Separating managerial inefficiency from influences of the operating environment: an application in dialysis

Two-Step Estimation of the Impact of Contextual Variables on Technical Efficiency of Hospitals: The Case Study of Public Hospitals in Iran

Background: Measuring the efficiency and productivity of hospitals is a key tool to cost contamination and management that is very important for any healthcare system for having an efficient system. Objective: The purpose of this study is to examine the effects of contextual factors on hospital efficiency in Iranian public hospitals. Methods: This was a quantitative and descriptive-analytical study conducted in two steps. First, we measured the efficiency score of teaching and non-teaching hospitals by using the Data Envelopment Analysis (DEA) method. Second, the relationship between efficiency score and contextual factors was analyzed. We used median statistics (first and third quarters) to describe the concentration and distribution of each variable in teaching and non-teaching hospitals, then the Wilcoxon test was used to compare them. The Spearman test was used to evaluate the correlation between the efficiency of hospitals and contextual variables (province area, province population, population density, and the number of beds per hospital). Results: On average, the efficiency score in non-teaching hospitals in 31 provinces was 0.67 and for teaching hospitals was 0.54. Results showed that there is no significant relationship between the efficiency score and the number of hospitals in the provinces (p = 0.1 and 0.15, respectively). The relationship between the number of hospitals and the population of the province was significant and positive. Also, there was a positive relationship between the number of beds and the area of the province in both types of teaching and non-teaching hospitals. Conclusion: Multilateral factors influence the efficiency of hospitals and to address hospital inefficiency multi-intervention packages focusing on the hospital and its context should be developed. It is necessary to pay attention to contextual factors and organizational architecture to improve efficiency.

Comparing public and private providers: a scoping review of hospital services in Europe

BACKGROUND

What is common to many healthcare systems is a discussion about the optimal balance between public and private provision. This paper provides a scoping review of research comparing the performance of public and private hospitals in Europe. The purpose is to summarize and compare research findings and to generate questions for further studies.

METHODS

The review was based on a methodological approach inspired by the British EPPI-Centre's methodology. This review was broader than review methodologies used by Cochrane and Campbell and included a wider range of methodological designs. The literature search was performed using PubMed, EconLit and Web of Science databases. The search was limited to papers published from 2006 to 2016. The initial searches resulted in 480 studies. The final sample was 24 papers. Of those, 17 discussed economic effects, and seven studies addressed quality.

RESULTS

Our review of the 17 studies representing more than 5500 hospitals across Europe showed that public hospitals are most frequently reported as having the best economic performance compared to private not-for-profit (PNFP) and private for-profit (PFP) hospitals. PNFP hospitals are second, while PFP hospitals are least frequently reported as superior. However, a sizeable number of studies did not find significant differences. In terms of quality, the results are mixed, and it is not possible to draw clear conclusions about the superiority of an ownership type. A few studies analyzed patient selection. They indicated that public hospitals tend to treat patients who are slightly older and have lower socioeconomic status, riskier lifestyles and higher levels of co-morbidity and complications than patients treated in private hospitals.

CONCLUSIONS

The paper points to shortcomings in the available studies and argues that future studies are needed to investigate the relationship between contextual circumstances and performance. A big weakness in many studies addressing economic effects is the failure to control for quality and other operational dimensions, which may have influenced the results. This weakness should also be addressed in future comparative studies.

The effect of quality and socio-demographic variables on efficiency measures in primary health care

This paper aims to extend the literature on measuring efficiency in primary health care by considering the influence of quality indicators and environmental variables conjointly in a case study. In particular, environmental variables are represented by patients' characteristics and quality indicators are based on technical aspects. In order to deal with both aspects, different extensions of data envelopment analysis (DEA) methodology are applied. Specifically, we use weight restrictions to ensure that the efficiency scores assigned to the evaluated units take quality data into account, and a four-stage model to identify which exogenous variables have impact on performance as well as to compute efficiency scores that incorporate this information explicitly. The results provide evidence in support of the importance of including information about both aspects in the analysis so that the efficiency measures obtained can be interpreted as an accurate reflection of performance.

A multiple stage approach for performance improvement of primary healthcare practice

Chilean primary healthcare practice is analyzed using a Data Envelopment Analysis (DEA) multiple stage approach. We estimate the efficiency level of 259 municipalities nationwide. Since the efficiency score by itself is of limited value for decision making, we use a multivariate tool to help explain the effect of relevant factors. First, we use a cluster analysis to homogenize the units under study. Second, we use DEA to estimate the efficiency levels, which varies from 61% to 71% for urban municipalities, and from 51% to 56% in rural ones. Third, we use bootstrap to estimate confidence intervals for the efficiency scores, and a Biplot method to identify adequate variables to include in the Tobit Model, which is our last stage. We identify six factors associated with rural municipalities' operational efficiency, and two with urban ones. Knowing the efficiency level of municipalities can help determine ways to improve their efficiency.

Improving the efficiency of distributive and clinical services in hospital pharmacy

Three problems impede the assessment of hospital pharmacy efficiency. First, although multiple efficiency indicators are utilized to measure a large variety of activities, it has not been possible to validly measure overall efficiency. Second, there have been no widely-used clinical activity indicators, so key outputs often have not been accounted for. Third, there has been no effective methodology for identifying when declines in efficiency are normal random variations and when they represent true decreases in performance. This paper presents a procedure that simultaneously addresses these three problems. It analyzes data from a group of U.S. hospital pharmacies that collect an inclusive set of clinical and distributional indicators. It employs Data Envelopment Analysis to develop comprehensive efficiency measures from the numerous outputs and inputs. It applies statistical Panel Data Analysis to estimate confidence intervals within which each pharmacy's true efficiency resides, and to develop control charts for signaling when a pharmacy's efficiency has declined by more than can be attributed to random variation. This integrated efficiency evaluation system is transferable to other hospital pharmacy systems, thereby offering decision makers a better way of measuring, controlling and improving hospital pharmacy efficiency.