Emergency Department Length of Stay: A Community Hospital Initiative.

OBJECTIVE: This quality improvement initiative was conducted to determine if a provider in triage and split flow model could decrease the length of stay (LOS) of discharged patients seen in a community hospital emergency department (ED). BACKGROUND: Extended LOSs within the ED lead to delays in the care of patients, increase the number of patients who leave without being seen by a provider, decrease patient satisfaction, and cause a loss of revenue for health care organizations. Using a provider in triage and a split flow model, where patients can be seen and dispositioned without delays, can improve ED throughput and decrease the overall LOS. METHODS: Through a structured, interdisciplinary approach using the Plan-Do-Study-Act Shewhart Cycle of Process Improvement, a provider was placed in triage, and an interior waiting room was used to evaluate emergency severity index level 3 and 4 patients to expedite diagnostic testing and perform procedures. This model allowed lower acuity patients to be cared for separately from higher acuity patients, who were being treated in the main ED. In addition, the median arrival to provider, arrival to bed, and LOS from arrival to departure of discharged patients were compared to the current departmental processes. RESULTS: There was a significant improvement in the LOS of discharged patients and the time of arrival to triage, arrival to bed, and arrival to provider using a provider in triage and a split flow model compared to the current intake. CONCLUSION: Implementation of a provider in triage and a split flow model can demonstrate a decrease in the LOS of discharged patients along with other ED metrics and improve efficiencies in patient care within a community hospital.

The allocation and utilization efficiency of hospital beds in Sichuan Province, China.

OBJECTIVE: To analyze the allocation and utilization efficiency of hospital beds in Sichuan Province, China, and to provide a scientific basis for improving the rational allocation and efficient utilization. METHODS: The supply and demand balance method, health resource agglomeration degree (HRAD), bed efficiency index and bed utilization model were used to evaluate the allocation and utilization efficiency of hospital beds in Sichuan Province from 2017 to 2021. RESULTS: The number of hospital beds per 1000 population in Sichuan Province increased from 4.97 in 2017 to 5.94 in 2021. The overall supply and demand ratio of hospital beds in Sichuan Province is between 0.85 and 1.01, and the supply and demand situation is a basically balanced situation. The HRAD of hospital beds in Ya'an, Aba, Ganzi and Liangshan is <1, indicating that the equity of hospital beds by geography in these regions is low. The difference between HRAD and population agglomeration degree (PAD) in 9 regions, including Deyang, Aba, Ganzi and Liangshan, is <0, indicating that there are insufficient hospital beds in these areas relative to the agglomerated population. The bed efficiency index of hospital beds in 17 regions, including Chengdu, Zigong, Aba and Ganzi, are all <1, which means that hospital beds are operating with low efficiency. The bed utilization model of Panzhihua is efficiency type, that of Zigong, Deyang and Ziyang is pressure bed type, and that of Nanchong and Ya'an is idle type. CONCLUSION: The hospital bed allocation in Sichuan Province is relatively good, and the supply and demand situation is in a basically balanced situation. The hospital bed allocation in Aba, Ganzi and Liangshan is insufficient by geography and population. The overall operational efficiency of hospital beds is low, and there are more idle and pressure bed utilization models.

Approach in inputs & outputs selection of Data Envelopment Analysis (DEA) efficiency measurement in hospitals: A systematic review.

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.

Public healthcare efficiency in India: Estimates and determinants using two stage DEA approach.

BACKGROUND: Nearly 400 million Indians (30 % of the total population) lack any financial protection for health which leads to very high out of pocket expenditure. In India more than 90 million people spend 10-25 % of household expenses on healthcare. This is a serious threat to Sustainable Development Goal 3, which aims at providing universal health coverage along with protection from catastrophic spending on health. AIM: The aim of this paper is to estimate the efficiency and determinants of public health in India at subnational level. METHODS: To estimate the efficiency of public healthcare, input oriented bias corrected DEA model has been used. In this model life expectancy at birth and infant survival rate have been treated as outputs. Public health spending and per capita income are treated as inputs. In the second stage Tobit regression is used to analyse the determinants of efficiency. RESULTS: The mean bias corrected efficiency score across Indian states is 0.60, implying that on average there is a 40 % inefficiency in public healthcare in India. Maharashtra and Mizoram are the most and least efficient states with efficiency score of 0.921 and 0.218, respectively. Fourteen states have efficiency scores less than 0.60, two states have efficiency score of 0.60 and 15 states have the efficiency score greater than 0.60. Socio economic factors outweigh the medical factors in determining the public healthcare efficiency in India. CONCLUSION: There are 40 % inefficiencies in public health in India implying significant wastages in public health. By improving public health efficiency, there would be savings of 48 % in terms of government expenditure on health per capita. It will also improve infant survival rate by 27.19 % and life expectancy by 20.65 %.

Enhancing Healthcare Efficiency: Integrating ChatGPT in Nursing Documentation.

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.

Intelligent Clinic Nurse Scheduling Considering Nurses Paired with Doctors and Preference of Nurses.

The nurse scheduling problem (NSP) has been a crucial and challenging research issue for hospitals, especially considering the serious deterioration in nursing shortages in recent years owing to long working hours, considerable work pressure, and irregular lifestyle, which are important in the service industry. This study investigates the NSP that aims to maximize nurse satisfaction with the generated schedule subject to government laws, internal regulations of hospitals, doctor-nurse pairing rules, shift and day off preferences of nurses, etc. The computational experiment results show that our proposed hybrid metaheuristic outperforms other metaheuristics and manual scheduling in terms of both computation time and solution quality. The presented solution procedure is implemented in a real-world clinic, which is used as a case study. The developed scheduling technique reduced the time spent on scheduling by 93% and increased the satisfaction of the schedule by 21%, which further enhanced the operating efficiency and service quality.

Efficiency evaluation, regional technological heterogeneity and determinant of total factor productivity change in China's healthcare system.

Enhancing efficiency and productivity in countries' healthcare systems is a global challenge. The Chinese government invested huge resources to improve the efficiency and productivity of the healthcare system across the country. To assess the success of the mission above, this research utilized DEA-SBM Meta frontier analysis alongside the Malmquist Productivity Index. These methodologies were employed to gauge Efficiency, production technology heterogeneity, and productivity of healthcare systems change across 31 mainland Chinese provinces and four distinct geographical regions throughout the study period spanning from 1997 to 2022. Results revealed that the mean efficiency score of China's healthcare system is 0.7672. It indicates a growth potential of 23.28 percent in the operational efficiency of healthcare systems. The eastern region's efficiency level (0.86917) is higher among all four regions. Zhejiang, Shandong, and Guangdong are the top three healthcare-efficiency performers. The technology gap ratio indicates that eastern regions witnessed a high TGR (0.9909), showing the country's attainment of superior healthcare technologies. Beijing, Guangdong, Shanghai, Tianjin, and Zhejiang witnessed higher TGR values among all 31 mainland Chinese provinces. The total factor productivity index of the healthcare system witnessed a slight growth of 0.33%, with an average MI score of 1.0033. Efficiency change (EC) was found to be the main determinant of TFPC as technology change TC is less than EC. Moreover, the MI score of the Western region (1.033) is higher than the corresponding Eastern, northeastern, and central regions. Guizhou, Anhui, and Yunnan were found to be the top three performers in TFPC growth. Finally, the Kruskal-Wallis test confirmed the statistically significant difference among 4 Chinese regions for the healthcare system's efficiency, TFPC, and TGR.

Modelling efficiency in primary healthcare using the DEA methodology: an empirical analysis in a healthcare district.

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.

Technical efficiency and its determinants in health service delivery of public health centers in East Wollega Zone, Oromia Regional State, Ethiopia: Two-stage data envelope analysis.

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 (ß = -0.35, 95% CI: -0.54, -0.07) and affected health centers' catchment areas by armed conflicts declined (ß = -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, ß = 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.

Evaluating China's primary healthcare services' efficiency and spatial correlation: a three-stage DEA-Malmquist model.

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.

Outcome evaluation of technical strategies on reduction of patient waiting time in the outpatient department at Kilimanjaro Christian Medical Centre-Northern Tanzania.

BACKGROUND: The Tanzania healthcare system is beset by prolonged waiting time in its hospitals particularly in the outpatient departments (OPD). Previous studies conducted at Kilimanjaro Christian Medical Centre (KCMC) revealed that patients typically waited an average of six hours before receiving the services at the OPD making KCMC have the longest waiting time of all the Zonal and National Referral Hospitals. KCMC implemented various interventions from 2016 to 2021 to reduce the waiting time. This study evaluates the outcome of the interventions on waiting time at the OPD. METHODS: This is an analytical cross-sectional mixed method using an explanatory sequential design. The study enrolled 412 patients who completed a structured questionnaire and in-depth interviews (IDI) were conducted among 24 participants (i.e., 12 healthcare providers and 12 patients) from 3rd to 14th July, 2023. Also, a documentary review was conducted to review benchmarks with regards to waiting time. Quantitative data analysis included descriptive statistics, bivariable and multivariable. All statistical tests were conducted at 5% significance level. Thematic analysis was used to analyse qualitative data. RESULTS: The findings suggest that post-intervention of technical strategies, the overall median OPD waiting time significantly decreased to 3 h 30 min IQR (2.51-4.08), marking a 45% reduction from the previous six-hour wait. Substantial improvements were observed in the waiting time for registration (9 min), payment (10 min), triage (14 min for insured patients), and pharmacy (4 min). Among the implemented strategies, electronic medical records emerged as a significant predictor to reduced waiting time (AOR = 2.08, 95% CI, 1.10-3.94, p-value = 0.025). IDI findings suggested a positive shift in patients' perceptions of OPD waiting time. Problems identified that still need addressing include, ineffective implementation of block appointment and extension of clinic days was linked to issues of ownership, organizational culture, insufficient training, and ineffective follow-up. The shared use of central modern diagnostic equipment between inpatient and outpatient services at the radiology department resulted in delays. CONCLUSION: The established technical strategies have been effective in reducing waiting time, although further action is needed to attain the global standard of 30 min to 2 h OPD waiting time.

Business and Corporate Models for Interventional Radiology in the Office Based Lab and Ambulatory Surgical Center Setting.

The landscape of healthcare is shifting towards outpatient settings such as Office-Based Labs (OBLs) and Ambulatory Surgery Centers (ASCs). This transition, driven by the Centers for Medicare & Medicaid Services (CMS), presents various business and corporate models for interventional radiologists seeking to practice outside traditional hospital environments. The role of private equity and management services in facilitating these transitions is highlighted, offering opportunities for growth, efficiency, and enhanced control over practice operations. The document also discusses the financial aspects of establishing an OBL or ASC, the benefits of outpatient procedures, and the adaptability of private equity deals to the specific needs of medical practices. It concludes by emphasizing the potential for long-term wealth creation and the adaptability of these models to individual physician needs.

Commentary: The North West London Clinical Trials Alliance: efficiency and innovation in clinical trial delivery.

BACKGROUND: The set-up, activation, and delivery of clinical trials is pivotal for the advancement of medical science, serving as the primary mechanism through which new therapeutic interventions are validated for clinical use. Despite their critical role, the execution of these trials is often encumbered by a multitude of challenges. The North West London Clinical Trials Alliance (The Alliance) was established to address these complexities. It aims to bridge the gap between emerging scientific research and its clinical application through strategic collaborations among healthcare and research entities, thereby enhancing the regional ecosystem for clinical trials. MAIN TEXT: This commentary aims to offer clarity on the fundamental insights that underlie The Alliance, providing a comprehensive understanding of its operational structure and the ecosystem it has fostered to optimise clinical trial delivery and revenue generation. The strategy employed by The Alliance centres on the cultivation of strategic partnerships across a broad spectrum of stakeholders. This approach addresses key operational challenges in clinical trial management, facilitating improvements in the development, setup, activation, and recruitment stages. Notably, The Alliance has reduced the average time to initiate trials to 19 days, compared to the standard 75 days typically observed for commercial setups in North West London. The effectiveness of The Alliance's framework was notably demonstrated during the COVID-19 pandemic, particularly with the expedited recruitment performance in the Janssen COVID-19 vaccine study conducted at Charing Cross Hospital. This instance highlighted the Alliance's capability to meet and exceed recruitment targets promptly while maintaining diversity within study cohorts. Additionally, The Alliance has effectively harnessed digital technology and infrastructure, enhancing its attractiveness to commercially funded studies and illustrating a sustainable model for clinical trial financing and execution. CONCLUSION: The North West London Clinical Trials Alliance represents a strategic response to the conventional challenges faced in clinical trial management, emphasising the importance of cross-sectoral collaboration and resource optimisation. Its efforts, particularly highlighted by its response to the COVID-19 pandemic, provide a case study in enhancing trial delivery and efficiency with significant implications for both regional and global clinical trials research communities.

The Regional Total Factor Productivity Changes of Healthcare Delivery in China: A Bootstrap Malmquist Data Envelopment Analysis.

Improving the productivity of healthcare delivery and optimizing the allocation of regional healthcare resources are crucial for the health providers. The objective of this study is to evaluate the productivity dynamics of healthcare delivery at the regional (provincial) level in China, to provide evidence-based policy implications. After a review of literature, actual number of open beds, number of occupational or assistant doctors, number of registered nurses, and number of other staff were selected as input variables. The number of diagnostic visits and number of discharged inpatients were adopted as the output indicators. The panel data of 31 provinces in mainland China from 2010 to 2019 were extracted from Health Statistics Yearbook. Bootstrap-Malmquist Data Envelopment Analysis (DEA) model was used to measure the total factor productivity changes (TFPC) and its components. During the study period, the analysis of total factor productivity (TFP) in China revealed a declining trend with an average annual decline of 0.9% (ranging from 0.860 to 1.204). For each of the 31 provinces, the annual TFP scores varied from 0.971 to 1.029. On average, technical efficiency changes (TEC) had showed a downward trend from 2010-2011 (0.980) to 2013-2014 (0.982), and then an upward trend in 2014-2015 (1.029) and the following three consecutive years since 2016-2017 (1.000, 1.013, 1.009). Similarly, the trend in technological changes (TC) was consistent with the TEC from 2010-2019, which fluctuated between 0.969 and 1.011 on average per year at the provincial level. Notably, the point of inflection appeared at 2013-2014. Regional healthcare inputs and outputs in mainland China saw an upward trend from 2010 to 2019. However, TFPC, TEC, and TC decreased across all 31 provinces. TFP experienced a declining trend from 2010 to 2014, followed by growth until 2019. This may be related to the new healthcare reform being implemented since 2009, as service efficiency and capacity may undergo a reversal at the beginning of the reform.

The varied perspectives of organisational effectiveness: What's at stake for early childhood development programmes in Rwanda?

Within global health and development, dissatisfaction with nongovernmental organisations' effectiveness (NGOs) is an increasingly pervasive aspect of programming. Today, the international community no longer accepts that NGOs are doing what they claim. This change in expectations has emphasised the importance of measuring organisational effectiveness for improved health and development impact. Using New Institutionalism as a theoretical framework, we investigated how institutional norms and expectations influence the adoption of structures and processes by NGOs, and Early Childhood Development (ECD) programming effectiveness in Rwanda - since little research connects these concepts. We employed qualitative methods: 45 in-depth interviews and 6 focus group discussions. Findings revealed a misalignment of 'organizational effectiveness' across scales, from global to local. Findings stress that, effectiveness, though an expectation of the institutional environment, may not be a valid construct for NGOs, generating implications for ECD programming. Findings also indicate measurement of global health interventions generally and the notion of effectiveness specifically can yield adverse implications for ECD programming. These findings are relevant for researchers and practitioners trying to better understand organisational effectiveness for ECD programmes because they suggest that effectiveness is socially constructed and measured differently across the different scales.

The Potential of Advanced Rooming to Improve Communication and Visit Efficiency in Federally Qualified Health Centers.

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.

A Multi-dimensional Framework of Valued Output for Primary Care in England.

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.

Efficiency evaluation and promoter identification of primary health care system in China: an enhanced DEA-Tobit approach.

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.

Pursuing sustainable performance in healthcare organizations: a sustainable business model perspective.

PURPOSE: This paper explores the use of Dynamic Business Modeling for Sustainability (DBMfS) in healthcare management settings as a holistic approach to integrating economic, social, and environmental dimensions into the business formula of these complex organizations. DESIGN/METHODOLOGY/APPROACH: After framing sustainable value in healthcare in terms of organizational complexity, wicked problems, and emerging managerial challenges, the paper proposes and illustrates the DBMfS approach that adopts a systemic view of sustainable value in healthcare. According to a qualitative perspective, a single-case study of a maternity-related healthcare treatment is also described to explore the implications and limitations of using this approach to sustainable business modeling in healthcare organizations. FINDINGS: Findings show that, by embracing sustainability through DBMfS, healthcare organizations can improve operational efficiency, reduce waste (like energy, water, and medical supplies), and enhance cost-effectiveness, thus contributing significantly to societal well-being. ORIGINALITY/VALUE: In recent years, the healthcare sector has faced numerous challenges and wicked problems, including escalating costs, resource constraints, and growing environmental concerns. As a result, the concept of sustainability has gained significant attention, thus calling scholars and practitioners to develop methods and tools able to integrate it into strategic management systems of healthcare organizations. By proposing the adoption of DBMfS in the healthcare sector, this paper contributes to feeding up the current debate.