Quantifying the effects of modelling choices on hospital efficiency measures: A meta-regression analysis

It has often been argued that the results of efficiency analyses in health care are influenced by the modelling choices made by the researchers involved. In this paper we use meta-regression analysis in an attempt to quantify the degree to which modelling factors influence efficiency estimates. The data set is derived from 253 estimated models reported in 95 empirical analyses of hospital efficiency in the 22-year period from 1987 to 2008. A meta-regression model is used to investigate the degree to which differences in mean efficiency estimates can be explained by factors such as: sample size; dimension (number of variables); parametric versus non-parametric method; returns to scale (RTS) assumptions; functional form; error distributional form; input versus output orientation; cost versus technical efficiency measure; and cross-sectional versus panel data. Sample size, dimension and RTS are found to have statistically significant effects at the 1% level. Sample size has a negative (and diminishing) effect on efficiency; dimension has a positive (and diminishing) effect; while the imposition of constant returns to scale has a negative effect. These results can be used in improving the policy relevance of the empirical results produced by hospital efficiency studies.

Measuring intra-hospital clinic efficiency and productivity : an application to a Greek university general hospital

In this paper we use Data Envelopment Analysis and the Malmquist Productivity Index and its decompositions to assess the productive efficiency and productivity of the in-patient clinics of a large Greek University General Hospital. Clinics are represented by means of a simple model whereby they use inputs (labor and capital) to produce outputs (in-patient days and patient discharges). The efficiency model is input oriented and assumes constant returns to scale. Model validation analyses showed that this model appears to be externally valid. The framework proposed here is a simple and useful tool for informing intra-hospital management decisions.peer-reviewe

“High Spending, Poor Productivity Gains!” Assessing Public Health System (In)Efficiency and Hospital Performance In The State Of Kuwait: Would More Private Delivery Improve Healthcare?

The healthcare sector in the State of Kuwait has been nurtured for many decades by the government, where the majority of health services in the country are controlled by the Ministry of Health (MoH). Although healthcare services in public sector hospitals are at highly subsidized rates, causing private sector involvement in healthcare to be considerably low, the growing demands for private delivery of care burgeoned participation of private hospitals in Kuwait, and improving hospital efficiency and productivity is more critical and timelier than ever. This dissertation aims to analyze public health system efficiency and hospital performance in the State of Kuwait using data envelopment analysis (DEA) techniques; where we begin by evaluating the input-oriented technical efficiency (TE) of MoH hospitals in 2015-2019 and identifying potential areas for efficiency improvement by exploring influencing institutional and environmental factors. We further conduct an output-oriented comparative study of public-private productivity in view of ownership, hospital management, and other external variables to understand drivers of productive efficiency and potential factors of output maximization disparities in 2019/2020

Tomorrow’s public hospital in Greece: Managing health care in the post crisis era

Η νοσοκομειακή διοίκηση (οριζόμενη ως ηπροσπάθεια για την βέλτιστη απόδοση μέσωκατάλληλων κύκλων σχεδιασμού, αποφάσεων, αξιολόγησης και επανελέγχου) τέμνει όλεςτις λειτουργικές παραμέτρους παραγωγής καιπροσφοράς υπηρεσιών υγείας. Το δημόσιοΕλληνικό νοσοκομείο του αύριο θα πρέπει νααπαντήσει στις τέσσερις προβληματικές ενότητες του σημερινού συστήματος: τον ιατρικόυποκειμενισμό, το απαρχαιωμένο μοντέλο διοίκησης, την έλλειψη εργαλείων διαχείρισηςανθρώπινου δυναμικού και την προβληματικήχρηματοδότηση των ελληνικών νοσοκομείων.Το νοσοκομείο του αύριο θα πρέπει να σέβεται την αυτονομία του ιατρικού επαγγέλματοςενώ ταυτόχρονα να απαιτεί επιστημονική λογοδοσία, θα πρέπει να χρησιμοποιεί μοντέρναεργαλεία επιχειρησιακής οργάνωσης ώστε ναδιαχειριστεί το ανθρώπινο δυναμικό του μεαπώτερο στόχο την αποδοτική και αποτελεσμα-τική παραγωγή υπηρεσιών υγείας και τέλος θαπρέπει να μετράει την απόδοση του σε κάθεπεριστατικό. Σε αυτή την κατεύθυνση θα κατευθυνθούν τα νοσοκομεία τα επόμενα χρόνια.The management of the hospitals (definedas the attempt for optimum performancevia appropriate cycles of planning, deciding,evaluating, and reviewing), transcends allthe functional parameters of the productionand provision of health services. Tomorrow’spublic hospital in Greece demands anew managerial approach. This approachwould sufficiently answer to the main fourproblematic conundrum of today: the perverseunaccountability of medical subjectivity, theobsolete management model, the lack ofhuman resources management tools and theunhealthy financing of hospitals. Tomorrow’shospital would respect the autonomy of themedical profession while at the same timewould demand scientific accountability,would utilize modern organizational toolsto manage its human resources in order toproduce effectively and efficiently qualityservices and finally would measure itsperformance on a case by case basis

Data Envelopment Analysis for Relative Efficiency Measurement of Chinese Hospitals: A Systematic Review

The purpose was to explore the gap between China and the international world in efficiency measurement of hospitals with Data Envelopment Analysis, and to improve the standardization of healthcare efficiency measurement in China. A systematic review was conducted using appropriate search strategies. Studies were included containing DEA approaches regarding general hospital efficiency, published in international literature and in both Chinese and English about Chinese hospitals from January 2004 to October 2014. The results showed that statistical significances were found in indicators such as number of DMUs, percentage of allocative efficiency studies, ratio of studies with multiple years, number of studies with monetary indicators in input and output sets, etc. The statistical insignificance in some indicators such as the number of input and output indicators were also found among China, Europe, USA and others. Some problems were found in current DEA-based hospital efficiency studies in China, such as inappropriate selection of input-output indicators, no bias-correction on efficiency scores, etc. The standardization of DEA methods applied in China’s hospital efficiency research needs to be improved. Chinese researchers should pay more attention to latest international research findings, so as to keep pace with the cutting edge hospital efficiency research

Measuring across hospital efficiency and productivity : the case of second regional health authority of Attica

The purpose of the study is to investigate technical efficiency and productivity change of a sample of Greek Hospitals over the period 1998 - 2005. Efficiency and productivity measurement became a crucial issue in Greece after the launching of health reforms in 2001, with the legislative Act No. 2889, aiming at cost containment and improvements in hospital efficiency. Applying the linear programming method of Data Envelopment Analysis we investigate how efficiently the hospital resources are used to obtain the maximum possible outcome, before and after the reforms. Hospital output is modelled in terms of interventions, laboratory examinations, outpatient and inpatient cases. Inputs considered include beds, doctors, nurses and rest personnel and operational expenses. The analysis indicates that the reforms have generated efficiency gains when only input and output quantities are considered. During the period 1998- 2002 an overall efficiency regress is observed followed by an upturn, after the launching of managerial reforms. However, when the running costs of the hospitals are considered, then the sample experiences significant regress, implying relatively higher production costs over time. We conclude that DEA is a useful technique to assess relative efficiency and optimum hospital performance across hospitals.peer-reviewe

The macroeconomic implications of healthcare. Bruegel Policy Contribution Issue n˚11 | August 2018

Health-care systems play a crucial role in supporting human health. They also have major macroeconomic implications, an aspect that is not always properly acknowledged. Countries spend very different amounts on healthcare, with spending in North America (Canada and the United States) more than twice as much per capita as in the European Union on average, and there are significant differences between EU countries too. Various explanatory factors such as income levels, population age structures and epidemiological profiles cannot explain the differences between countries. Decisions on the optimal level of spending should also consider various others factor, including the macroeconomic implications of health-care systems. Whatever amount is spent on health care, it should be spent efficiently, in order not to waste resources and to improve the macroeconomic impacts. We demonstrate that there are threshold effects whereby certain quantitative indicators of health tend to improve with increased spending only up to certain amount of spending, but not further. Using a standard method to measure efficiency, data envelopment analysis (DEA), we find significant differences between countries, suggesting that not all countries use existing technologies and best practices to their full potential. This finding calls for policy responses. Health-care systems matter for the macroeconomy because of their large size in output, employment and research. They also have direct fiscal implications in terms of the long-term sustainability of public finances, while health-care spending decisions influence short-term economic development through the fiscal multiplier effect, which is substantial. Most southern European countries cut health-care spending aggressively in recent years, likely amplifying the depth of their recessions and possibly causing hysteresis effects from long-term unemployment and reduced productivity. Fiscal consolidation strategies should aim to preserve spending items that have large fiscal multipliers, including health-care expenditures. Health-care systems also influence labour force participation, productivity and human capital formation through various channels, and thereby have an influence on overall macroeconomic outcomes. They also play an important role in inequality, and we find that inequality of access to health care is particularly high in about one-third of EU countries, which calls for policy responses. It is essential that discussions of health systems consider both the opportunity cost and the economic value of investing in health. Such an approach can help policymakers resist the temptation to default to the potentially inefficient status quo

An application of statistical interference in DEA models: An analysis of public owned university departments' efficiency

This paper uses Data Envelopment Analysis (DEA) model formulations in order to determine the performance levels of 16 departments of the University of Thessaly. Particularly, the constant returns to scale (CRS) and variable returns to scale (VRS) models have been applied alongside with bootstrap techniques in order to determine accurate performance measurements of the 16 departments. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating institutional performance issues. The paper provides the efficient departments and the target values which need to be adopted from the inefficient departments in order to operate in the most productive scale size (MPSS). Moreover it provides bias corrected estimates alongside with their confidence intervals. The analysis indicates that there are strong inefficiencies among the departments, emphasizing the misallocation of resources or/and inefficient application of departments policy developments.University efficiency; DEA; Bootstrap techniques; Kernel density estimation, Economic research; Europe; University rankings.

A DEA approach to regional development

Our research is based on the effect of fiscal policies on the Greek prefectures. Using DEA methodology we compare the efficiency of the prefectures over the last three decades. Moreover, we determine where the resources are distributed in an efficient way and /or have been used efficiently by the local authorities in order to stimulate regional development and provide quality of life to the Greek citizens. The efficient prefectures seem to have definite and strong characteristics, which are determined and discussed in detail. Our empirical results imply that the resources of a prefecture don’t necessarily ensure the efficiency of this prefecture.Data Envelopment Analysis; Regional Development; Living Standards; Greek Prefectures

How efficient are Kenyan hospitals? : an application of frontier analysis techniques

Efficiency is an important concern for health systems. This includes delivery of the health care, health financing, and investment on hospital facilities and the management of health facilities. Measurement of efficiency in health facilities is important to ensure maximum allocation and utilization of limited resources. The aim of this study was to estimate efficiency in level IV Kenyan hospitals using data envelopment analysis and stochastic frontier analysis. Panel data were collected from 27 public and faith-based hospitals between 2008 and 2012. Data envelopment analysis (DEA), a non-parametric approach and stochastic frontier analysis (SF A) a parametric approach were applied to the data. Ownership as a factor of efficiency was assessed from the collected samples. The results show evidence of technical inefficiencies across the hospitals. Based on DEA bootstrapped model, the efficiency scores was 0.7597 and 0.7751 for 2011 and 2012 data respectively. Using the cross sectional data set, SFA values were comparable to DEA with an average of 0.7919 and 0.7701 for the 2011 and 2012 data sets respectively. Based on the panel data, the SF A model gave a range of scores that were between 0.62 (Pitt and Lee and Battese and Coelli) and 0.85 (true effect models). There was no evidence of patterns in efficiency scores over time based on both DEA and SF A approaches. This data did not suggest a significant effect on efficiency based on hospital ownership. In conclusion, this study shows presence of technical inefficiencies in Kenyan hospitals. It also provides a platform in exploring further the frontier techniques and incorporating ownership when measuring efficiency in Kenyan hospitals