Evaluating the decentralisation of the Spanish healthcare system: a data envelopment analysis approach.

OBJECTIVES: The aim of the study was to answer whether the central government has been more efficient than the regional governments or vice versa. Likewise, through the analysis of the data, the aim was to shed light on whether decentralisation has had a positive impact on the efficiency of the hospital sector or not. DESIGN: In this paper, we have used data envelopment analysis to analyse the evolution of efficiency in the last 10 Autonomous Regions to receive healthcare competences at the end of 2001. PARTICIPANTS: For this study, we have taken into account the number of beds and full-time workers as inputs and the calculation of basic care units as outputs to measure the efficiency of the Spanish public sector, private sector and jointly in the years 2002, 2007, 2012 and 2017 for the last Autonomous Regions receiving healthcare competences. RESULTS: Of the Autonomous Regions that received the transfers at the end of 2001, the following stand out for their higher efficiency growth: the Balearic Islands (81.44% improvement), the Madrid Autonomous Region, which practically reached absolute efficiency levels (having increased by 63.77%), and La Rioja which, together with the Balearic Islands which started from very low values, improved notably (46.13%). CONCLUSION: In general, it can be observed that the transfer of responsibilities in the health sector has improved efficiency in the National Health Service. JEL CLASSIFICATION: C14; I18; H21.

A Bi-Objective Home Health Care Routing and Scheduling Problem under Uncertainty.

Home health care companies provide health care services to patients in their homes. Due to increasing demand, the provision of home health care services requires effective management of operational costs while satisfying both patients and caregivers. In practice, uncertain service times might lead to considerable delays that adversely affect service quality. To this end, this paper proposes a new bi-objective optimization problem to model the routing and scheduling problems under uncertainty in home health care, considering the qualification and workload of caregivers. A mixed-integer linear programming formulation is developed. Motivated by the challenge of computational time, we propose the Adaptive Large Neighborhood Search embedded in an Enhanced Multi-Directional Local Search framework (ALNS-EMDLS). A stochastic ALNS-EMDLS is introduced to handle uncertain service times for patients. Three kinds of metrics for evaluating the Pareto fronts highlight the efficiency of our proposed method. The sensitivity analysis validates the robustness of the proposed model and method. Finally, we apply the method to a real-life case and provide managerial recommendations.

Surgical productivity recovery after the COVID-19 pandemic in Japan.

Introduction: Previous studies demonstrated that the surgical productivity regressed in 2020. This study therefore explored whether the COVID-19 pandemic had any significant lasting effect of reducing the surgical productivity in Japan. This is a retrospective observational study which is an extension of the previous ones. Methods: The authors analyzed 18,805 surgical procedures performed during the study period from April 1 through September 30 in 2016-22. A non-radial and non-oriented Malmquist model under the variable returns-to-scale assumptions was employed. The decision-making unit (DMU) was defined as a surgical specialty department. Inputs were defined as (1) the number of assistants, and (2) the surgical duration. The output was defined as the surgical fee. The study period was divided into 42 one-month periods. The authors added all the inputs and outputs for each DMU during these study periods, and computed its Malmquist index, efficiency change and technical change. The outcome measures were its annual productivity, efficiency, and technical changes between the same months in each year. Results: There was no statistically significant difference in annual productivity, efficiency, and technical changes between pre-pandemic and post-pandemic periods. Discussion: No evidence was found to suggest that the COVID-19 pandemic has any significant lasting effect of reducing the surgical productivity.

Associations between corporate ownership of primary care providers and doctor wellbeing, workload, access, organizational efficiency, and service quality.

Traditionally, in many countries general practices have been privately-owned independent small businesses. However, the last three decades has seen the rise of large corporate medical groups defined as private companies which are able to have non-GP shareholders and with branches across many locations. The greater prominence of profit motives may have implications for costs, access to care and quality of care. We estimate that 45% of GPs in Australia worked in a practice that was a private company, and within this group over one third (19.9% of total) worked in a corporate medical group (a private company with 10 or more practice locations). We examine the association between being in a corporate medical group and 19 outcomes classified into five groups: GP wellbeing, workload, patient access, organizational efficiency, and service quality. GPs who worked in such groups were more likely to be older, qualified overseas, and to have a conscientious personality. There was mixed evidence on GPs wellbeing, with GPs in corporate medical groups reporting a higher turnover of GPs but similar levels of job satisfaction. GP workload was similar in terms of hours worked and after hours work but they reported a lower work-life balance. Patient access was better in terms of lower fees charged to patients but there was weak evidence that patients waited longer. GPs in corporate medical groups reported higher organisational efficiency because GPs spent less time spent on administration and management, had more nurses per GP, but despite this GPs were more likely to undertake tasks someone less qualified could do suggesting that nurses were complements not substitutes. There were no differences in service quality (teaching, patient complaints, consultation length, patients seen per hour). Corporate medical groups have become a substantial part of primary care provision in Australia. There is evidence they are more efficient, patient access is better with lower out of pocket costs and there are no differences in our measures service quality, but concerns remain about GP's wellbeing and work-life balance. Further research is needed on continuity of care and patient reported experiences and health outcomes.

Unveiling the affecting mechanism of digital transformation on total factor productivity of Chinese firms.

The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.

Bridging the gap: coordinating equity and efficiency in older people care resource allocation in China.

BACKGROUND: With the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation. METHODS: The data used in this study were derived from the "China Statistical Yearbook" and the "China Civil Affairs Statistical Yearbook" for the period of 2010-2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020. RESULTS: The equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation. CONCLUSION: With the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

Does Rounding Order Bias Discharge Efficiency? Predictors of Discharge Timing on an Academic Urology Service.

ABSTRACT: No previous works have analyzed whether the order in which surgical teams see patients on morning rounds affects discharge efficiency at teaching hospitals. We obtained perioperative urologic surgery timing data at our academic institution from 2014 to 2019. We limited the analysis to routine postoperative day 1 discharges. Univariate and multivariate analyses were performed to determine whether various hospital and patient factors were associated with discharge timing. We analyzed 1,494 patients. Average discharge order time was 11:22 a.m. and hospital discharge 1:24 p.m. Univariate regression revealed earlier discharge order time for patients seen later in rounds by 4 minutes per sequential room cluster (p = .013) and by 12 minutes per cluster when excluding short-stay patients. Multivariate analysis revealed discharge order placement did not vary significantly by rounding order. However, time of hospital discharge did (p < .001), likely due to speed of discharge in the designated short-stay units. Attending physician was the most consistent predictor in variations of discharge timing, with statistical significance across all measured outcomes. Patients seen later in rounding progression received earlier discharge orders, but this relationship does not remain in multivariate modeling or translate to earlier discharge. These findings have helped guide quality improvement efforts focused on discharge efficiency.

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.

Factors influencing the technical efficiency of diabetes care at primary care level in Mexico.

Diabetes prevalence is rising globally, especially in low- and middle-income countries like Mexico, posing challenges for healthcare systems that require efficient primary care to manage the disease. However, healthcare efficiency is influenced by factors beyond decision-makers, including socioeconomic and political conditions. This study aims to evaluate the technical efficiency of primary healthcare for diabetes patients in Mexico over a 12-year period and explore the impact of contextual variables on efficiency. A longitudinal analysis was conducted using administrative and socio-demographic data from 242 health jurisdictions between 2009 and 2020. Data envelopment analysis with bootstrapping and output orientation was used to measure the technical efficiency; health resources in infrastructure and human resources were used as inputs. As outcome, the number of patients receiving treatment for diabetes and the number of patients with controlled diabetes were considered. Machine learning algorithms were employed to analyse multiple factors affecting the provision of diabetes health services and assess heterogeneity and trends in efficiency across different health jurisdictions. The average technical efficiency in primary healthcare for diabetes patients was 0.44 (CI: 0.41-0.46) in 2009, reaching a peak of 0.71 (CI: 0.69-0.72) in 2016, and moderately declining to 0.60 (CI: 0.57-0.62) in 2020; these differences were statistically significant. The random forest analysis identified the marginalization index, primary healthcare coverage, proportion of indigenous population and demand for health services as the most influential variables in predicting efficiency levels. This research underscores the crucial need for the formulation of targeted public policies aimed at extending the scope of primary healthcare services, with a particular focus on addressing the unique challenges faced by marginalized and indigenous populations. According to our results, it is necessary that medical care management adjust to the specific demands and needs of these populations to guarantee equitable care in Mexico.

Process reengineering using DMAIC framework for reduction of waiting time in daycare infusion therapy for better patient experience.

Daycare infusion therapy is an integral aspect of oncology, but increased waiting time raises concerns for patients. Patient-reported experience measures prompted the need to evaluate reasons for prolonged appointment delays. This study seeks to analyze and address patients' concerns, to streamline the process flow and reduce waiting time for daycare infusion therapy thereby enhancing patient experience. The define, measure, analyze, improve, and control methodology was implemented, and its impact on reducing waiting times was evaluated. The objective is to ensure that >85% of patients enter the daycare infusion unit within an hour of their appointment time in 6 months. The baseline data for patient waiting times was measured for a period of 2 months, and the average waiting time was determined. Potential causes contributing to prolonged waiting times were identified through time-motion analysis, with a fishbone diagram categorizing potential causes and a Pareto chart prioritizing them. Plan, do, study, and act cycles were conducted for implementing the changes, and a new process flow mapped. Baseline data showed 32% average adherence to the defined turnaround time of 1 hour, with an average waiting time of 108 minutes. Forty causes were identified for increased waiting time, of which eight were key. Adherence to waiting time turnaround time improved from 32% to 89% and the average waiting time decreased by 59 minutes from 108 minutes, increasing patient satisfaction index by 7.5%. The balancing measures include an increase in operational efficiency and throughput of the unit and the inventory levels of oncology medicine were decreased, leading to a 50% reduction in inventory value, while medication error declined by 0.62%, improving patient safety. The project gained tangible and intangible benefits impacting staff, patients, and relatives while improving operational efficiency. This study, with its scientific and systematic approach, enhanced patient satisfaction, patient safety, and better utilization of resources.

Assessing the dynamic performance of water companies through the lens of service quality.

The measurement of performance within the water industry holds significant importance for policymakers, as it can help guide decision-making for future development and management initiatives. In this study, we apply data envelopment analysis (DEA) cross-efficiency techniques to evaluate the productivity change of the Chilean water industry during the years 2010-2018. Water leakage and unplanned interruptions are included in the analysis as quality of service variables. Moreover, we use cluster analysis and regression techniques to better understand what drives productivity change of water companies. The results indicate that the Chilean water industry is characterized by considerable high levels of inefficiency and low levels of productivity change. This is due to the existence of technical regress whereas gains in efficiency were small. Concessionary water companies were found to be more productive than full private and public water companies. Best and worst performers need to make efforts to reduce production costs and improve service quality. Other factors such as customer density and ownership type statistically affect productivity.

The Missing Link: Lean Leadership.

People often equate "Lean" with the tools that are used to create efficiencies and standardize processes. However, implementing tools represents at most 20 percent of the effort in Lean transformations. The other 80 percent is expended on changing leaders' practices and behaviors, and ultimately their mindset. Senior management has an essential role in establishing conditions that enable 80 percent of the effort to succeed. Their involvement includes establishing governance arrangements that cross divisional boundaries, supporting a thorough, long-term vision of the organization's value-producing processes, and holding everyone accountable for meeting Lean commitments. This is accomplished through regular, direct involvement. When upper management sets the example, durable Lean success and an increasingly Lean leadership mindset follow.

Non-homogeneity in the efficiency evaluation of health systems.

BACKGROUND: An international comparison of health system performance is a popular tool of health policy analysis. However, the efficiency evaluation of health systems is a practical example of an international comparison in which non-homogeneity is expected. The objective of this paper is to evaluate the efficiency of health systems by models in which a degree of non-homogeneity among countries is considered. METHODS: We study the problem of non-homogeneity of health systems in the theoretical framework of the data envelopment analysis (DEA), which is a popular method of efficiency evaluation with hundreds of applications from various fields. DEA assume the homogeneity of production units and the homogeneity of the environment in which the production units operate. Hence, we compiled a summary of 14 recommendations on how to deal with the non-homogeneity in the DEA models. The analysed sample includes 38 OECD member countries. The data are from the year 2019. RESULTS: As an example, we evaluated the health system efficiency of the Czech Republic. We used the DEA models with the neighbourhood measure of distance and the constraint limiting the comparison of countries with different levels of economic development. The health system inputs were the numbers of physicians, nurses, and hospital beds. In the production of the intermediate outputs (doctor consultations, inpatient care discharges), the Czech Republic should look at Poland, Slovakia and Slovenia. In the production of health outcomes (life expectancy), the peer countries are France, Italy and Switzerland. CONCLUSIONS: The results of the DEA analysis are only indicative because no single analytical method can determine whether a health system is better or worse than others. We need to combine different methods, and DEA is one of them. We consider DEA as an exploratory method, not a method providing definitive answers.

Efficiency trends of essential public health services and possible influencing factors since the new round health reform in China: a case study from Hainan Province.

Objective: This article aimed to evaluate the efficiency trends and influencing factors of essential public health services in Hainan Province after the healthcare reform launched in 2009 in China. Methods: The efficiency of essential public health services (EPHS) at primary health institutions was assessed using data envelopment analysis (DEA), and the efficiency change was analyzed by employing the Malmquist productivity index (MPI). We used Tobit regression to identify the influence of environmental factors on the efficiency of public health services. The bootstrap method was adopted to reduce the impact of random errors on the result. Results: The bootstrapping bias-corrected efficiency revealed that the average values of technical efficiency, pure technical efficiency, and scale efficiency were 0.7582, 0.8439, and 0.8997, respectively, which meant that the EPHS in Hainan Province were not at the most effective state. The average bias-corrected MPI was 1.0407 between 2010 and 2011 and 1.7404 between 2011 and 2012. MPIs were less than 1.0000 during other periods investigated, ranging from 0.8948 to 0.9714, indicating that the efficiency of EPHS has been decreasing since 2013. The Tobit regression showed that the regression coefficients of per capita GDP, population density, the proportion of older people aged over 65, and the proportion of ethnic minority population were 0.0286, -0.0003, -0.0316, and - 0.0041 respectively, which were statistically significant (p < 0.05). Conclusion: There was a short-term improvement in the efficiency of EPHS in Hainan after the launch of the new round of health reform. However, this trend has not been sustained after 2013. In particular, equalized financial investment in essential public health could not fulfill the needs of poor counties. This has resulted in the inability to improve scale efficiency in some counties, which in turn has affected the improvement of overall EPHS efficiency. Therefore, to promote EPHS efficiency sustainably, it is suggested that under this model of provincial control of counties, the equity of resource allocation should be effectively improved while further advancing the technology of service delivery.

Efficiency Determinants in Healthcare: A Systematic Review With an Integrated Canonical Correlation Analysis-Data Envelopment Analysis/Assurance Region Model.

GOAL: Instead of considering many variables for the accurate measurement of healthcare efficiency, working with the select few variables that really affect efficiency will provide more accurate efficiency scores. In addition, calculating the efficiency by weighting the inputs and outputs according to their effect and severity levels will give more realistic results. In this article, a three-step hybrid system with a two-stage CCA (canonical correlation analysis)-DEA/AR (data envelopment analysis/assurance region) model is proposed to obtain results of health efficiency. METHODS: Healthcare efficiency studies conducted between 2000 and 2020 were reviewed. In this examination of the input and output variables used in the DEA of 63 previous studies, the 6 inputs and 5 outputs preferred by previous researchers were determined. Afterward, the health efficiency scores of countries represented in the research were calculated with weight-restricted DEA, and CCA was used for a priori statistical analysis in determining the weights. Thus, in this analysis of the preferred outputs and inputs with the help of CCA to estimate the relationship between multiple input and output sets, the variables that had no effect were eliminated and the ones that had an effect were included in DEA/AR with their degree of effectiveness. PRINCIPAL FINDINGS: For the model proposed here, three inputs and three outputs were identified by following a five-item variable reduction procedure. The numbers of doctors and nurses were identified as the most effective inputs, and infant mortality rates were found to be the most effective outputs. Therefore, health efficiency scores obtained with the proposed CCA-DEA/AR model and the basic DEA are presented together. A review of the results found fewer health-efficient countries with the weight-restricted DEA. This is proof that weighting the variables into the DEA increases the discriminating power of the method. PRACTICAL APPLICATIONS: By applying the proposed model, healthcare administrators can analyze healthcare efficiency accurately and thus improve efficiency by transferring limited resources to the right places according to deficiencies or surpluses identified by the model's inputs. Resources can be allocated at both private and public hospitals in a way that increases healthcare efficiency outputs.