Using data envelopment analysis for assessing the performance of pediatric emergency department physicians

The Application of Data Envelopment Analysis to Emergency Departments and Management of Emergency Conditions: A Narrative Review

The healthcare industry is one application for data envelopment analysis (DEA) that can have significant benefits for standardizing health service delivery. This narrative review focuses on the application of DEA in emergency departments (EDs) and the management of emergency conditions such as acute ischemic stroke and acute myocardial infarction (AMI). This includes benchmarking the proportion of patients that receive treatment for these emergency conditions. The most frequent primary areas of study motivating work in DEA, EDs and management of emergency conditions including acute management of stroke are sorted into five distinct clusters in this study: (1) using basic DEA models for efficiency analysis in EDs, i.e., applying variable return to scale (VRS), or constant return to scale (CRS) to ED operations; (2) combining advanced and basic DEA approaches in EDs, i.e., applying super-efficiency with basic DEA or advanced DEA approaches such as additive model (ADD) and slack-based measurement (SBM) to clarify the dynamic aspects of ED efficiency throughout the duration of a first-aid program for AMI or heart attack; (3) applying DEA time series models in EDs like the early use of thrombolysis and percutaneous coronary intervention (PCI) in AMI treatment, and endovascular thrombectomy (EVT) in acute ischemic stroke treatment, i.e., using window analysis and Malmquist productivity index (MPI) to benchmark the performance of EDs over time; (4) integrating other approaches with DEA in EDs, i.e., combining simulations, machine learning (ML), multi-criteria decision analysis (MCDM) by DEA to reduce patient waiting times, and futile transfers; and (5) applying various DEA models for the management of acute ischemic stroke, i.e., using DEA to increase the number of eligible acute ischemic stroke patients receiving EVT and other medical ischemic stroke treatment in the form of thrombolysis (alteplase and now Tenecteplase). We thoroughly assess the methodological basis of the papers, offering detailed explanations regarding the applied models, selected inputs and outputs, and all relevant methodologies. In conclusion, we explore several ways to enhance DEA's status, transforming it from a mere technical application into a strong methodology that can be utilized by healthcare managers and decision-makers.

A Fuzzy Hybrid MCDM Approach for Assessing the Emergency Department Performance during the COVID-19 Outbreak

The use of emergency departments (EDs) has increased during the COVID-19 outbreak, thereby evidencing the key role of these units in the overall response of healthcare systems to the current pandemic scenario. Nevertheless, several disruptions have emerged in the practical scenario including low throughput, overcrowding, and extended waiting times. Therefore, there is a need to develop strategies for upgrading the response of these units against the current pandemic. Given the above, this paper presents a hybrid fuzzy multicriteria decision-making model (MCDM) to evaluate the performance of EDs and create focused improvement interventions. First, the intuitionistic fuzzy analytic hierarchy process (IF-AHP) technique is used to estimate the relative priorities of criteria and sub-criteria considering uncertainty. Then, the intuitionistic fuzzy decision making trial and evaluation laboratory (IF-DEMATEL) is employed to calculate the interdependence and feedback between criteria and sub-criteria under uncertainty, Finally, the combined compromise solution (CoCoSo) is implemented to rank the EDs and detect their weaknesses to device suitable improvement plans. The aforementioned methodology was validated in three emergency centers in Turkey. The results revealed that the most important criterion in ED performance was ER facilities (14.4%), while Procedures and protocols evidenced the highest positive D + R value (18.239) among the dispatchers and is therefore deemed as the main generator within the performance network.

Analysis of the effect of patients' health status on efficiency: Application of data envelopment analysis in healthcare

The effective and efficient operation of public healthcare systems is more and more important as a consequence of the increasing amount of money spent on their operation. For this reason, accurate and science-based efficiency information is needed for managers and healthcare policy makers. The evaluation of the efficiency in this sector is particularly difficult because several measures and indicators are used. Data envelopment analysis (DEA) can provide aggregate and overall measures of efficiency. The purpose of this paper is the examination of the efficiency of in-patient rehabilitation units curing musculoskeletal disorders in Hungary. The research presented focuses on rehabilitation units which attend to patients recovering from stroke or other acquired brain injuries. Output-oriented, slack-based DEA models are applied for the evaluation of in-patient rehabilitation units using data of a national survey. The novelty of the method presented is the consideration of the change in patients' functional status when efficiency is evaluated using DEA.

Measuring the efficiency of Turkish maternal and child health hospitals: A two-stage data envelopment analysis

This study aims to examine the changes in efficiency and efficiency levels of the maternal and child health hospitals in Turkey from 2014 to 2017, by applying two-stage data envelopment analysis (DEA). At the first stage of the study, the efficiency of the hospitals was evaluated with input-oriented CCR (Charnes, Cooper, Rhodes) and Malmquist Productivity Index (MPI). At the second stage, panel Tobit regression analysis was utilized to find out the factors that affect the efficiency scores specified at the first stage. According to the results of the first stage, the mean efficiency values calculated for 2014, 2015, 2016, and 2017 were 0.83, 0.90, 0.86, and 0.80, respectively. At the second stage, it was revealed that the variables of not being in a metropolis and having 200 beds at least had statistically a significant effect on the efficiency score (p < 0.05) whereas being a training and research hospital was ineffective (p > 0.05). The number of the studies which assess the efficiency of maternal and child health hospitals in Turkey was quite limited. Moreover, such studies do not contain second-stage analyses. Lastly, it is thought that those results will provide health policy-makers substantial and evidence-based information in the allocation of the resources for the related services.

The effects of ethnic diversity and friendship ties on managers' emotional exhaustion: a network-based case study of Caribbean information technology firms

Purpose

The purpose of this article is to empirically examine the relationship between managers' emotional exhaustion and the ethnic diversity, workload requirements, and friendship ties within their work-groups.

Design/methodology/approach

The research employs a full-network sample of all managers from an indigenously owned ethnically diverse IT firm located in the Caribbean island nation of Trinidad and Tobago. Using a social network design within a regression model, the relationship between managerial power and operational workload and the burnout dimension of emotional exhaustion is initially examined as a baseline model. Work-group ethnicity and friendship ties are then examined as moderators to this relationship. The authors then examine the role of work-group ethnicity and friendship ties as a buffer mechanism using an efficient frontier analysis where managers act as decision-making units.

Findings

The study indicates that ethnic diversity acts more as a “negative moderator” to emotional exhaustion, while friendship ties act as both a “positive moderator” and “buffer” to work-related emotional exhaustion.

Originality/value

This is one of the few empirical studies that has examined the issues of ethnic diversity and burnout using social network and efficient frontier methodologies. This is also one of the first empirical studies to investigate these issues using an in-depth, full-sample case study of actual, real-work network relationships.

Evaluating the Technical Efficiency of Hospitals Providing Tertiary Health Care in Turkey: An Application Based on Data Envelopment Analysis

Tertiary care hospitals use more resources compared to other hospitals, which makes technical efficiency measurements specific to these hospitals important. This study explored the factors affecting the efficiencies of training and research hospitals affiliated to the Ministry of Health (n = 41) and university hospitals (n = 51) in Turkey via Data Envelopment Analysis, Malmquist Total Factor Productivity Index and panel Tobit Regression. The results showed that hospital size and the status of being a training and research or a university hospital affected the technical efficiency (p < 0.05). The size and the status of the hospitals should be taken into consideration while allocating the resources.

Measuring the operational and financial efficiency using a Malmquist data envelopment analysis: a case of Egyptian hospitals

Purpose

The efficient use of organizational resources is integral to the existence of prime firms. This study, using Malmquist data envelopment analysis (DEA), aims to assess in the level of operational and financial efficiency and its determinants for ensuring and sustaining excellent performance in 33 Egyptian private hospitals.

Design/methodology/approach

This study adopted a Malmquist DEA approach to assess the changes in operational and financial efficiency in Egyptian hospitals. Tobit regression was also used to identify the significant variables affecting their efficiency. In addition, a sensitivity analysis is carried out for model validations.

Findings

Out of 33 hospitals, 17 were found inefficient due to the decline in their technical efficiency. Moreover, the total value of the software programs and operational expenses and the total number of employees are common factors affecting both operational and financial efficiency. In addition, the number of physicians significantly affects the hospital's financial efficiency.

Practical implications

The study sheds light on the value of using DEA to assess efficiency. DEA in the context of emerging economy such as Egypt's can be a useful tool for decision-makers and practitioners in identifying and addressing performance weaknesses and thus supports continuous improvement in performance.

Originality/value

Several studies have adopted the DEA approach to assess the overall efficiency of hospitals in Europe and the United States. However, in the MENA region, these studies are uncommon. This study is thought to be one of the earliest attempts to assess hospitals' efficiency in Egypt.

Data envelopment analysis applications in primary health care: a systematic review

BACKGROUND

Strategic management of primary health care centres is necessary for creating an efficient global health care system that delivers good care.

OBJECTIVES

To perform a systematic literature review of the use of data envelopment analysis in estimating the relative technical efficiency of primary health care centres, and to identify the inputs, outputs and models used.

METHODS

PubMed, MEDLINE Complete, Embase and Web of Science were searched for papers published before the 25 March 2019.

RESULTS

Of a total of 4231 search results, 54 studies met the inclusion criteria. The identified inputs included personnel costs, gross expenditures, referrals and days of hospitalization, as well as prescriptions and investigations. Outputs included consultations or visits, registered patients, procedures, treatments and services, prescriptions and investigations. A variety of data envelopment analysis models used was identified, with no standard approach.

CONCLUSIONS

Data envelopment analysis extends the scope of tools used to analyse primary care functioning. It can support health economic analyses when assessing primary care efficiency. The main issues are setting outputs and inputs and selecting a model best suited for the range of products and services in the primary health care sector. This article serves as a step forward in the standardization of data envelopment analysis, but further research is needed.

Business school teams up with clinical innovators: An opportunity for health system transformation

Healthcare represents one of the largest sectors in the economy with the health spending on average accounting for about 9% of GDP in OECD countries. Canada was projected in 2018 to spend about 11% of its GDP on healthcare with an expected health expenditure growth of 4.2%. Addressing this issue asks for a redesign of health delivery system and associated cultural shift allowing for incorporation of industry and business best practices. To make this redesign happen, system transformation requires seeking out new institutional mechanisms, partnerships, and forums where industry leaders in business and healthcare can develop a top-down approach with a shared vision, shared best practices, and support coming from a bottom-up approach through pilots and scaling-up initiatives. In this article, we describe one successful partnership initiative-Telfer Health Transformation Exchange at the Telfer School of Management at the University of Ottawa.

Measuring the efficiency of Palestinian public hospitals during 2010-2015: an application of a two-stage DEA method

Background

While health needs and expenditure in the Occupied Palestinian Territories (OPT) are growing, the international donations are declining and the economic situation is worsening. The purpose of this paper is twofold, to evaluate the productive efficiency of public hospitals in West Bank and to study contextual factors contributing to efficiency differences.

Methods

This study examined technical efficiency among 11 public hospitals in West Bank from 2010 through 2015 targeting a total of 66 observations. Nationally representative data were extracted from the official annual health reports. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. To elaborate further on performance, we used Tobit regression to identify contextual factors whose impact on inefficient performance is statistically significant.

Results

Despite the increase in efficiency mean scores by 4% from 2010 to 2015, findings show potential savings of 14.5% of resource consumption without reducing the volume of the provided services. The significant Tobit model showed four predictors explaining the inefficient performance of a hospital (p <  0.01) are: bed occupancy rate (BOR); the outpatient-inpatient ratio (OPIPR); hospital’s size (SIZE); and the availability of primary healthcare centers within the hospital’s catchment area (PRC). There is a strong effect of OPIPR on efficiency differences between hospitals: A one unit increase in OPIPR will lead a decrease of 19.7% in the predicted inefficiency level holding all other factors constant.

Conclusion

To date, no previous studies have examined the efficiency of public hospitals in the OPT. Our work identified their efficiency levels for potential improvements and the determinants of efficient performance. Based on the measurement of efficiency, the generated information may guide hospitals’ managers, policymakers, and international donors improving the performance of the main national healthcare provider. The scope of this study is limited to public hospitals in West Bank. For a better understanding of the Palestinian market, further research on private hospitals and hospitals in Gaza Strip will be useful.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3228-1) contains supplementary material, which is available to authorized users.