Health systems: changes in hospital efficiency and profitability

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals. We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

Efficiency effects of public hospital closures in the context of public hospital reform: a multistep efficiency analysis

In the wake of hospital reforms introduced in 2011 in Turkey, public hospitals were grouped into associations with joint management and some shared operational and administrative functions, similar in some ways to hospital trusts in the English National Health Service. Reorganization of public hospitals effect hospital and market area characteristics and existence of hospitals. The objective of this study is to examine the effect of closure on competitive hospital performances. Using administrative data from Turkish Public Hospital Statistical Yearbooks for the years 2005 to 2007 and 2014 to 2017, we conducted a three-step efficiency analysis by incorporating data envelopment analysis (DEA) and propensity score matching techniques, followed by a difference-in-differences (DiD) regression. First, we used bootstrapped DEA to calculate the efficiency scores of hospitals that were located near hospitals that had been closed. Second, we used nearest neighbour propensity score matching to form control groups and ensure that any differences between these and the intervention groups could be attributed to being near a hospital that had closed rather than differences in hospital and market area characteristics. Lastly, we employed DiD regression analysis to explore whether being near a closed hospital had an impact on the efficiency of the surviving hospitals while considering the effect of the 2011 hospital reform policies. To shed light on a potential time lag between hospital closure and changes in efficiency, we used various periods for comparison. Our results suggest that the efficiency of public hospitals in Turkey increased in hospitals that were located near hospitals that closed in Turkey from 2011. Hospital closure improves the efficiency of competitive hospitals under hospital market reforms. Future studies may wish to examine the efficiency effects of government and private sector collaboration on competition in the hospital market.

Relative Efficiency of Radiation Treatment Centers: An Application of Data Envelopment Analysis

This study determines the relative efficiencies of a number of cancer treatment centers in Ontario, taking into account the differences among them so that their performances can be compared against the provincial targets. These differences can be in physical and financial resources, and patient demographics. An analytical framework is developed based on a three-step data envelopment analysis (DEA) model to build efficiency metrics for planning, delivery, and quality of treatment at each center. Regression analysis is used to explain the efficiency metrics and demonstrates how these findings can inform continuous improvement efforts.

(Re)defining nursing leadership: On the importance of parrhèsia and subversion

AIM

Through a review of philosophical and theoretical constructs, this paper offers insight and guidance as to ways in which nurse leaders may operationalize advocacy and an adherence to nursing's core ethical values.

BACKGROUND

The US health care system works in opposition to core nursing values. Nurse leaders are obliged to advocate for the preservation of ethical care delivery.

EVALUATION

This paper draws upon the philosophies of Fromm, Foucault, and Deleuze and Guattari to critically review the functions of nurse leaders within a capitalist paradigm.

KEY ISSUE

Key emergent issues in the paper include health care and capitalism and the nurse leader's obligations towards advocacy.

CONCLUSION

The nurse leader acts as parrhèsia in viewing truth telling as a duty critical to improving the lives of patients. Ramifications of the decisions by those in power have even greater impact in institutions that serve those with little to no political agency.

IMPLICATIONS FOR NURSING MANAGEMENT

The nurse leader has a freedom and platform that their patients do not and must take the courageous risk of choosing to speak. This paper serves as a call to action for nurse leaders to urgently address the current state of US health outcomes.

Risk of hospital insolvency and its relationship with income and borrowings from banks: a case-control study with large-scale financial data in Japan

Considering the variety of stakeholders surrounding hospitals, hospital financial distress should be understood as a social issue, rather than just a matter involving the hospital owners. The present study aimed to assess Japanese hospital insolvency and related factors based on a nationwide financial dataset, and to identify indicators of the risk of insolvency. The legal financial reports used included a balance sheet and a profit-and-loss statement of hospitals owned by healthcare corporations, representing about 70% of all Japanese hospitals. This case-control study with descriptive analyses was conducted to clarify the financial status of healthcare corporations and to assess associations between specific factors and insolvency. Insolvency was found in 5.9% of healthcare corporations in 2016. Insolvency was significantly associated with operational income per sales (odds ratio, 0.16), and both short- and long-term borrowings per sales (odds ratios: 1.46 and 1.22 in this order). The present study found that 5.9% of Japanese healthcare corporations were insolvent, and hospital profitability and borrowing (both short- and long-term) could be key factors related to preventing hospital insolvency in Japan. To maintain sustainable healthcare services by hospitals, decision makers should consider the risk of insolvency, and balance the amount of borrowings against sales.

The increasing impact of length of stay "outliers" on length of stay at an urban academic hospital

BACKGROUND

As healthcare systems strive for efficiency, hospital "length of stay outliers" have the potential to significantly impact a hospital's overall utilization. There is a tendency to exclude such "outlier" stays in local quality improvement and data reporting due to their assumed rare occurrence and disproportionate ability to skew mean and other summary data. This study sought to assess the influence of length of stay (LOS) outliers on inpatient length of stay and hospital capacity over a 5-year period at a large urban academic medical center.

METHODS

From January 2014 through December 2019, 169,645 consecutive inpatient cases were analyzed and assigned an expected LOS based on national academic center benchmarks. Cases in the top 1% of national sample LOS by diagnosis were flagged as length of stay outliers.

RESULTS

From 2014 to 2019, mean outlier LOS increased (40.98 to 45.11 days), as did inpatient LOS with outliers excluded (5.63 to 6.19 days). Outlier cases increased both in number (from 297 to 412) and as a percent of total discharges (0.98 to 1.56%), and outlier patient days increased from 6.7 to 9.8% of total inpatient plus observation days over the study period.

CONCLUSIONS

Outlier cases utilize a disproportionate and increasing share of hospital resources and available beds. The current tendency to exclude such outlier stays in data reporting due to assumed rare occurrence may need to be revisited. Outlier stays require distinct and targeted interventions to appropriately reduce length of stay to both improve patient care and maintain hospital capacity.

Application of the DEA Model in Tourism SMEs: An Empirical Study from Slovakia in the Context of Business Sustainability

Slovak spa services are not given sufficient attention directly following the support and sustainable development. The paper focuses on the evaluation of the overall development and current level of efficiency of the Slovak spas in 2013–2018, through the application of DEA models. Input variables (total number of beds, employees, medical staff) and output variables (use of bed capacity, number of treated clients) within the structure of DEA models analyzed (CCR-I, CCR-O, BCC-I, BCC-O) are determined by results of the correlation analysis. The data were obtained from the annual reports of the spa enterprises. By the results, the average efficiency score for all enterprises reached 0.7527, i.e., the average spa enterprise would need only 75.27% of currently used inputs for a given output production to move to the efficiency frontier. The development of the average efficiency score confirmed a positive growing trend until 2015; however, the efficiency decreased by 1.84% in a year-to-year comparison in 2016–2018. In each year of the analyzed period, the number of inefficient enterprises (66.67%) exceeded that of the efficient ones (33.33%). Through research carried out in spa facilities, the authors contributed to expanding the application of the DEA method in another tourism sector.

Arrangements with the NHS for providing healthcare services: do they improve financial performance of private for-profit hospitals in Spain?

BACKGROUND

In developed countries around the world there is a trend to enhance the public-private collaboration in healthcare. In Spain, a decentralized country with a NHS funded with taxes and universal coverage, commissioning to for-profit private hospitals the production of healthcare services to specific patients that are publicly insured is a traditional practice. Around 43% of the for-profit private hospitals in Spain have a commissioning agreement with the NHS to diagnose or treat patients on public tariffs. These revenues represent 26% of the total revenues of private for-profit hospitals. The research question of this study is if commissioning with the NHS improves the financial performance of private-for-profit hospitals in Spain.

METHODS

With a long panel (2000-2017) of for-profit hospitals we estimate a model for the financial performance (return on assets) using commissioning as main explanatory variable and other variables as control (variables financial indicators and structural information). Specific models are estimated for subgroups of hospitals according to size and specialization. The models are estimated by panel regression with fixed effects and GMM as robustness.

RESULTS

Private for-profit hospitals that have commissioning with NHS obtain higher financial performance than no-commissioning hospitals. This effect varies depending on hospital size and type (hospital specialization), the advantage being more relevant for general hospitals and particularly for hospital with at least 50 beds.

CONCLUSIONS

Commissioning with the NHS is a promising source of financial profitability for general acute private for-profit hospitals. The evidence provided by this study may orientate the NHS in the regulation and negotiation of commissioning contracts in healthcare.

Innovative methods of evaluating business efficiency: a comparative study

This paper evaluates the efficiency level of medical spa businesses operating in Slovakia. The research aims to compile an efficiency ranking of these specific healthcare facilities to apply both methods and analyze their alternative use within the efficiency level measurement. The object of research is the Slovak spa businesses over the years 2014-2018. The study involved the Simplex Method of Linear Programming and the selected Data Envelopment Analysis model. In the study frame, the authors quantified the efficiency of medical spa businesses as the optimization task of SMPL and BCC input-oriented DEA model to identify prosperous businesses from non-prosperous ones. The study applied the Spearman rank correlation to reveal a potential degree of association of business rankings. The calculations were provided by the MS Excel, MS Excel Solver package, and the statistical program Gretl. The findings indicated that the business efficiency measured by SMPL provided similar results to the DEA model. These methods could be considered equivalent. Therefore, their alternative use was confirmed. The obtained results showed that both methods almost equally divided the businesses into two groups: 1) with efficiency score above (10 DMUs) and 2) below the overall achieved average (11 DMUs). According to the average results of both applied methods, the most efficient DMUs were DMU09 (Spa Lúcky, j.s.c.) and DMU03 (Spa Bojnice, j.s.c.), vice versa, the lowest efficiency score was achieved by DMU04 (Spa Brusno, j.s.c.). This research could be considered an important opportunity to identify new gaps in the prior literature and present the need for further development in these specific healthcare facilities, not only in Slovakia. The presented research findings are also beneficial for practice as they may lead to the formulation of recommendations for improvement of the current state of Slovak spa tourism and the spa businesses themselves.

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.

Investigating the link between medical urgency and hospital efficiency - Insights from the German hospital market

With hospital budgets remaining tight and healthcare expenditure rising due to demographic change and advances in technology, hospitals continue to face calls to contain costs and allocate their resources more efficiently. In this context, efficiency has emerged as an increasingly important way for hospitals to withstand competitive pressures in the hospital market. Doing so, however, can be challenging given unpredictable fluctuations in demand, a prime example of which are emergencies, i.e. urgent medical cases. The link between medical urgency and hospitals' efficiency, however, has been neglected in the literature to date. This study therefore aims to investigate the relationship between hospitals' urgency characteristics and their efficiency. Our analyses are based on 4094 observations from 1428 hospitals throughout Germany for the years 2015, 2016, and 2017. We calculate an average urgency score for each hospital based on all cases treated in that hospital per year and also investigate the within-hospital dispersion of medical urgency. To analyze the association of these urgency measures with hospitals' efficiency we use a two-stage double bootstrap data envelopment analysis approach with truncated regression. We find a negative relationship between the urgency score and hospital efficiency. When testing for non-linear effects, the results reveal a u-shaped association, indicating that having either a high or low overall urgency score is beneficial in terms of efficiency. Finally, our results reveal that higher within-hospital urgency dispersion is negatively related to efficiency.

Impact of Global Budget Revenue Policy on Emergency Department Efficiency in the State of Maryland

INTRODUCTION

On January 1, 2014, the State of Maryland implemented the Global Budget Revenue (GBR) program. We investigate the impact of GBR on length of stay (LOS) for inpatients in emergency departments (ED) in Maryland.

METHODS

We used the Hospital Compare data reports from the Centers for Medicare and Medicaid Services (CMS) and CMS Cost Reports Hospital Form 2552-10 from January 1, 2012-March 31, 2016, with GBR hospitals from Maryland and hospitals from West Virginia (WV), Delaware (DE), and Rhode Island (RI). We implemented difference-in-differences analysis and investigated the impact of GBR implementation on the LOS or ED1b scores of Maryland hospitals using a mixed-effects model with a state-level fixed effect, a hospital-level random effect, and state-level heterogeneity.

RESULTS

The GBR impact estimator was 9.47 (95% confidence interval [CI], 7.06 to 11.87, p-value<0.001) for Maryland GBR hospitals, which implies, on average, that GBR implementation added 9.47 minutes per year to the time that hospital inpatients spent in the ED in the first two years after GBR implementation. The effect of the total number of hospital beds was 0.21 (95% CI, 0.089 to 0.330, p-value = 0 .001), which suggests that the bigger the hospital, the longer the ED1b score. The state-level fixed effects for WV were -106.96 (95% CI, -175.06 to -38.86, p-value = 0.002), for DE it was 6.51 (95% CI, -8.80 to 21.82, p-value=0.405), and for RI it was -54.48 (95% CI, -82.85 to -26.10, p-value<0.001).

CONCLUSION

Our results indicate that GBR implementation has had a statistically significant negative impact on the efficiency measure ED1b of Maryland hospital EDs from January 2014 to April 2016. We also found that the significant state-level fixed effect implies that the same inpatient might experience different ED processing times in each of the four states that we studied.

Efficiency of acute public hospitals in the region of Murcia, Spain

Aim: To evaluate the level of efficiency of public acute hospitals situated in the region of Murcia (Spain). Materials & methods: Data from nine acute general hospitals of Murcia's Health Service (SMS by its Spanish acronym) were analyzed over the 2012-2014 period. The data were extracted from the In-patient Health Establishment Statistics of the Ministry of Health, Social Services and Equality, from the National Health Service (SNS) portal and the SMS portal. To this end, the data envelopment analysis (DEA)-window method was used, since this extension of the basic DEA model allows to compare the efficiency of a small number of units over different years and analyze changes in efficiency over time. In addition, the model was complemented by smooth bootstrapping and a superefficiency analysis to improve the quality of the data interpretation. Four inputs were used (number of beds, number of operating rooms, personnel costs and operating costs), two undesirable outputs (average stay and rate of return) and three desirable outputs (weighted discharges, emergencies and surgical interventions). Results: The average level of inefficiency was 1.58% over the study period, with a good evolution between 2012 (3.53%) and 2014 (0.20%). This improvement was also reflected in the number of efficient hospitals that rose from two in 2012 to eight in 2014. Moreover, the slack levels detected were small. Conclusion: The management of the public hospitals analyzed was favorable, both regarding average level of efficiency and the number of hospitals qualified as efficient. However, the analysis revealed several ways to increase efficiency by reducing specific inputs and nondesirable outputs (mainly operating and personnel costs as well as average length of stay) while increasing desirable outputs (mostly the number of surgical interventions). To finish, specific policy measures are suggested to improve the performance of these hospitals.

A comprehensive map of the evidence on the performance evaluation indicators of public hospitals: a scoping study and best fit framework synthesis

INTRODUCTION

Key performance indicators are essential navigation tools for hospitals. They provide managers with valid information enabling them to identify institutional strengths and weaknesses and improve managerial performance. In this study, the synthesis of evidence relating to hospital performance indicators was carried out by means of a field review and the indicators were analyzed through the Best Fit Method.

METHODS

The five-step approach of Arksey and O'Malley was used as follows: selection of the research question; search for related studies; selection and refinement of the studies; synthesis and tabulation of key information; derivation of the related summary and report. Applying the Best Fit Framework Synthesis Method, the initial themes and subthemes were created and a model of public hospitals performance evaluation finally generated.

RESULTS

Forty-nine studies were considered eligible to form part of the synthesis. The final model included the efficiency/productivity, effectiveness and financial themes. The efficiency/productivity sub-themes incorporated human resources indicators, hospital beds, costs, operating room productivity, emergency rooms, ICU, radiology, labs, technology and equipment productivity. Other sub-themes relate to general indicators such as BOR, ALS, number of outpatients and hospitalized patients. Financial themes included profit, revenue, cash flow, cost, investment, assets, debt and liquidity. Concerning effectiveness, the indicators were categorized in terms of access (equity), safety, quality and responsiveness. The accountability indicators were classified into patient-centeredness, staff orientation, and social responsibility.

CONCLUSION

Hospital performance management is a multi-dimensional issue, each dimension having its own significance. Based on the evidence, indicators are dependent on the evaluation model employed, the evaluation objective, and the views of executive managers and participants in the study. Selection of the most appropriate indicators is therefore key to a comprehensive performance evaluation system.

Healthcare efficiency assessment using DEA analysis in the Slovak Republic

A regional disparity is becoming increasingly important growth constraint. Policy makers need quantitative knowledge to design effective and targeted policies. In this paper, the regional efficiency of healthcare facilities in Slovakia is measured (2008-2015) using data envelopment analysis (DEA). The DEA is the dominant approach to assessing the efficiency of the healthcare system but also other economic areas. In this study, the window approach is introduced as an extension to the basic DEA models to evaluate healthcare technical efficiency in individual regions and quantify the basic regional disparities and discrepancies. The window DEA method was chosen since it leads to increased discrimination on results especially when applied to small samples and it enables year-by-year comparisons of the results. Two stable inputs (number of beds, number of medical staff), three variable inputs (number of all medical equipment, number of magnetic resonance (MR) devices, number of computed tomography (CT) devices) and two stable outputs (use of beds, average nursing time) were chosen as production variable in an output-oriented 4-year window DEA model for the assessment of technical efficiency in 8 regions. The database was made available from the National Health Information Center and the Slovak Statistical Office, as well as from the online databases Slovstat and DataCube. The aim of the paper is to quantify the impact of the non-standard Data Envelopment Analysis (DEA) variables as the use of medical technologies (MR, CT) on the results of the assessment of the efficiency of the healthcare facilities and their adequacy in the evaluation of the monitored processes. The results of the analysis have shown that there is an indirect dependence between the values of the variables over time and the results of the estimated efficiency in all regions. The regions that had low values of the variables over time achieved a high degree of efficiency and vice versa. Interesting knowledge was that the gradual addition of variables number of MR, number of CT and number of medical devices together, to the input side did not have a significant impact on the overall estimated efficiency of healthcare facilities.

Impact of network size and demand on cost performance for high- and low-quality healthcare service organizations

Purpose

Healthcare networks are becoming ubiquitous, yet it is unclear how hospitals with varying quality capabilities would fare by being affiliated with large healthcare networks. The purpose of this paper is to first consider the deductive configuration perspective and distinguish high and low quality hospitals by using clinical and experiential quality as two dimensions of quality capability. Next, it examines the impact of healthcare network size on operating costs of hospitals. Additionally, the paper investigates the interaction effect of hospital demand and healthcare network size on operating costs.

Design/methodology/approach

The paper uses a dataset that was created by combining five separate sources. Cluster analysis technique is used to classify hospitals into four groups – holistic quality leaders (high clinical and experiential quality capability), experiential quality focusers (low clinical quality capability and high experiential quality capability), clinical quality focusers (high clinical capability and low experiential quality capability), and quality laggards (low clinical and experiential quality capability). The authors test the research hypotheses by means of regression analyses after controlling for several contextual characteristics.

Findings

The results show that affiliation with large healthcare networks reduces operating costs for quality laggards, but increases these costs for experiential quality focusers and clinical quality focusers. The hypothesized positive relationship between healthcare network size and costs is not supported for holistic quality leaders. The authors find that clinical quality focusers and holistic quality leaders can complement higher utilization levels in their operations due to increased demand and healthcare network size to reduce their operating costs per day.

Originality/value

There has been increasing evidence suggesting that hospitals must carefully manage both clinical and experiential quality. By focusing on both clinical and experiential quality, unlike experiential quality focusers and clinical quality focusers, holistic quality leaders are not adversely affected by the size of their network. The results suggest that experiential quality focusers and clinical quality focusers should either embrace holistic quality management or restrict the size of their networks to maintain their quality level and to reduce coordination costs.

Integrated Analysis of Healthcare Efficiency: A Systematic Review

Data Envelopment Analysis (DEA) has been used as a performance measurement tool in efficiency assessment of healthcare systems. However, over the years, researchers and health practitioners presented the theoretical and methodological limitations of DEA that limits the full view of healthcare efficiency. To address these limitations, a commonly used strategy is to integrate other statistical methods and techniques with DEA to provide better efficiency evaluation. This paper reviews 57 studies with DEA applications in the healthcare industry to illustrate the integrated analysis of healthcare efficiency. With DEA as the central method, regression models in conjunction with statistical tests are commonly used. Input-oriented radial DEA models using predominantly capacity-related inputs and activity-related outputs and following either constant return to scale or variable return to scale assumptions are mostly applied to measure healthcare efficiency.

Impact of Health System Affiliation on Hospital Resource Use Intensity and Quality of Care

OBJECTIVE

To assess the impact of hospital affiliation, centralization, and managed care plan ownership on inpatient cost and quality.

DATA SOURCES

Inpatient discharges from 3,957 community hospitals in 44 states and American Hospital Association Annual Survey data from 2010 to 2012.

STUDY DESIGN

We conducted a retrospective longitudinal regression analysis using hierarchical modeling of discharges clustered within hospitals.

DATA COLLECTION

Detailed discharge data including costs, length of stay, and patient characteristics from the Healthcare Cost and Utilization Project State Inpatient Databases were merged with hospital survey data from the American Hospital Association.

PRINCIPAL FINDINGS

Hospitals affiliated with health systems had a higher cost per discharge and better quality of care compared with independent hospitals. Centralized systems in particular had the highest cost per discharge and longest stays. Independent hospitals with managed care plans had a higher cost per discharge and better quality of care compared with other independent hospitals.

CONCLUSIONS

Increasing prevalence of health systems and hospital managed care ownership may lead to higher quality but are unlikely to reduce hospital discharge costs. Encouraging participation in innovative payment and delivery reform models, such as accountable care organizations, may be more powerful options.