = 0.85, 0.94), and 0.88 (95%CI = 0.84, 0.91), respectively. Sub-group analysis on the basis of study year (before and after HSEP in 2011) indicated that random pool estimation of technical (0.86), managerial (0.91), and scale (0.90) efficiencies of Iranian hospitals for 2011 and before were better than technical (0.78), managerial (0.86), and scale (0.74) efficiencies after 2011.Conclusion: Type of hospital ownership was effective on hospital efficiency. However, HSEP has not improved hospital efficiency, so it is necessary for future national plans to consider all aspects.

Hospital Efficiency Measurement in the West of Iran: Data Envelopment Analysis and Tobit Approach

Objective The optimal hospital performance and optimal use of resources are among the goals of healthcare policymakers. This study aimed to assess the association between hospital size and hospital area population with technical efficiency in public hospitals . Methods In this descriptive-analytical study, the statistical population consisted of 15 public hospitals in the west of Iran. First, the data envelopment analysis (DEA) method was used to evaluate technical efficiency. Data inputs included staff and beds, and data outputs consisted of the number of surgeries, the number of patients, and the average length of stay. Then, according to the public ownership of all hospitals, their educational and therapeutic activities, as well as their size and population were considered as the environmental factor affecting efficiency. Thus, Tobit regression was applied to measure their effects on efficiency. Results The average technical efficiency of the studied hospitals, the average management efficiency, and the average efficiency of the scale were 0.933, 0.951, and 0.977, respectively. Out of the total evaluated hospitals, six and nine hospitals had an efficiency of less than one and one, respectively. Moreover, the size of the hospital and the population as the environment variable were significant in the Tobit model. Our regression demonstrated that although the size of the hospital is positively associated with its technical efficiency, the hospital population negatively affects hospital efficiency. Conclusion According to the size and area population of the hospitals, they decrease their inputs to maximize their efficacy by optimizing their surplus amounts. It would be possible for policy-makers to examine the least efficient hospitals to correct widespread inefficiency.

Can integrated care improve the efficiency of hospitals? Research based on 200 Hospitals in China

Background The shift towards integrated care (IC) represents a global trend towards more comprehensive and coordinated systems of care, particularly for vulnerable populations, such as the elderly. When health systems face fiscal constraints, integrated care has been advanced as a potential solution by simultaneously improving health service effectiveness and efficiency. This paper addresses the latter. There are three study objectives: first, to compare efficiency differences between IC and non-IC hospitals in China; second, to examine variations in efficiency among different types of IC hospitals; and finally, to explore whether the implementation of IC impacts hospital efficiency. Methods This study uses Data Envelopment Analysis (DEA) to calculate efficiency scores among a sample of 200 hospitals in H Province, China. Tobit regression analysis was performed to explore the influence of IC implementation on hospital efficiency scores after adjustment for potential confounding. Moreover, the association between various input and output variables and the implementation of IC was investigated using regression techniques. Results The study has four principal findings: first, IC hospitals, on average, are shown to be more efficient than non-IC hospitals after adjustment for covariates. Holding output constant, IC hospitals are shown to reduce their current input mix by 12% and 4% to achieve optimal efficiency under constant and variable returns-to-scale, respectively, while non-IC hospitals have to reduce their input mix by 26 and 20% to achieve the same level of efficiency; second, with respect to the efficiency of each type of IC, we show that higher efficiency scores are achieved by administrative and virtual IC models over a contractual IC model; third, we demonstrate that IC influences hospitals efficiency by impacting various input and output variables, such as length of stay, inpatient admissions, and staffing; fourth, while bed density per nurse was positively associated with hospital efficiency, the opposite was shown for bed density per physician. Conclusions IC has the potential to promote hospital efficiency by influencing an array of input and output variables. Policies designed to facilitate the implementation of IC in hospitals need to be cognizant of the complex way IC impacts hospital efficiency.

The Impact of Public Reporting Schemes and Market Competition on Hospital Efficiency

In the wake of growing attempts to assess the validity of public reporting, much research has examined the effectiveness of public reporting regarding cost or quality of care. However, relatively little is known about whether transparency through public reporting significantly influences hospital efficiency despite its emerging expectations for providing value-based care. This study aims to identify the dynamics that transparency brought to the healthcare market regarding hospital technical efficiency, taking the role of competition into account. We compare the two public reporting schemes, All-Payer Claims Database (APCD) and Hospital Compare. Employing Data Envelopment Analysis (DEA) and a cross-sectional time-series Tobit regression analysis, we found that APCD is negatively associated with hospital technical efficiency, while hospitals facing less competition responded significantly to increasingly transparent information by enhancing their efficiency relative to hospitals in more competitive markets. We recommend that policymakers take market mechanisms into consideration jointly with the introduction of public reporting schemes in order to produce the best outcomes in healthcare.

Determinants of Health Service Efficiency in Hospi-tal: A Systematic Review

One of the benchmarks for assessing service performance in hospitals is efficiency in medical services. Measurement of service efficiency will affect the quality of the hospital. Patients will consider the completeness of the service facilities they have and the quality of services to be obtained. This is due to the tendency of people to seek quality health services. Improving service quality standards in hospitals will have an impact on increasing income and getting recognition from the community for the quality of services in hospitals. This study aims to look at the determinant factors that affect hospital efficiency. This study uses a systematic review method based on the PRISMA protocol. Article searches were conducted through four online databases (PubMed, ProQuest, SAGE and SpingerLink). The initial search found 307 articles, filtered using inclusion criteria, so as many as 8 articles were analyzed with a time span of 2017-2021. The efficiency of health services in hospitals is the basis for obtaining a wider patient base and producing quality services. The results of the literature study show that there are 29 factors affecting hospital efficiency. The various factors obtained were categorized into organizational factors, health resource factors, and technical efficiency factors.