Public vs. Private in Hospital Efficiency: Exploring Determinants in a Competitive Environment

Guerrini, Andrea; Romano, Giulia; Campedelli, Bettina; Moggi, Sara; Leardini, Chiara

doi:10.1080/01900692.2016.1256892

Cited by 24 publications

(23 citation statements)

References 41 publications

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“…Assessing the determinants of efficiency allows managers to formulate appropriate organizational strategies to meet the challenges associated with continuous change. Focusing on the Italian National Health System, Guerrini et al [ 4 ] note that in recent years, increasing attention has been paid to ensuring financial equilibrium and reducing the average annual growth rate of total health expenditure per capita. Italy has a regionally based National Health System that provides universal coverage free of charge [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Orsini

Leardini

Vernizzi

et al. 2021

BMC Health Serv Res

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Background The objective of this study was to assess public hospital efficiency, including quality outputs, inefficiency determinants, and changes to efficiency over time, in an Italian region. To achieve this aim, the study used secondary data from the Veneto region for the years 2018 and 2019. Methods A nonparametric approach—that is, multistage data envelopment analysis (DEA)—was applied to a sample of 43 hospitals. We identified three categories of input: capital investments (Beds), labor (FTE), operating expenses. We selected five efficiency outputs (outpatient visits, inpatients, outpatient visit revenue, inpatient revenue, bed occupancy rate) and two quality outputs (mortality rate and inappropriate admission rate). Efficiency scores were estimated and decomposed into two components. Slack analysis was then conducted. Further, DEA efficiency scores were regressed on internal and external variables using a Tobit model. Finally, the Malmquist Productivity Index was applied. Results On average, the hospitals in the Veneto region operated at more than 95% efficiency. Technical and scale inefficiencies often occurred jointly, with 77% of inefficient hospitals needing a downsizing strategy to gain efficiency. The inputs identified as needing significant reductions were full-time employee (FTE) administrative staff and technicians. The size of the hospital in relation to the size of the population served and the length of patient stay were important factors for the efficiency score. The major cause of decreased efficiency over time was technical change (0.908) rather than efficiency change (0.974). Conclusions The study reveals improvements that should be made from both the policy and managerial perspectives. Hospital size is an important feature of inefficiency. On average, the results show that it is advisable for hospitals to reorganize nonmedical staff to enhance efficiency. Further, increasing technology investment could enable higher efficiency levels.

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Section: Introductionmentioning

confidence: 99%

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Orsini

Leardini

Vernizzi

et al. 2021

BMC Health Serv Res

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“…The study by Du (2018) conducted on the hospitals in 31 provinces of China reflected that the efficiency score decreases as the number of other health personnel increases. The study by Guerrini et al (2018) regarding the public and private hospitals in Italy showed that there is a negative correlation between the number of beds and efficiency scores. Similarly, the study by Nistor et al (2017) conducted on the developing countries showed that there is a negative relationship between the number of physicians and efficiency; while there is not any significant relationship between the number of beds and efficiency.…”

Section: Discussionmentioning

confidence: 99%

“…The control variables can take place as institutional and environmental factors, although they differ according to the purpose of the research (Bobo et al, 2018). Numbers of hospitals, beds, physicians, nurses þ midwives and other health personnel used as inputs in this study were also used as inputs in the studies conducted by Afonso and Aubyn (2011), Mutter et al (2008), Bilsel and Davutyan (2014), Lobo et al (2014), Karagiannis (2015), Samut and Cafri (2016), Chowdury and Zelenyuk (2016), Nistor et al (2017), Guo et al (2017), Du (2018), Guerrini et al (2018), Bobo et al (2018) and Habib and Shahwan (2020). Similarly, it has been observed that the variables of number of outpatients, proportion of inpatients and surgeries and risk-adjusted crude mortality rate are used in most studies in the literature (Mutter et al, 2008;Bilsel and Davutyan, 2014;Lobo et al, 2014;Chowdury and Zelenyuk, 2016;Nistor et al, 2017;Guo et al, 2017;Du, 2018;Bobo et al, 2018;Habib and Shahwan, 2020).…”

Section: Rq1mentioning

confidence: 99%

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

Şahin

İlgün

Sönmez

2021

BIJ

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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.

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“…For instance, Chai et al [ 5 ] evaluate the productivity and efficiency of health production pre- and post-reform periods, compare the effects across all the 31 provinces of mainland China and identify potential determinants. Various other studies have explored the question of how health inputs are used to generate the highest possible outcomes both at the micro level [ 17 , 18 ] and the macro level [ 19 , 20 , 21 ].…”

Section: Brief Literature Reviewmentioning

confidence: 99%

An Empirical Analysis of Income Elasticity of Out-of-Pocket Healthcare Expenditure in Mauritius

Jeetoo

Jaunky

2022

Healthcare

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A free universal healthcare provision exists in Mauritius. Yet the share of out-of-pocket healthcare expenditure out of total household expenditure has been growing over time. This study estimates income elasticity of out-of-pocket healthcare expenditure using Mauritian household data within an Engel curve framework. In the absence of longitudinal data on out-of-pocket healthcare expenditure patterns, the study proposes the application of the pseudo-panel approach using cross-sectional Household Budget Survey waves from 1996/97 to 2017. Income elasticity of out-of-pocket healthcare expenditure is estimated to be 0.938, which is just below unity. This implies that out-of-pocket healthcare demand is not considered to be a luxury, but a necessity in Mauritius. In order to see the differences in income elasticities by income groups, separate regressions are estimated for each income quartile over different years. The results indicate that income elasticities of out-of-pocket healthcare expenditure vary non-monotonically.

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Public vs. Private in Hospital Efficiency: Exploring Determinants in a Competitive Environment

Cited by 24 publications

References 41 publications

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

Inefficiency of public hospitals: a multistage data envelopment analysis in an Italian region

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

An Empirical Analysis of Income Elasticity of Out-of-Pocket Healthcare Expenditure in Mauritius

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