Search

BACKGROUND : The efficiency of medical services directly impacts the economic burden of healthcare, making it crucial to analyze the input-output efficiency of various types of medical institutions. However, while hospitals had been extensively analyzed for their efficiency, other types of medical institutions had received limited attention in this regard. METHODS : In this study, we employed data envelopment analysis (DEA) methods based on time series and internal benchmarks to autonomously assess the efficiency of 18 distinct categories of healthcare facilities in China over the past decade. The verification was conducted through the utilization of the critical incident technique (CIT). Additionally, we utilized the Delphi process (AHP) method to evaluate suppliers of medical consumables, implemented a multi-population genetic algorithm for managing these consumethod and analytic hierarchymables efficiently, and applied stakeholder theory to manage medical personnel efficiency.  RESULTS : Our findings indicated that medical institutions capable of providing clinical services exhibited higher levels of efficiency compared to those unable to do so. Multiple indicators suggested redundancy within these institutions. Notably, comprehensive benefit evaluation revealed that clinical laboratory had performed poorly over the past decade. We selected an inefficient medical institution for intervention in reagent management and the work efficiency of medical staff. After implementing the Delphi method and multi-population genetic algorithm for consumable replenishment, the reagent cost was reduced by 40%, 39% and 31% respectively in each of the three experimental groups, compared to the control group. By applying stakeholder theory and process reengineering methods, we were able to shorten quality control management time for medical staff in the experimental group by 41 min per day, reduce clinical service time by 25 min per day, and extend rest time by 70 min per day, while the quality indicators were all meeting the targets. CONCLUSION: By employing various mathematical models as described above, we were able to reduce costs associated with medical consumables and enhance medical personnel work efficiency without compromising quality objectives., Competing Interests: Declarations Ethics approval and consent to participate This study received ethical approval from the Research Ethics Committee (REC) of the Ping An Healthcare Diagnostics Center with the reference number ‘2021 Ethics approval (declaration) No. 67’. The study obtained voluntary and informed consent from all participants, who expressed their willingness to participate. Furthermore, each eligible participant was provided with detailed information about the study and their right to withdraw or decline participation at any point. Additionally, a unique identifier was assigned to ensure the confidentiality and privacy of respondents’ data. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

US health care spending is growing at an unsustainable rate. Since physicians control or influence the majority of spending, it is our responsibility to try and control costs. As surgeons we need to learn and consider the cost of implants and supplies and factor them into our treatment decisions to ensure we are providing value for our patients. Although the burden is on us to become more cost conscious, we should never do it at the expense of quality of patient care., Competing Interests: Disclosure Author has no relevant financial relationships or conflicts of interest with any ineligible companies., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: A routine preoperative assessment is considered both ineffective and inefficient. Despite the widespread application of lean thinking in healthcare, there is little evidence of successful experiences in preoperative admissions in order to reduce "No value added" activities. A conceptual framework reporting the drivers (clinic, tools, innovation, organization, and governance) and impacts (patient, efficiency, sustainability, time, learning and growth) was developed. Methodology: Drawing on the experience of an Italian high complexity hospital, this paper analyzes the case study by reporting evidence on how to implement lean in preoperative assessment and how to evaluate the positive results obtained. Results: Applying lean principles, the identification of value improved the appropriateness of care by creating 40 personalized pathways; the value stream resulted in a reduction of "No Value Added Time" from 37% to 28%, chest X-rays from 41% to 14% and cardiac visits from 49% to 37%; the pursuit of continuous flow through innovation contributed to increase the use of digitalization; the new pull organization helped to reduce the average time spent per year by 1.5 h; the continuous improvement was ensured through the governance of results. Conclusion: The proposed framework should be used to improve the quality of care in preoperative admissions by adopting the lean drivers for successful implementation and reporting the impacts., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objective: Analysing and evaluating how efficiently health resources are allocated to county-level Traditional Chinese Medicine (TCM) hospitals in Zhejiang Province, this study aims to provide empirical evidence for improving operational efficiency and optimising resource allocation in these hospitals., Design and Setting: The study employed a three-stage Data Envelopment Analysis (DEA) model to assess efficiency, using data from 68 county-level TCM hospitals. Four input and five output variables related to TCM services were selected for the analysis., Results: The first-stage DEA results indicated that in 2022, the technical efficiency (TE) of TCM hospitals in Zhejiang Province was 0.788, the pure technical efficiency (PTE) was 0.876 and the scale efficiency (SE) was 0.903. The classification of hospitals into four groups based on the bed size showed statistically significant differences in returns to scale (p<0.001). The Stochastic Frontier Analysis regression results were significant at the 1% level across four regressions, showing that environmental variables such as per capita GDP, population density and the number of hospitals impacted efficiency. In the third stage DEA, after adjusting the input variables, the TE, PTE and SE improved to 0.809, 0.833 and 0.917, respectively. The adjusted mean TE rankings by region were West (0.860) > East (0.844) > South (0.805) > North (0.796) > Central (0.731)., Conclusion: There is an imbalance between the inputs and outputs of county-level TCM hospitals. Each region must consider factors such as the local economy, population and medical service levels, along with the specific development characteristics of hospitals, to reasonably determine the scale of county-level TCM hospital construction. Emphasis should be placed on improving hospital management and technical capabilities, coordinating regional development, promoting the rational allocation and efficient use of TCM resources and enhancing the efficiency of resource allocation in county-level TCM hospitals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: This study aimed to assess the operational efficiency of Sub-District or Tambon Health Promoting Hospitals (THPHs) in Thailand's Eastern Economic Corridor (EEC) and to propose management guidelines for future improvements., Background: The current state of Thailand's public health demonstrates that government policy has prioritized equal access to public health services in all areas. This increases the need for primary public health services, yet resources are limited and cannot be increased to meet the growing demand. The only effective way to address this issue is to develop the efficiency of public health operations., Methods: The sample consisted of 104 THPHs in Chachoengsao, a province in Thailand's EEC. Data for five input and seven output variables were collected between September 18 and November 15, 2023. An online survey was conducted to gather the required data for fiscal year 2022. Data envelopment analysis was used to measure the efficiency of THPHs., Findings: The average efficiency index of the 104 THPHs was 0.9066, with about 60% having an efficiency index of 1.00. When classified by size, it was found that the efficiency levels of the THPHs grew with size, considering that the average efficiency index of the small, medium, and large THPHs was 0.8642, 0.9140, and 0.9417, respectively. The proportion of efficient THPHs also increased with size, at 58.14%, 60.00%, and 66.67%, respectively. Regarding efficiency improvement targets, small THPHs had the highest output targets (28.40%), followed by medium THPHs (15.31%) and large THPHs (9.91%). For the inefficient THPHs, some management guidelines were made to improve their future performances.

Introduction: Burkina Faso faces many challenges in the health domain, with no real opportunity for an increase in public health expenditures. In Burkina Faso, as in all low-income countries, health spending efficiency is crucial. The objective of this paper is to assess the efficiency of Advanced Medical Centers (AMCs)-which correspond to district hospitals-in Burkina Faso over the 2017-2020 period and identify the factors that promote-or, on the contrary, limit-the efficiency of these health structures., Method: We first assessed the efficiency level of the 45 AMCs running in the country between 2017 and 2020 using a bootstrap Data Envelopment Analysis (DEA) methodology. Inputs include the number of doctors, nurses, other medical staff, non-medical staff, and beds, while output variables correspond to the number of inpatients, surgeries, outpatients, and inpatient days. In a second step, determinants of AMC's efficiency levels were explored using a double-bootstrap procedure. The roles of AMCs' internal and environmental factors were both considered., Results: We found a mean efficiency score of 0.51 over the study period, indicating that AMCs could have almost doubled their healthcare production without needing additional resources. The size, education level, and health status of the covered population and the density of the healthcare supply in the district appeared to be the driving factors of AMCs' efficiency., Conclusion: Our results indicate that improving the efficiency of AMCs should be a high-level priority for the Burkinabe health policy. Resources could be reallocated across AMCs to increase the overall efficiency of the health system., (© 2024. The Author(s).)

Objective: Overcrowding and extended waiting times in emergency departments are a pervasive issue, leading to patient dissatisfaction. This study aims to compare the efficacy of two process mining and simulation models in identifying bottlenecks and optimizing patient flow in the emergency department of Al-Zahra Hospital in Isfahan. The ultimate goal is to reduce patient waiting times and alleviate population density, ultimately enhancing the overall patient experience., Methods: This study employed a descriptive, applied, cross-sectional, and retrospective design. The study population consisted of 39,264 individuals referred to Al-Zahra Hospital, with a sample size of at least 1,275 participants, selected using systematic random sampling at a confidence level of 99%. Data were collected through a questionnaire and the Hospital Information System (HIS). Statistical analysis was conducted using Excel software, with a focus on time-averaged data. Two methods of simulation and process mining were utilized to analyze the data. First, the model was run 1000 times using ARENA software, with simulation techniques. In the second step, the emergency process model was discovered using process mining techniques through Access software, and statistical analysis was performed on the event log. The relationships between the data were identified, and the discovered model was analyzed using the Fuzzy Miner algorithm and Disco tool. Finally, the results of the two models were compared, and proposed scenarios to reduce patient waiting times were examined using simulation techniques., Results: The analysis of the current emergency process at Al-Zahra Hospital revealed that the major bottlenecks in the process are related to waiting times, inefficient implementation of doctor's orders, delays in recording patient test results, and congestion at the discharge station. Notably, the process mining exercise corroborated the findings from the simulation, providing a comprehensive understanding of the inefficiencies in the emergency process. Next, 34 potential solutions were proposed to reduce waiting times and alleviate these bottlenecks. These solutions were simulated using Arena software, allowing for a comprehensive evaluation of their effectiveness. The results were then compared to identify the most promising strategies for improving the emergency process., Conclusion: In conclusion, the results of this research demonstrate the effectiveness of using simulation techniques and process mining in making informed, data-driven decisions that align with available resources and conditions. By leveraging these tools, unnecessary waste and additional expenses can be significantly reduced. The comparative analysis of the 34 proposed scenarios revealed that two solutions stood out as the most effective in improving the emergency process. Scenario 19, which involves dedicating two personnel to jointly referring patients to the ward, and scenario 34, which creates a dedicated discharge hall, have the potential to create a more favorable situation., (© 2024. The Author(s).)

Objective: One minute of operating room (OR) time costs $36 to 37. However, ORs are notoriously inefficient. There is growing literature on improving OR efficiency, but no formal review of this topic within otolaryngology has been performed. This study reviews and synthesizes the current literature on improving OR efficiency within otolaryngology., Data Sources: MEDLINE, EMBASE, Web of Science, CINAHL, Cochrane Library, preprints.org, and medRxiv were searched on November 4, 2022., Review Methods: Published English studies were included if they reported on metrics for improving OR efficiency within otolaryngology. There were no publication date restrictions. Articles were screened by 2 reviewers. Preferred Reporting Items for Systematic Reviews and Meta-analysis reporting for scoping reviews was followed., Results: The search yielded 9316 no-duplicate articles; 129 articles were included. Most of the studies reported on head and neck procedures (n = 52/129). The main tactics included surgical considerations: hemostatic devices, techniques, and team/simultaneous approaches; anesthetic considerations: local anesthetic and laryngeal mask airways; procedure location considerations: procedures outside of the OR and remote technologies; standardization: equipment, checklists, and personnel; scheduling considerations: use of machine learning for booking, considering patient/surgeon factors, and utilizing dedicated OR time/multidisciplinary teams for on-call cases., Conclusion: The current literature brings to attention numerous strategies for improving OR efficiency within otolaryngology. Applying these strategies and implementing novel techniques to manage surgical cases may assist in offloading overloaded health care systems and improving access to care while facilitating patient safety and outcomes. Anticipated barriers to implementation include resistance to change, funding, and the current strain on health care systems and providers., (© 2024 The Authors. Otolaryngology–Head and Neck Surgery published by Wiley Periodicals LLC on behalf of American Academy of Otolaryngology–Head and Neck Surgery Foundation.)

Advanced rooming is a workflow that enables non-clinician staff to take on additional responsibilities to improve quality and productivity. However, the impact is not well understood, particularly in Federally Qualified Health Centers (FQHCs). In this observational study at two FQHC sites, we found that in advanced rooming more questions were asked by patients and staff and more problems were identified and addressed. Advanced rooming medical assistants spent more time with patients and huddled longer with clinicians without significant differences in the clinical portion of the visit or total visit length. Advanced rooming may be a way to enhance care, ease clinician burden, and increase efficiency., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: As the Chinese government places an increasing emphasis on public fitness services, there has been a concomitant growth in public demand for greater fiscal expenditure in this area. However, in light of the constrained growth in government financial resources, it is of paramount importance to allocate these resources in a rational manner in order to effectively address the public's fitness and health needs. This study aims to evaluate the efficiency of public expenditure on national fitness services across China, thereby providing valuable insights for policymakers to optimize resource allocation and improve service efficiency., Methods: The study employs a super-efficiency Data Envelopment Analysis (DEA) model, in conjunction with the Malmquist Index and Tobit regression model, to assess the efficiency of fiscal spending on fitness services in 31 Chinese provinces from 2017 to 2020. The analysis employs both static and dynamic approaches to present an objective view of the development of public fitness service levels across different regions and to empirically identify the key factors influencing fiscal spending efficiency., Results: The findings indicate substantial regional variations in the efficiency of fiscal expenditure on public fitness services. While some provinces demonstrate high efficiency in the use of public funds, others exhibit notable inefficiencies, particularly in areas with lower levels of economic development and population density. The findings underscore the existence of redundant expenditure and the varying effectiveness of resource utilization across provinces., Discussion: The study recommends that future strategies prioritize the scientific planning of fiscal inputs into public fitness services, the precise optimization of expenditure structures, the exploration of collaborative supply mechanisms, the expansion of demand-driven feedback channels, the integration of technological innovations, and the acceleration of digitalization in public fitness services., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gao, Cao and Gu.)

Improving efficiency and productivity are key aspects to ensure that general practices in England can meet the needs of a growing population with increasingly demanding and costly healthcare needs. However, current evidence on the efficiency and productivity of general practices is weak, partly due to suboptimal approaches to measure their 'valued' output. To overcome this limitation, this paper presents a multi-dimensional framework and indicators of valued output from the healthcare decision-maker's perspective. We identified existing primary care performance frameworks through a targeted literature review. We reviewed the frameworks and selected the dimensions relating to the impact on patients' health outcomes, corresponding with the definition of 'valued' output from the healthcare decision-maker perspective. For each dimension, we reviewed the National Institute for Health and Care Excellence (NICE) evidence base and guidance on best practice to develop indicators of valued output. Clinical experts and representatives of the main primary care stakeholders reviewed and validated the framework's comprehensiveness and development process. Based on a review of three existing frameworks, we synthesised a multi-dimensional output framework comprising 13 dimensions for significant primary care-related conditions and services and 51 indicators of valued output. Each indicator of valued output measures a healthcare episode and the resulting impact on patient's health. The multi-dimensional framework and indicators provide a theoretical tool to improve the measurement of primary care output in economic efficiency and productivity studies. Future research should explore the measurability of the indicators through available datasets and the implementation of the framework through analytical approaches for efficiency measurement., (© 2024. The Author(s).)

Background: Efficient utilization of the operating room (OR) is essential. Inefficiencies are thought to cause preventable delays. Our goal was to identify OR incidents causing delays and estimate their impact on the duration of various general surgery procedures., Materials: Three trained observers prospectively collected intraoperative data using the ExplORer Surgical app, a tool that helped capture incidents causing delays. The impact of each incident on case duration was assessed using multivariable analysis., Results: 151 general surgery procedures were observed. The mean number of incidents was 2.7 per each case that averaged 109min. On average, each incident caused a 2.8 ​min delay (p ​< ​0.001), however, some incidents were associated with longer delays. The procedural step of each procedure most susceptible to incidents was also defined., Conclusion: The identification of the type of incidents and the procedural step during which they occur may allow targeted interventions to optimize OR efficiency and decrease operative time., Competing Interests: Declaration of Competing interest Our team is submitting an original research article that has not been published previously and is not under consideration for publication elsewhere. It is also approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This study aims to evaluate the technical efficiency levels of healthcare systems in underdeveloped countries and to reveal the impact of COVID-19 along with some other factors on the efficiency levels via a two-stage data envelopment analysis. The study covers panel data from 2013 to 2020. The results show that technical efficiency scores decreased during the pandemic period. It is also understood from the results that immunization and the ratio of population ages 65 and above have significant and negative effects on inefficiency scores while carbon dioxide emissions have significant and positive effects. It is thought that the results of this study can guide decision-makers regarding efficiency gains in healthcare systems., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024. Published by Elsevier Ltd.)

Objective: This study aims to assess the efficiency and productivity of the Luohu Hospital Group after the reform and to identify factors influencing the efficiency to support the future development of medical consortia., Methods: Data on health resources from Shenzhen and the Luohu Hospital Group for the years 2015 to 2021 were analyzed using the super-efficiency slack-based measure data envelopment analysis (SE-SBM-DEA) model, Malmquist productivity index (MPI), and Tobit regression to evaluate changes in efficiency and productivity and to identify determinants of efficiency post-reform., Results: After the reform, the efficiency of health resource allocation within the Luohu Hospital Group improved by 33.87%. Community health centers (CHCs) within the group had an average efficiency score of 1.046. Moreover, the Luohu Hospital Group's average total factor productivity change (TFPCH) increased by 2.5%, primarily due to gains in technical efficiency change (EFFCH), which offset declines in technical progress change (TECHCH). The efficiency scores of CHCs were notably affected by the ratio of general practitioners (GPs) to health technicians and the availability of home hospital beds., Conclusion: The reform in the Luohu healthcare system has shown preliminary success, but continuous monitoring is necessary. Future strategies should focus on strengthening technological innovation, training GPs, and implementing the home hospital bed policy. These efforts will optimize the efficiency of health resource allocation and support the integration and development of resources within the medical consortium., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gong, Zhou, Luo, Hu and Lin.)

Purpose: Efficiency standards, similar to industrial measures like overall equipment effectiveness (OEE), are being used in healthcare systems more and more. Performance indicator models applied to machines assume a constant completion time. However, for human resources, the completion time of a task may vary depending on the stress experienced. This study seeks to bridge this gap by integrating the human behavior of the physician into the performance evaluation., Design/methodology/approach: The paper presents a new algorithm called PerfoBalance that is intended to distribute waiting-patient values among doctors. By maximizing each physician's stress zones, this method helps to improve their performance as a whole. A thorough case study with medical professionals is carried out to confirm the effectiveness of the suggested methodology. The PerfoBalance algorithm is used in a variety of contexts to divide waiting-patient values among doctors and optimize stress zones., Findings: Experimental results demonstrate a significant improvement in physician efficiency when implementing the PerfoBalance algorithm. The algorithm strategically selects stress zones that contribute to higher performance rates for physicians by optimizing waiting-patient values., Originality/value: By addressing the undervaluation of human performance difficulties in current efficiency models used in the healthcare industry, this research constitutes a significant contribution to the field. With its launch, the PerfoBalance algorithm offers a fresh viewpoint on waiting-patient value allocation and stress zone management in healthcare settings, hence representing a powerful method for increasing physician productivity., (© Emerald Publishing Limited.)

Background: Primary healthcare management efficiency conditions the functioning of specialized care and has a direct impact on the outcomes of the health system and its sustainability. The objective of this research is to develop models to evaluate the efficiency, including health outcomes, of the primary healthcare centres (PHC) of the Clínico - La Malvarrosa Health District in Valencia., Methods: To evaluate efficiency, Data Envelopment Analysis (DEA) was used with output orientation and variable returns to scale, with panel data from the years 2015 to 2019. In rates per 10,000 inhabitants, the inputs are: medical and nursing staff and pharmacy cost. The outputs are: number of consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and pharmaceutical prescription efficiency. As exogenous variables: the percentage of population over 65 years old, over 80 and case-mix. Three models were developed, all of them with the same inputs and different combinations of outputs related to: healthcare activity, outcomes, and both, in order to study the influence of the different approaches on efficiency. Each model is analysed both without exogenous variables and with each of them., Results: The efficiency results vary depending on the model used, although certain PHCs are always on, or very close to, the efficient frontier, while others are always inefficient. When healthcare activity outputs are considered, efficiency scores improve and the number of efficient PHCs increases. However, in general, the PHC score decreases throughout the evaluated period. This decrease is more pronounced when only activity outputs are included., Conclusions: DEA allows the inefficiencies of PHCs to be analysed and the efficient ones are clearly distinguished from the inefficient, although different efficiency scores are obtained depending on the model used. Evaluation can be according to healthcare activity, health outcomes or both, making it necessary to identify the expected objectives of the PHCs, as the perspective of the analysis influences the results., (© 2024. The Author(s).)

Background: Priority-setting becomes more difficult for decision-makers when the demand for health services and health care resources rises. Despite the fact that the Ethiopian healthcare system places a strong focus on the efficient utilization and allocation of health care resources, studies of efficiency in healthcare facilities have been very limited. Hence, the study aimed to evaluate efficiency and its determinants in public health centers., Methods: A cross-sectional study was conducted in the East Wollega zone, Oromia Regional State, Ethiopia. Ethiopian fiscal year of 2021-2022 data was collected from August 01-30, 2022 and 34 health centers (decision-making units) were included in the analysis. Data envelope analysis was used to analyze the technical efficiency. A Tobit regression model was used to identify determinants of efficiency, declaring the statistical significance level at P < 0.05, using 95% confidence interval., Results: The overall efficiency score was estimated to be 0.47 (95% CI = 0.36-0.57). Out of 34 health centers, only 3 (8.82%) of them were technically efficient, with an efficiency score of 1 and 31 (91.2%) were scale-inefficient, with an average score of 0.54. A majority, 30 (88.2%) of inefficient health centers exhibited increasing return scales. The technical efficiency of urban health centers was (β = -0.35, 95% CI: -0.54, -0.07) and affected health centers' catchment areas by armed conflicts declined (β = -0.21, 95% CI: -0.39, -0.03) by 35% and 21%, respectively. Providing in-service training for healthcare providers increased the efficiency by 27%; 95% CI, β = 0.27(0.05-0.49)., Conclusions: Only one out of ten health centers was technically efficient, indicating that nine out of ten were scale-inefficient and utilized nearly half of the healthcare resources inefficiently, despite the fact that they could potentially reduce their inputs nearly by half while still maintaining the same level of outputs. The location of health centers and armed conflict incidents significantly declined the efficiency scores, whereas in-service training improved the efficiency. Therefore, the government and health sector should work on the efficient utilization of healthcare resources, resolving armed conflicts, organizing training opportunities, and taking into account the locations of the healthcare facilities during resource allocation., (© 2024. The Author(s).)

Our study at Chi Mei Medical Center introduced "A+ Nurse," a ChatGPT-based LLM tool, into the nursing documentation process to enhance efficiency and accuracy. The tool offers optimized recording and critical reminders, reducing documentation time from 15 to 5 minutes per patient while maintaining record quality. Nurses appreciated the tool's intuitive design and its effectiveness in improving documentation. This successful integration of AI-generated content in healthcare illustrates the potential of AI to streamline processes and improve patient care, setting a precedent for future AI-driven healthcare innovations.

The efficiency and productivity evaluation process commonly employs Data Envelopment Analysis (DEA) as a performance tool in numerous fields, such as the healthcare industry (hospitals). Therefore, this review examined various hospital-based DEA articles involving input and output variable selection approaches and the recent DEA developments. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was utilised to extract 89 English articles containing empirical data between 2014 and 2022 from various databases (Web of Science, Scopus, PubMed, ScienceDirect, Springer Link, and Google Scholar). Furthermore, the DEA model parameters were determined using information from previous studies, while the approaches were identified narratively. This review grouped the approaches into four sections: literature review, data availability, systematic method, and expert judgement. An independent single strategy or a combination with other methods was then applied to these approaches. Consequently, the focus of this review on various methodologies employed in hospitals could limit its findings. Alternative approaches or techniques could be utilised to determine the input and output variables for a DEA analysis in a distinct area or based on different perspectives. The DEA application trend was also significantly similar to that of previous studies. Meanwhile, insufficient data was observed to support the usability of any DEA model in terms of fitting all model parameters. Therefore, several recommendations and methodological principles for DEA were proposed after analysing the existing literature., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zubir et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Healthcare knowledge management systems can mitigate hospitals' operational inefficiency. As a healthcare information technology, the electronic health record (EHR) receives much attention from medical institutions due to its considerable impact on operational cost performance. This paper focuses on EHR systems to address operational inefficiency by which patients pay more for health care services, and many U.S. hospitals are filing for bankruptcy. From the theoretical perspective of the practice-based view, this paper introduces a path to implement EHR systems for improving cost performance. The empirical investigation is archival data of 200 hospitals collected from the U.S. healthcare agencies. Findings contribute to prior work by hypothesizing moderating and mediating roles in EHR systems implementation. This paper introduces absorptive capacity and monitoring mechanisms as enablers of implementing EHR systems. The results showed that hospital monitoring strengthens the relationship between absorptive capacity and electronic health record systems implementation, which results in better operational cost performance. Theoretically, this study supports the long-term potential benefits of EHR adoption, and its findings are consistent with optimizing efficiency through data standardization and interoperability. From a practical perspective, this study supports hospitals' investments in evolving healthcare information technology systems through the development of a knowledge-based system employing EHR, particularly when hospitals are merging or need a financial strategic plan to control expenses., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: With Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement., Methods: Utilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation., Results: The study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion., Conclusions: Horizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts., (© 2024. The Author(s).)

Summary: The study has used a nonparametric method to estimate the technical efficiency of health-care sector in the substate level of Assam. The study is based on secondary data for the year 2018-2019. The average constant return to scale technical efficiency score is 0.81, while the average efficiency scores in variable return to scale technical efficiency and scale efficiency (SE) are 0.88 and 0.92 respectively. Moreover, seven (26%) districts are technically efficient. The major cause of inefficiency is the poor management of health-care sector. Four (15%) districts Chirang, Dima Hasao, Baksa, and Udalguri have achieved least efficiency score, while five (19%) districts Kamrup (Rural), Sivasagar, Dibrugarh, Lakhimpur, and Goalpara have the highest potentiality to achieve efficiency level. The study is static in nature. However, it will help the health policymakers to improve management and size of operation of health sector in the state., (Copyright © 2024 Copyright: © 2024 Indian Journal of Public Health.)

Objective: This study aimed to investigate the effect of spatial adjacencies on nurses' walking patterns and the subsequent impact on staff satisfaction with perceived accessibility and adjacency-related issues., Background: Recognizing the crucial importance of spatial adjacencies in healthcare facilities is essential, as they significantly affect staff morale, fatigue management, operational efficiency, error reduction, and overall patient care excellence, highlighting the need for objective assessments to evaluate the impact of facility layout and space configuration on workflow patterns and staff satisfaction in patient care units., Methods: Integrating on-site observations with survey data, we explored how spatial adjacencies affect staff walking behavior and satisfaction in two med-surgical unit floors., Results: The findings highlighted a significant frequency of movements between nurse stations, patient rooms, and medication areas. Regression analysis identified several contributing factors to staff satisfaction, including the proximity of supplies, team visibility, ease of access across departments, and the location of equipment rooms. Specifically, satisfaction with the proximity of supplies was positively associated with increased provider satisfaction with workflow, quality of care, and workplace. Additionally, valuable feedback from staff revealed concerns regarding break room placement, medication area functionality, and disparities in the availability of supplies., Conclusion: This study highlighted the critical need for carefully planned spatial adjacency strategies to enhance workflow efficiency and raise clinical staff satisfaction within healthcare facilities. The actionable insights gleaned from this research offer valuable direction to architects, healthcare administrators, and design professionals, enabling the creation of environments that positively resonate with healthcare providers and improve healthcare operations., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Non-OR Anesthesia (NORA) is rapidly becoming standard in many high-volume institutions and efficiency in these spaces has yet to be optimized. On-time first start percentage has been suggested to correlate with more efficient flow, and this correlation is established within the surgical space., Purpose: To investigate the effects of timetable targets on first case on-time first start percentage within a NORA setting., Materials and Methods: A retrospective study of anesthesia-supported first start cases from October 2022 to April 2023 was performed to analyze the effect of timetable targets on on-time first-case starts for planned cases. Statistical analysis was calculated using Student's t-tests with statistical significance defined as p < 0.05. Additionally, analysis of variance was used to compare three or more groups, and Tukey Kramer was used to evaluate groups pairwise., Results: One hundred twenty-four first start cases were included in the evaluation. After intervention with timetable targets, average patient arrival to the room time improved from 7:49 AM to 7:40 AM (p < 0.05) and procedure start time improved from 8:31 AM to 8:20 AM (p < 0.01). The percentage of procedure start times occurring prior to the goal time increased from 35 % to 58 % after the implementation (p < 0.05). With exception of Tuesdays (Anesthesia Late Start Day), on-time starts improved from 17 % to 48 % (p < 0.01) and sustained this improvement throughout the post-implementation period., Conclusion: Implementation of novel timetable targets yielded statistically significant improvement in first case start times. This improvement in efficiency and throughput results in increased room utilization, improved case throughput, and decreased block overrun times, all of which contribute toward increased revenues, decreased costs, and thus improved return on investment., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: Improving transition to the operating room (OR) can enhance healthcare efficiency. Our aim was to determine whether adopting a communication board (CB) for first case surgical patients reduced delays to OR., Methods: A retrospective observational study was conducted from April to October 2021. We calculated differences in surgical daycare (SDC) departure time before and after implementation of the CB, differences in departure whether the CB was used or not, delay in variability between surgical specialties, and overall adoption of the CB., Results: After CB adoption, 13% of first cases left SDC by predefined target times. The mean delay in transfer was 18:51 minutes. When the CB was used, cases were on average 10:43 late, compared with 26:00 when it was not used. Otolaryngology had the shortest delays while plastic surgery had the longest. Reasons for delays included staffing delays, holds, and pending laboratory results., Conclusions: Introducing a CB significantly reduced delays in transferring first case surgical patients from SDC to the OR., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 National Association for Healthcare Quality.)

Introduction: Enhancing the efficiency of primary healthcare services is essential for a populous and developing nation like China. This study offers a systematic analysis of the efficiency and spatial distribution of primary healthcare services in China. It elucidates the fundamental landscape and regional variances in efficiency, thereby furnishing a scientific foundation for enhancing service efficiency and fostering coordinated regional development., Methods: Employs a three-stage DEA-Malmquist model to assess the efficiency of primary healthcare services across 31 provincial units in mainland China from 2012 to 2020. Additionally, it examines the spatial correlation of efficiency distribution using the Moran Index., Results: The efficiency of primary healthcare services in China is generally suboptimal with a noticeable declining trend, highlighting significant potential for improvement in both pure technical efficiency and scale efficiency. There is a pronounced efficiency gap among provinces, yet a positive spatial correlation is evident. Regionally, efficiency ranks in the order of East > Central > West. Factors such as GDP per capita and population density positively influence efficiency enhancements, while urbanization levels and government health expenditures appear to have a detrimental impact., Discussion: The application of the three-stage DEA-Malmquist model and the Moran Index not only expands the methodological framework for researching primary healthcare service efficiency but also provides scientifically valuable insights for enhancing the efficiency of primary healthcare services in China and other developing nations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Huang, Li, Shi, Su, Hao, Zhao and Chai.)

Purpose: This study investigates how a hospital can increase the flow of patients through its emergency department by using benchmarking and process improvement techniques borrowed from the manufacturing sector., Design/methodology/approach: An in-depth case study of an Australasian public hospital utilises rigorous, multi-method data collection procedures with systems thinking to benchmark an emergency department (ED) value stream and identify the performance inhibitors., Findings: High levels of value stream uncertainty result from inefficient processes and weak controls. Reduced patient flow arises from senior management's commitment to simplistic government targets, clinical staff that lack basic operations management skills, and fragmented information systems. High junior/senior staff ratios aggravate the lack of inter-functional integration and poor use of time and material resources, increasing the risk of a critical patient incident., Research Limitations/implications: This research is limited to a single case; hence, further research should assess value stream maturity and associated performance enablers and inhibitors in other emergency departments experiencing patient flow delays., Practical Implications: This study illustrates how hospital managers can use systems thinking and a context-free performance benchmarking measure to identify needed interventions and transferable best practices for achieving seamless patient flow., Originality/value: This study is the first to operationalise the theoretical concept of the seamless healthcare system to acute care as defined by Parnaby and Towill (2008). It is also the first to use the uncertainty circle model in an Australasian public healthcare setting to objectively benchmark an emergency department's value stream maturity., (© Emerald Publishing Limited.)

Background: Medical service efficiency is an important indicator for measuring the equity of medical services. Therefore, this study primarily focuses on investigating the spatiotemporal domain to explore both spatial and temporal characteristics, as well as influencing factors that affect medical service efficiency across diverse provinces in China., Methods: The super Epsilon-based Measure (EBM) unexpected model has previously been utilized to quantify energy eco-efficiency, carbon emission efficiency, and green development efficiency. However, limited studies have applied this method to assess the efficiency of healthcare services. Therefore, this study investigates the application of the super-EBM-unexpected model in evaluating medical service efficiency, and further integrates spatial econometric models to explore the influencing factors of medical service efficiency and aims to identify potential avenues for improvement., Results: The average efficiency of medical services in the 31 provinces of China ranges from 0.6 to 0.7, indicating predominantly low efficiency values. However, economically developed coastal areas exhibit relatively high efficiency levels above 1. Conversely, regions with relatively lower levels of economic development demonstrate lower efficiency rates at approximately 0.3. Evidently, substantial regional disparities exist. For the influencing factors, the enhancement of residents' living standards can effectively foster the medical service efficiency, while residential living standards of nearby areas can also exert an impact in this region. The influence of educational attainment on medical service efficiency exhibits a significant inhibitory effect., Conclusions: The majority of China's 31 provinces exhibit suboptimal medical service efficiency, with notable regional disparities. Future policy initiatives should be tailored to address the unique challenges faced by regions with lower levels of economic development, prioritizing enhancements in both the efficacy and quality of their healthcare systems., (© 2024. The Author(s).)

Harnessing the power of data is a necessary competency in fueling innovation, improving financial and clinical outcomes, and achieving operational excellence. It can be analyzed, visualized, dashboarded, and embedded into workflows seamlessly with very little technical expertise. Moreover, data can galvanize organizational culture with its neutrality, transparency, and portability. Using data to highlight qualitative evaluations, patient experiences, and employee performance can help validate perceptions and identify broader organizational opportunities. Yet useful data is frequently nonexistent, invalid, or insufficient. Moving from promise to realization requires reframing data management, as described here., Competing Interests: The author declares no conflicts of interest., (Copyright © 2024 Foundation of the American College of Healthcare Executives.)

This paper addresses the management of patients' transportation requests within a hospital, a very challenging problem where requests must be scheduled among the available porters so that patients arrive at their destination timely and the resources invested in patient transport are kept as low as possible. Transportation requests arrive during the day in an unpredictable manner, so they need to be scheduled in real-time. To ensure that the requests are scheduled in the best possible manner, one should also reconsider the decisions made on pending requests that have not yet been completed, a process that will be referred to as rescheduling. This paper proposes several policies to trigger and execute the rescheduling of pending requests and three approaches (a mathematical formulation, a constructive heuristic, and a local search heuristic) to solve each rescheduling problem. A simulation tool is proposed to assess the performance of the rescheduling strategies and the proposed scheduling methods to tackle instances inspired by a real mid-size hospital. Compared to a heuristic that mimics the way requests are currently handled in our partner hospital, the best combination of scheduling method and rescheduling strategy produces an average 5.7 minutes reduction in response time and a 13% reduction in the percentage of late requests. Furthermore, since the total distance walked by porters is substantially reduced, our experiments demonstrate that it is possible to reduce the number of porters - and therefore the operating costs - without reducing the current level of service., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Since the early 2000s, artificial intelligence (AI) has raised concerns regarding its use in healthcare to manage vast amounts of patient data, ensure proper handling, and maintain robust security measures. Nevertheless, contemporary healthcare organizations are exploring ways AI can safely enhance operational efficiency and support their patient populations. Successful, evidence-based utilization relies on a well-defined ambulatory strategy, and operational efficiency must be foundational to that strategy. Patient no-shows and appointment compliance, especially in the context of social determinants of health such as access, present inherent obstacles to patient and provider satisfaction, continuity of care, practice productivity, and the financial sustainability of an organization. To address these obstacles, Berkeley Research Group has been working with Phoebe Physician Group. Their shared objective is twofold: enhance patient encounter volume and the associated revenue. This article provides insights into the steps taken to integrate AI and machine learning to mitigate the problem of no-shows by automatically double-booking appointments for patients with a high probability of not showing up. A glimpse into the outcomes achieved and lessons learned throughout the process also is presented., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Foundation of the American College of Healthcare Executives.)

Objectives: To improve access, the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 mandated a 2-year study of medical scribes in Veterans Health Administration specialty clinics and emergency departments. Medical scribes are employed in clinical settings with the goals of increasing provider productivity and satisfaction by minimizing physicians' documentation burden. Our objective is to quantify the economic outcomes of the MISSION Act scribes trial., Methods: A cluster-randomized trial was designed with 12 Department of Veterans Affairs (VA) medical centers randomized into the intervention. We estimated the total cost of the trial, cost per scribe-year, and projected cost of hiring additional physicians to achieve the observed scribe productivity benefits in relative value units and visits per full-time-equivalent over the 2-year intervention period (June 30, 2020 to July 1, 2022)., Results: The estimated cost of the trial was $4.6 million, below the Congressional Budget Office estimate of $5 million. A full-time scribe-year cost approximately $74 600 through contracting and $62 900 through VA hiring. Randomization into the trial led to an approximate 30% increase in productivity in cardiology and 20% in orthopedics. The projected incremental cost of using additional physicians instead of scribes to achieve the same productivity benefits was nearly $1.7 million more, or 75% higher, than the observed cost of scribes in cardiology and orthopedics., Conclusions: As the largest randomized trial of scribes to date, the MISSION Act scribes trial provides important evidence on the costs and benefits of scribes. Improving productivity enhances access and scribes may give VA a new tool to improve productivity in specialty care at a lower cost than hiring additional providers., Competing Interests: Author Disclosures Author disclosure forms can be accessed below in the Supplemental Material section., (Copyright © 2024. Published by Elsevier Inc.)

Efficiency analysis is crucial in healthcare to optimise resource allocation and enhance patient outcomes. However, the prompt adaptation of inputs can be hindered by adjustment costs, which impact Long-Run Technical Efficiency (LRTE). To bridge this gap in healthcare literature, this research employs a Bayesian Dynamic Stochastic Frontier Model to estimate parameters and explore healthcare efficiency dynamics over time. The study reveals the LRTE for New Zealand District Health Boards (DHBs) as 0.76, indicating around 32% more input utilisation due to adjustment costs. Most DHBs exhibit consistent short-run operational efficiency, with the national Short-Run Technical Efficiency (SRTE) very close to the LRTE. Among the tertiary providers, Auckland and Capital & Coast DHBs operate below the LRTE level, setting them apart from other tertiary providers. Similarly, Tairawhiti and West Coast DHBs also fall below the LRTE level, as indicated by their SRTE scores, potentially influenced by their unique healthcare settings and resource challenges. This research brings a new perspective to policy discussions by incorporating the temporal dynamics of decision-making and considering adjustment costs. It underscores the need to balance short-term and long-term technical efficiency, underlining their collective significance in fostering a sustainable and efficient healthcare system in New Zealand., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Introduction: The Ethiopian government has introduced several healthcare financing reforms intending to improve efficiency. Piloting implementation of performance-based financing is one of these actions. The purpose of this research is to assess the efficiency of healthcare facilities that have implemented performance-based financing compared to those that have not., Methods: Efficiency was measured using a nonparametric data envelopment analysis and the Malmquist Productivity Index technique. Total factor productivity change, technical change, and technological change are compared across eight sampled healthcare facilities that are implementing performance-based financing and eight that are not in Ethiopia., Results: Health facilities implementing performance-based financing have a mean technical efficiency score of 64%, allowing for a potential 36% reduction in inputs without affecting outputs. Their scale efficiency is 88%, indicating a potential 12% increase in total outputs without expanding facilities. In contrast, facilities not implementing performance-based financing have a mean technical efficiency score of 62%, with a potential for 38% input reduction without affecting outputs. Their scale efficiency is 87%, suggesting a potential 13% increase in total outputs without scaling up facilities. Among the 16 healthcare facilities observed, seven experienced a decline in the mean total productivity, while one remained stagnant. The remaining eight facilities witnessed an increase in productivity. The healthcare facilities implementing performance-based financing showed a 1.3% decrease in mean total productivity during the observed period. Among them, five showed an increase and three showed a decrease in the total factor of productivity. The mean total factor of productivity of all healthcare facilities not implementing performance-based financing remained stagnant over the three-year period (2019-2021), with four showing an increase and four showing a decrease in total productivity., Conclusions: The study concludes that implementing performance-based financing did not improve productivity levels among healthcare facilities over three years. In fact, productivity decreased among the facilities implementing performance-based financing, while those not implementing it remained stagnant. This shows health facilities that implement performance-based financing tend to utilize more resources for similar outputs, contradicting the anticipated efficiency improvement., (© 2024. The Author(s).)

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., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Goal: A lack of improvement in productivity in recent years may be the result of suboptimal measurement of productivity. Hospitals and clinics benefit from external benchmarks that allow assessment of clinical productivity. Work relative value units have long served as a common currency for this purpose. Productivity is determined by comparing work relative value units to full-time equivalents (FTEs), but FTEs do not have a universal or standardized definition, which could cause problems. We propose a new clinical labor input measure-"clinic time"-as a substitute for using the reported measure of FTEs., Methods: In this observational validation study, we used data from a cluster randomized trial to compare FTE with clinic time. We compared these two productivity measures graphically. For validation, we estimated two separate ordinary least squares (OLS) regression models. To validate and simultaneously adjust for endogeneity, we used instrumental variables (IV) regression with the proportion of days in a pay period that were federal holidays as an instrument. We used productivity data collected between 2018 and 2020 from Veterans Health Administration (VA) cardiology and orthopedics providers as part of a 2-year cluster randomized trial of medical scribes mandated by the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018., Principal Findings: Our cohort included 654 unique providers. For both productivity variables, the values for patients per clinic day were consistently higher than those for patients per day per FTE. To validate these measures, we estimated separate OLS and IV regression models, predicting wait times from the two productivity measures. The slopes from the two productivity measures were positive and small in magnitude with OLS, but negative and large in magnitude with IV regression. The magnitude of the slope for patients per clinic day was much larger than the slope for patients per day per FTE. Current metrics that rely on FTE data may suffer from self-report bias and low reporting frequency. Using clinic time as an alternative is an effective way to mitigate these biases., Practical Applications: Measuring productivity accurately is essential because provider productivity plays an important role in facilitating clinic operations outcomes. Most importantly, tracking a more valid productivity metric is a concrete, cost-effective management tactic to improve the provision of care in the long term., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Foundation of the American College of Healthcare Executives.)

Abstract: A strong link exists between adequate supply chain management and nurse efficiency and satisfaction. Implementing Lean methodology, specifically 5S process improvement, staff created a unit-based supply room that was clean, safe, and well organized which led to reduced waste, greater efficiency, and cost savings., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: Operating room (OR) efficiency has an impact on surgeon productivity and patient experience. Accuracy of case duration estimation is important to optimize OR efficiency. The purpose of this study was to identify factors associated with inaccurate case time estimates in outpatient hand surgery. A better understanding of these findings may help to improve OR efficiency and scheduling., Methods: All outpatient hand surgical cases from 2018 to 2019 were reviewed. Poorly-estimated cases (i.e., poor scheduling accuracy) were defined as those cases where the actual operative time differed from the predicted time by >50% (either quicker by >50% or slower by >50% than the predicted time). The percentages of poorly-estimated cases were analyzed, categorized, and compared by surgeon, procedure type, and scheduled case length., Results: A total of 6,620 cases were identified. Of 1,107 (16.7%) cases with poorly estimated case durations, 75.2% were underestimated. There was no difference in the likelihood of poor estimation related to start time. Well-estimated cases tended to have longer scheduled case duration, but shorter realized case duration and surgical time. Our systems analysis identified specific surgeons and procedures as predictable outliers. Cases scheduled for 15-30 minutes frequently were inaccurate, whereas cases scheduled for 30-45 and 106-120 minutes had accurate estimates., Conclusions: The accuracy of case time estimations in a standard outpatient hand surgery practice is highly variable. Nearly one-fifth of outpatient hand surgery case durations are poorly estimated, and inaccurate case time estimation can be predicted based on surgeon, procedure type, and case time., Clinical Relevance: Maximizing OR efficiency should be a priority for surgeons and hospital systems. With multiple surgeries done per day, the efficiency of the OR has an impact on surgeon productivity and patient experience., (Copyright © 2024 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.)

Background: In hospital management, pinpointing steps that most enhance operating room (OR) throughput is challenging. While prior literature has utilized discrete event simulation (DES) to study specific strategies such as scheduling and resource allocation, our study examines an earlier planning phase, assessing all workflow stages to determine the most impactful steps for subsequent strategy development., Methods: DES models real-world systems by simulating sequential events. We constructed a DES model for thoracic, gastrointestinal, and orthopedic surgeries summarized from a tertiary Chinese hospital. The model covers preoperative preparations, OR occupation, and OR preparation. Parameters were sourced from patient data and staff experience. Model outcome is OR throughput. Post-validation, scenario analyses were conducted for each department, including: (1) improving preoperative patient preparation time; (2) increasing PACU beds; (3) improving OR preparation time; (4) use of new equipment to reduce the operative time of a selected surgery type; three levels of improvement (slight, moderate, large) were investigated., Results: The first three improvement scenarios resulted in a 1%-5% increase in OR throughput across the three departments. Large reductions in operative time of the selected surgery types led to approximately 12%, 33%, and 38% increases in gastrointestinal, thoracic, and orthopedic surgery throughput, respectively. Moderate reductions resulted in 6%-17% increases in throughput and slight reductions of 1%-7%., Conclusions: The model could reliably reflect OR workflows of the three departments. Among the options investigated, model simulations suggest that improving OR preparation time and operative time are the most effective., (© 2024 International Society of Surgery/Société Internationale de Chirurgie (ISS/SIC).)

Background: Contextualizing in China's recent health reform, we empirically explore the heterogeneous effects of two distinct government roles, accommodating private hospitals vs investing in public hospitals, on health system efficiency., Methods: We use panel data covering 31 provinces during 2010-2019 to assess health system efficiency. We incorporate health service volumes and population health outcomes to ascertain health system outputs, employing the non-radial directional distance function to estimate efficiency. We employ Bayesian Tobit quantile regression to explore the heterogeneous effects of the share of private hospitals and government subsidy to public providers on efficiency., Results: China's health system inefficiency scores range from 0 to 0.45. The association between the share of private hospitals and inefficiency score are only significant in higher-inefficiency quantiles (coefficients -0.0258, -0.0315 and -0.0327 for quantiles 0.7, 0.8 and 0.9), meaning a heterogeneously positive impact for low-efficiency provinces. The association between government subsidy and inefficiency score are positive for all quantiles (from 0.0339 to 0.0567), meaning persistent negative impacts on efficiency., Conclusions: The heterogeneous impacts of the share of private hospitals suggest that the government should accommodate more private hospitals in provinces with low efficiency. The persistent negative impacts of government subsidy suggest that the government investment seems not be subjected to economic objectives., (© The Author(s) 2023. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

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., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations' (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions., Design/methodology/approach: A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis., Findings: In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research's stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness., Originality/value: To the authors' knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges., (© Emerald Publishing Limited.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Fu, Madni. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study examines the causal impact of very important person (VIP) medical services on hospital total factor productivity in Deyang, a prefectural-level city in western China, spanning the years 2015-2020. This aims to offer empirical evidence and policy recommendations for the implementation of VIP practices in the medical field. A secondary unbalanced panel dataset of 416 observations was collected from the annual reports of the Health Commission and 92 eligible medical institutions were included. This study utilized a two-stage strategy. First, the Global Malmquist index was used to calculate the total factor productivity and its decomposition terms for hospitals from 2015 to 2020. In the second stage, two-way fixed effects models and Tobit models were used to identify the relationship between VIP medical services and hospital efficiency; instrumental variables were used to solve potential endogeneity problems in the model. The results showed that VIP medical services had a significantly negative impact on medical institutions' efficiency. The technological advances and pure technical efficiency related to VIP medical care may help explain these negative impacts, which were heterogeneous across groups divided by the nature of the hospital and the outside environment. It is imperative to prioritize the standardized provision of VIP medical services for medical institutions, optimize management and service process, enhance the training of clinical and scientific research capabilities of medical personnel, and scientifically allocate resources for both VIP and general medical services. This will help mitigate health inequality while improving the overall quality of medical services., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Cheng, Chen, Yuan and Wang.)