Journal of Health Organization and Management最新文献

{"title":"Physician employment and hospital readmission and mortality outcomes: an organizational perspective.","authors":"Shawna Green, Hanadi Hamadi, Mei Zhao, Aaron Spaulding","doi":"10.1108/JHOM-02-2026-0209","DOIUrl":"https://doi.org/10.1108/JHOM-02-2026-0209","url":null,"abstract":"<p><strong>Purpose: </strong>To assess if hospitals with high physician employment differ in risk-standardized mortality and readmission rates.</p><p><strong>Design/methodology/approach: </strong>A cross-sectional evaluation of data from the 2021 Hospital Readmission Reduction program, Hospital Value-Based Purchasing Program, American Hospital Association and Area Health Resource Files was utilized. A binary variable was created to identify hospitals with ≤ 50% or >50% employed physicians. Dependent variables included 30-day mortality and readmission rates for acute myocardial infarction (AMI), congestive heart failure (CHF), pneumonia (PN), and chronic obstructive pulmonary disease (COPD) hospitalizations. Propensity score matching was utilized to compare hospitals. The final matched cohort compared 200 hospitals in each group ( ≤ 50% physicians and > 50% physicians).</p><p><strong>Findings: </strong>After matching, hospitals with > 50% physician employment were associated with improved mortality scores for AMI (-0.36, 95% CI: -0.58, -0.14), COPD (-0.38, 95% CI: -0.63, -0.14), and PN (-0.71, 95% CI: -1.15, -0.27). No significant differences were noted for CHF mortality or readmission rates.</p><p><strong>Originality/value: </strong>There has been a growth in hospitals employing physician in the United States. This work demonstrates that hospitals with higher physician employment levels are associated with lower mortality scores. This likely reflects a broader organizational phenotype characterized by alignment, scale and clinical integration rather than physician employment as an isolated strategy. Further research should examine organizational features to better disentangle the structure and combination of organizational characteristics underlying these associations.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-12"},"PeriodicalIF":2.4,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148273377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Workaround behaviors: nurses' strategies for coping with high workload and burnout.","authors":"Sari Mansour, Marie-Ève Beauchamp Legault, Denis Chênevert","doi":"10.1108/JHOM-08-2025-0468","DOIUrl":"https://doi.org/10.1108/JHOM-08-2025-0468","url":null,"abstract":"<p><strong>Purpose: </strong>Healthcare workers often develop particular work patterns that can improve their performance and patient safety. These working methods are known as \"workarounds\" and can be defined as alternative work procedures developed by employees to solve workflow obstacles or problems without necessarily analyzing the underlying causes. Studies on workarounds have mainly been concerned with documenting their existence, and few studies have looked at the potential antecedents of workarounds or their impacts. Building on previous research and the Conservation of Resources theory, this study aims to examine the effects of workload on workaround behaviors using the three components of burnout (emotional exhaustion, physical fatigue and cognitive exhaustion) as mediators.</p><p><strong>Design/methodology/approach: </strong>Cross-sectional data from 562 nurses in Quebec (a province of Canada) were analyzed. Structural Equation Modeling analyses provide crucial insights into the intricate relationship between workload and workarounds within healthcare settings.</p><p><strong>Findings: </strong>Notably, it reveals that physical fatigue, cognitive weariness, and emotional exhaustion are pivotal mediators in this dynamic.</p><p><strong>Originality/value: </strong>Navigating the complex dynamics between healthcare institutions' endeavors to standardize care quality and ensure patient safety and employees' responses to these demands underscores the critical role of human resource management. In this milieu, this research underscores the significant risks of workarounds while highlighting their potential positive impacts if managed adeptly. By addressing these challenges and leveraging the insights gleaned from this research, healthcare organizations can strive towards more resilient and adaptive systems that prioritize patient safety and staff well-being.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-16"},"PeriodicalIF":2.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148253639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rural hospitals closures and conversions: the role of organizational characteristics and market forces.","authors":"Mona Al-Amin, Kate J Li, Michael Rosko, Claudia Guerrazzi-Young","doi":"10.1108/JHOM-07-2025-0429","DOIUrl":"https://doi.org/10.1108/JHOM-07-2025-0429","url":null,"abstract":"<p><strong>Purpose: </strong>This study analyzes how organizational and market conditions affect rural US hospitals' risk of closure or conversion. This is especially important in light of the sweeping Medicaid cuts introduced by the Trump Administration's One Big Beautiful Bill. The paper applies the organizational legitimacy framework to explain rural hospital survival outcomes.</p><p><strong>Design/methodology/approach: </strong>Using a national panel dataset combining information from the Sheps Center, AHA Annual Survey, HCRIS, and Area Health Resource Files, the study analyzes 2,248 rural general acute hospitals. We apply a fixed effects penalized maximum likelihood estimation model to account for rare event bias and estimate the likelihood of hospital closure and conversion.</p><p><strong>Findings: </strong>Only 2.58% of hospitals closed and 1.82% converted during the study period. Rural hospitals with stronger markers of institutional legitimacy, such as critical access designation, emergency departments, or government ownership, were significantly less likely to close and convert. System membership and stronger financial performance also reduced closure risk. In contrast, higher staffing levels, longer ALOS, greater hospital density, and market concentration were associated with a higher likelihood of closure. Social vulnerability factors were more predictive of conversion than closure.</p><p><strong>Originality/value: </strong>This study is one of the first to simultaneously model rural hospital closure and conversion across a national sample using an institutional theory lens. It advances our understanding of how internal legitimacy and external market structure jointly shape organizational survival in rural healthcare and offers insights into the impact of OBBBA on rural hospitals.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-19"},"PeriodicalIF":2.2,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148260059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orchestrating digital transformation through service-dominant logic: a case study of a healthcare platform ecosystem.","authors":"Hsiaoping Yeh, Tsung-Sheng Chang, Yu-Hsin Li","doi":"10.1108/JHOM-07-2025-0385","DOIUrl":"https://doi.org/10.1108/JHOM-07-2025-0385","url":null,"abstract":"<p><strong>Purpose: </strong>This study explores how a healthcare organization can strategically orchestrate a digital platform-based business ecosystem (BE) to drive service innovation, improve care quality, and enhance patient-centered outcomes. Using SH Medicine Corporation in Taiwan as a case study, this research provides new insights into how service-dominant logic (SDL) and digital transformation reshape organizational practices and interorganizational coordination in healthcare.</p><p><strong>Design/methodology/approach: </strong>Adopting a qualitative case study approach, this study analyzed SH's ecosystem development through semi-structured interviews, document analysis, and on-site observations. The case illustrates how SH, as a focal actor, integrates hospitals, pharmacies, biotech firms, and digital service platforms into a decentralized yet coordinated system. The analysis draws on the theoretical lenses of SDL, resource orchestration, and business ecosystem theory.</p><p><strong>Findings: </strong>The findings reveal that SH leverages modular platform design, AI-enabled services, and real-time data orchestration to enhance procedural efficiency, service accessibility, and care personalization. By actively engaging with patients and community members as value co-creators, SH redefined the boundaries of traditional healthcare delivery. This study also highlights how SH aligns innovation with national health insurance policies to overcome resource constraints and sustain operational performance.</p><p><strong>Originality/value: </strong>This study contributes to the healthcare management literature by demonstrating how platform-based ecosystems and digital transformation can be operationalized to achieve both innovation and equity in healthcare services. It extends the SDL theory to health system design and identifies ecosystem-level resource orchestration as a critical capability for advancing resilient, intelligent, and inclusive healthcare organizations.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-21"},"PeriodicalIF":2.2,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148220110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The mediating role of job performance and satisfaction in the effect of digital leadership on heavy workload among healthcare workers.","authors":"Murat Sağbaş, Onur Oktaysoy, Ethem Topcuoglu","doi":"10.1108/JHOM-06-2025-0301","DOIUrl":"https://doi.org/10.1108/JHOM-06-2025-0301","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to investigate the mediating roles of job performance and job satisfaction in the effect of digital leadership on heavy workloads among healthcare workers. By focusing on the phenomenon of leadership in digital transformation in healthcare and its multi-level effects on employees, the research aims to make a unique contribution to the organizational behaviour and leadership literature.</p><p><strong>Design/methodology/approach: </strong>The theoretical framework was developed using the Resource-Based View (RBV) and Job Demands-Resources (JD-R) theories. The structural model was tested using data obtained from 386 employees working in the healthcare sector in Turkey through the Smart-PLS application.</p><p><strong>Findings: </strong>The study reveals that digital leadership has significant and positive effects on both job performance and job satisfaction. In addition, the study's findings indicate that digital leadership hurts heavy workloads, and this effect is indirectly mediated through job satisfaction. In addition to these findings, no significant effect of the job performance variable on heavy workload was found, thus not supporting the mediating role of this variable.</p><p><strong>Originality/value: </strong>The study reveals that digital leadership can transform employees' workload perceptions not only through direct effect mechanisms but also through variables related to psychological well-being. This provides a comprehensive perspective in terms of contributing to the literature on digital leadership and heavy workloads.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-23"},"PeriodicalIF":2.2,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148206602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable artificial intelligence to assess hospital financial performance during the COVID-19 pandemic through operating margin metric.","authors":"Seifollah Gholampour, Majid Asadi, Arshia Dehghan","doi":"10.1108/JHOM-04-2025-0207","DOIUrl":"10.1108/JHOM-04-2025-0207","url":null,"abstract":"<p><strong>Purpose: </strong>This study addresses critical gaps in understanding hospital financial resilience during the COVID-19 pandemic by developing an AI framework that enhances traditional analyses through capturing nonlinear interactions among clinical, financial and operational drivers of operating margins.</p><p><strong>Design/methodology/approach: </strong>Using 21 clinical, financial and operational parameters from US hospital financial reports, we evaluated 12 machine learning, ensemble and deep learning regression models to predict hospital operating margins. SHapley Additive exPlanations (SHAP) quantified feature importance, while Spearman correlation validated pairwise relationships. Interactive SHAP dependence plots analyzed hospital size-dependent dynamics.</p><p><strong>Findings: </strong>The Gradient Boosting model outperformed other regressors (MSE = 1,253, R2 = 0.79). SHAP analysis identified eight key determinants of operating margins during the COVID-19 era: supply expenses, licensed beds, patient days, charity care, Medicaid/Medicare revenues, employee benefits and the case mix index (CMI). Interactive SHAP analysis revealed hospital size-dependent financial dynamics - while supply and employee benefit expenses had a less pronounced impact on financial stability in larger hospitals, higher patient days and Medicaid/Medicare revenues played a more critical role. The impact of CMI in mid-sized hospitals remained uncertain. Smaller hospitals exhibited greater financial vulnerability, necessitating targeted cost management strategies.</p><p><strong>Originality/value: </strong>This study is among the first to integrate explainable AI with SHAP for hospital financial analysis during COVID-19, offering a blueprint for AI-powered, equity-focused stewardship. It can help leaders to balance cost containment with care quality while exposing systemic disparities in reimbursement structures.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"726-743"},"PeriodicalIF":2.2,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145281328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors affecting dentists' intention to adopt artificial intelligence: an extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) model.","authors":"Faten AlQaifi, Dilaver Tengilimoglu","doi":"10.1108/JHOM-03-2025-0159","DOIUrl":"10.1108/JHOM-03-2025-0159","url":null,"abstract":"<p><strong>Purpose: </strong>Advancements in science and technology have integrated artificial intelligence (AI) into dentistry, improving treatment processes, operational efficiency, and clinical outcomes. However, AI adoption among dentists remains underexplored, hindering progress in oral healthcare. This study aims to identify key barriers to AI adoption and examine factors influencing dentists' intention to use AI.</p><p><strong>Design/methodology/approach: </strong>A quantitative cross-sectional approach was employed, utilizing self-administered questionnaires distributed online and across various dental clinics and hospitals in Ankara, Turkey. A total of 440 dentists participated in the study. Data analysis was conducted using SPSS and SmartPLS.</p><p><strong>Findings: </strong>The study found that AI-anxiety negatively affects the intention to adopt AI in dentistry, showing a medium (almost large) effect that is stronger than other UTAUT factors such as performance expectancy, effort expectancy, and social influence, which demonstrated only small effects. Dentists with higher anxiety about learning and sociotechnical blindness are less likely to adopt AI, while concerns about job replacement and AI-configuration have less but still significant impact.</p><p><strong>Research limitations/implications: </strong>These results contribute to the growing body of knowledge on technology adoption in oral healthcare and provide practical implications for technology developers, policymakers, and other stakeholders seeking to facilitate AI integration in dentistry.</p><p><strong>Originality/value: </strong>This study provides novel insights into AI adoption in dentistry, offering guidance for future development and integration, and addressing a critical research gap in a growing field-particularly in Turkey, where implementation is still in its early stages.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"666-683"},"PeriodicalIF":2.2,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145193220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From control to action: understanding nurses' proactivity in health crises.","authors":"Uzoamaka Precious Mgbachi, Shadrack Notob Dackyirekpa, Tolulope Bolanle Osotuyi, Jeanette Beatrice Yelimon","doi":"10.1108/JHOM-12-2024-0537","DOIUrl":"10.1108/JHOM-12-2024-0537","url":null,"abstract":"<p><strong>Purpose: </strong>This study investigates the influence of service science education on nurses' locus of control, attitude and proactive behavior in response to health crises caused by recurring infectious disease outbreaks, thus addressing the relevance of proactive behavior among nurses to avert health crises.</p><p><strong>Design/methodology/approach: </strong>The study utilizes the theory of planned behavior and proactive motivation theory to address the relationship between locus of control, attitude and proactive behavior in averting health crises. The study obtained data from nurses in Nigeria; 415 valid responses were obtained. The measurement model was evaluated to ensure the validity of constructs, while the structural equation modeling (PLS-SEM) was employed to test the hypothesized relationships between variables.</p><p><strong>Findings: </strong>The findings confirm that locus of control positively and significantly influences nurses' attitudes and proactive behavior. Attitude positively and significantly mediates the relationship between locus of control and nurses' proactive behavior. Proactive behavior has a significant positive relationship with averting health crises. Service science education did not moderate the relationship between locus of control and attitude.</p><p><strong>Originality/value: </strong>This study integrates motivational (locus of control) and educational (service science education) factors to explain nurses' proactive behavior during health crises. It fills a gap by showing attitude's mediating role between locus of control and proactive behavior, often overlooked in prior research. The research informs nursing education and training programs aimed at fostering an internal locus of control and positive attitudes, enhancing healthcare workers' psychological readiness and crisis responsiveness.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"705-725"},"PeriodicalIF":2.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145253262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of burnout on nurses' intention to leave the profession: the role of work shifts.","authors":"Nancy Bouranta, Dimitrios Kafetzopoulos","doi":"10.1108/JHOM-03-2025-0139","DOIUrl":"10.1108/JHOM-03-2025-0139","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study is to examine the direct effects of burnout components on nurses' intention to leave the profession. The influence of work shift on burnout and turnover intention was also investigated.</p><p><strong>Design/methodology/approach: </strong>This empirical study involved 229 nurses working in Greek hospitals. The collected data were analysed by applying structural equation modelling (SEM). ANOVA analysis was also conducted to gain a better understanding of the significant differences of work shifts on burnout and turnover intention.</p><p><strong>Findings: </strong>The findings suggest that higher levels of emotional exhaustion and depersonalization play a significant role in nurses' intentions to leave the profession. It was also found that nurses working predominantly night and afternoon shifts reported higher levels of emotional exhaustion, lower levels of satisfaction with personal accomplishments, and greater alienation from their colleagues and patients than those working rotating or day shifts.</p><p><strong>Originality/value: </strong>While burnout is recognized as a significant factor in nurses' turnover intention, only a limited number of studies have examined the relationship between burnout and the more nuanced concept of intention to leave nursing. This study also contributes to the understanding of the effect of shifts on employee burnout and turnover intention.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"766-784"},"PeriodicalIF":2.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145276261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying and prioritizing factors affecting doctors' professional performance for effective performance management: an interval-valued Fermatean fuzzy analytic hierarchy process model.","authors":"Hilal Singer, Şükrü Özşahin","doi":"10.1108/JHOM-02-2024-0041","DOIUrl":"10.1108/JHOM-02-2024-0041","url":null,"abstract":"<p><strong>Purpose: </strong>Efficient and effective healthcare delivery relies on the optimal performance of healthcare workers. By understanding the key performance factors, decision-makers can make data-driven decisions and implement targeted improvements to achieve the best results. In the literature, no comprehensive framework yet exists that simultaneously captures the relative importance, hierarchical interactions and prioritized structure of the performance factors specific to doctors. This study aims to fill this gap by systematically identifying, structuring and weighting the key drivers of doctors' professional performance using an advanced fuzzy decision-making methodology.</p><p><strong>Design/methodology/approach: </strong>This study proposes an interval-valued Fermatean fuzzy analytic hierarchy process (AHP)-based decision-making framework to examine the decision problem. Within the model, five main factors are defined: \"personal factors,\" \"workplace conditions,\" \"social factors,\" \"management factors\" and \"career and development factors.\" Each main factor is broken down into various subfactors. The interval-valued Fermatean fuzzy AHP method is used to compare and prioritize the factors.</p><p><strong>Findings: </strong>According to the results, \"personal factors\" is the most significant main factor. The five most important subfactors are determined as \"education and experience,\" \"skills and competencies,\" \"quality of the working environment,\" \"technological infrastructure and resources\" and \"knowledge management and communication.\"</p><p><strong>Practical implications: </strong>The findings of this study serve to inform healthcare decision-making, facilitate policy development and design an effective performance management process. Additionally, they provide a valuable guide for doctors to self-assess and enhance their effectiveness.</p><p><strong>Originality/value: </strong>This study formulates the evaluation of doctors' professional performance as a complex fuzzy multicriteria decision-making problem. It pioneers the application of the interval-valued Fermatean fuzzy AHP method in healthcare and contributes by adding new dimensions to the existing body of literature. The originality of this research lies not only in the application of an advanced fuzzy methodology but also in the integration of key factors into a hierarchical structure and their systematic prioritization. The study contributes new perspectives to both theory and practice in healthcare performance management.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"811-836"},"PeriodicalIF":2.4,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145349255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}