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

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Zixuan Peng ◽  
Li Zhu ◽  
Guangsheng Wan ◽  
Peter C. Coyte
Keyword(s):  
Integrated Care ◽  
Systems Of Care ◽  
Returns To Scale ◽  
The Elderly ◽  
Hospital Efficiency ◽  
Tobit Regression ◽  
Service Effectiveness ◽  
Input And Output ◽  
Optimal Efficiency ◽  
Tobit Regression Analysis

Abstract 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.

scholarly journals Can Integrated Care Improve the Efficiency of Hospitals? - Research based on 200 Hospitals in China

2020 ◽  
Author(s):  
Zixuan Peng ◽  
Li Zhu ◽  
Guangsheng Wan ◽  
Peter C. Coyte
Keyword(s):  
Integrated Care ◽  
Systems Of Care ◽  
Returns To Scale ◽  
The Elderly ◽  
Hospital Efficiency ◽  
Tobit Regression ◽  
Service Effectiveness ◽  
Input And Output ◽  
Optimal Efficiency ◽  
Tobit Regression Analysis

Abstract Backgrounds: 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 Integrated Care 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.

scholarly journals DATA ENVELOPMENT ANALYSIS OF RUBBER SMALLHOLDERS: BCC AND CCR MODELS AND BOOTSTRAPPING TECHNIQUE

2018 ◽  
Vol 6 (5) ◽  
pp. 346-368
Author(s):  
A. ALIYU ◽  
K. BELLO
Keyword(s):  
Data Envelopment Analysis ◽  
Marital Status ◽  
Returns To Scale ◽  
Peninsular Malaysia ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Traditional Concept ◽  
Tobit Regression Analysis ◽  
Socio Demographic Factors ◽  
Constant Returns To Scale

The present study examined the economic efficiency of rubber smallholders in Peninsular Malaysia in a disaggregated form using Banker Charnes and Cooper (BCC) and Charnes Cooper and Rhodes (CCR) models of data envelopment analysis (DEA) as well as their respective bootstrap techniques. Multistage data collection was employed on 327 smallholders among 5 districts of Negeri Sembilan state. However, only 307 observations were used in computing inferential statistics, because the young-age category has been removed. The districts include Seremban, Tampin, Rembau, Kuala Pilah and Jempol. The results revealed that, the mean technical efficiency (TE) under variable returns to scale (VRS) and constant returns to scale (CRS) were 0.95, 0.97 0.96 and 0.45, 0.61, 0.33 for the all-age, matured-age and old-age crops respectively. The findings of the result also disclosed that naïve DEA has higher mean scores than bootstrapped-DEA, thus indicating the presence of bias in the former and absence of bias in the later. Also, the efficiency determinants under VRS and CRS as well as their respective bias-corrected (BC) efficiency scores were also analyzed using Tobit regression analysis against the 15 socio-demographic factors. It was found out that critical factors, common to all the age-categories, include educational level, tapping system and marital status under VRS and BC-VRS assumptions, while under CRS and BC-CRS assumptions include race, tapping system, marital status and farm’s distance. Therefore, education of smallholders should be given more attention to increase efficiency.  The study finally recommends that the traditional concept of computing efficiency or productivity of rubber and other perennial crops in an aggregated form should be complemented with the disaggregated form as this eliminates any bias and gives meaningful results. Improved methods such as bootstrapping should also be used as this only gives what is called bias-corrected efficiency scores. Regarding the determinants, factors such as education, tapping system and farm distance should be given more emphasis.

scholarly journals Efficiency Analysis of East Asian Zinc Smelters and the Effects of Capacity and Bonus Zinc on Efficiency

2019 ◽  
Vol 5 (1) ◽  
pp. 4 ◽  
Author(s):  
Ha Park ◽  
Daecheol Kim
Keyword(s):  
Returns To Scale ◽  
Labor Cost ◽  
Efficiency Analysis ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Tobit Regression ◽  
Iron Aluminum ◽  
Tobit Regression Analysis ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

Non-ferrous metals are widely used as basic materials in various industrial fields, and zinc is a metal that is produced and used next to iron, aluminum, and copper. In this study, DEA (data envelopment analysis) was applied to measure the efficiency of 43 zinc smelters in three countries in East Asia: Korea, China, and Japan. The constant returns to scale (CRS) and the variable returns to scale (VRS) models, and the slack-based measure (SBM) were used for the analysis. As a result of the efficiency analysis, there were three efficient zinc smelters in the CRS model, 14 in the VRS model and 14 in the SBM. The average efficiency was 0.458 based on the SBM, which indicates that there is room for improvement in efficiency. In addition, the average scale efficiency value was 0.689, showing the scale to be inefficient. Therefore, it can be seen that the labor cost and the energy cost must be brought to an appropriate level. The Tobit regression analysis was used to analyze the causes of efficiency. The greater the capacity and the larger amount of bonus Zn of the refinery, the higher the efficiency of the refinery.

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

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1031
Author(s):  
Ahreum Han ◽  
Keon-Hyung Lee
Keyword(s):  
Technical Efficiency ◽  
Market Competition ◽  
Public Reporting ◽  
Hospital Efficiency ◽  
Tobit Regression ◽  
Cross Sectional ◽  
Tobit Regression Analysis ◽  
Value Based Care ◽  
Hospital Compare ◽  
The Impact

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.

scholarly journals Optimal solutions of multiplier DEA models

2021 ◽  
Author(s):  
Victor V. Podinovski ◽  
Tatiana Bouzdine-Chameeva
Keyword(s):  
Returns To Scale ◽  
Scale Production ◽  
Optimal Solutions ◽  
Optimal Input ◽  
Input And Output ◽  
Decision Making Unit ◽  
Dea Models ◽  
Constraint Structure ◽  
Conventional Models ◽  
Almost All

AbstractConventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input and output weights of the multiplier DEA models based on these technologies are interpreted as being the most favorable for the decision making unit (DMU) under the assessment when the latter is benchmarked against the set of all observed DMUs. In this paper we consider a very large class of DEA models based on arbitrary polyhedral technologies, which includes almost all known convex DEA models. We highlight the fact that the conventional interpretation of the optimal input and output weights in such models is generally incorrect, which raises a question about the meaning of multiplier models. We address this question and prove that the optimal solutions of such models show the DMU under the assessment in the best light in comparison to the entire technology, but not necessarily in comparison to the set of observed DMUs. This result allows a clear and meaningful interpretation of the optimal solutions of multiplier models, including known models with a complex constraint structure whose interpretation has been problematic and left unaddressed in the existing literature.

Determining the factors affecting the technical efficiency scores of public hospitals using different regression methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bayram Şahin ◽  
Gülnur İlgün ◽  
Seda Sönmez
Keyword(s):  
Public Hospitals ◽  
Regression Analyses ◽  
Tobit Regression ◽  
Control Variables ◽  
Content Type ◽  
Factors Affecting ◽  
Provincial Level ◽  
Regression Methods ◽  
Input And Output ◽  
Dea Method

PurposeThis study aims to identify the efficiency scores of hospitals affiliated to the Ministry of Health in Turkey between the years of 2010–2015 at provincial level and to reveal the factors that affect the efficiency scores.Design/methodology/approachThe two-stage data envelopment analysis (DEA) method was used to achieve the study purpose. In the first stage, DEA method based on input-oriented Charnes–Cooper–Rhodes (CCR) model was performed to calculate the efficiency scores of public hospitals at the provincial level between 2010 and 2015, and in the second stage, Tobit regression and linear regression analyses were used to identify whether the efficiency scores of provinces are affected by the input, output and control variables.FindingsUpon the analysis, the average efficiency scores of 81 provinces by years were found to vary between 0.79 and 0.89. According to both regression analyses, all of the input and output variables were found to have significant effects on the efficiency scores of provinces while only the population of province among the control variables was identified as the factor with an effect on the efficiency scores of provinces (p < 0.05).Practical implicationsThe results of this study are thought to guide health policymakers and managers in terms of both determining efficient and inefficient hospitals at the provincial level and revealing which variables should be taken into account in order to increase efficiency.Originality/valueThe study differs from previous studies on the efficiency of hospitals. First, although previous studies were generally descriptive studies to determine the efficiency level of hospitals, this study is an analytical study that tries also to show the factors affecting the efficiency of hospitals. In addition, while examining the effect of input and output variables on efficiency scores, control variables were also included in the study.

An integrated approach for identifying the efficiency-oriented drivers of electronic markets in electronic business

2019 ◽  
Vol 32 (1) ◽  
pp. 60-74 ◽  
Author(s):  
Sophia Xiaoxia Duan ◽  
Hepu Deng ◽  
Feng Luo
Keyword(s):  
Regression Analysis ◽  
Integrated Approach ◽  
Electronic Business ◽  
Tobit Regression ◽  
Content Type ◽  
Novel Approach ◽  
Dea Analysis ◽  
Evaluation Problem ◽  
Overall Efficiency ◽  
Tobit Regression Analysis

Purpose Effectively evaluating the efficiency of individual e-markets for better understanding the efficiency-oriented critical drivers for individual e-markets is of great significance to the development of electronic business. The purpose of this paper is to develop an approach through adequately integrating data envelopment analysis (DEA) and bootstrapped Tobit regression analysis for identifying the efficiency-oriented critical drivers on the development of e-market in electronic business. Design/methodology/approach A review of the related literature is conducted for adequately formulating the e-market evaluation problem. DEA is appropriately used for assessing the efficiency of available e-markets, leading to the identification of the efficient e-market. Tobit regression analysis is then employed to examine the outcome of the DEA analysis for identifying the efficiency-oriented critical drivers in the development of e-markets in electronic business. Findings A better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business can be achieved with the use of the developed approach. Such understanding is built on the identification of the efficiency-oriented critical drivers on the development of e-market in electronic business. Originality/value This paper develops a novel approach for better understanding of the operations of individual e-markets with respect to their overall efficiency in electronic business. The adoption of this approach helps existing e-markets improve their efficiency by focussing on the efficiency-oriented critical drivers and provide new players in e-markets with guidelines for developing their efficient e-markets.

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

2021 ◽  
Vol 10 (04) ◽  
pp. 258-268
Author(s):  
Pantri Widyastuti ◽  
Atik Nurwahyuni
Keyword(s):  
Systematic Review ◽  
Data Envelopment Analysis ◽  
Hospital Efficiency ◽  
Data Envelopment ◽  
Truncated Regression ◽  
Tobit Regression

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.

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