Journal of Health Organization and Management最新文献

{"title":"A novel approach to integrating innovative technologies into healthcare facilities' performance measurement: an AHP-Koch Snowflake fuzzy application.","authors":"Sefer Aygün, Serkan Eti, Kevser Şahin, Yaşar Gökalp","doi":"10.1108/JHOM-10-2025-0731","DOIUrl":"https://doi.org/10.1108/JHOM-10-2025-0731","url":null,"abstract":"<p><strong>Purpose: </strong>Utilizing new technologies in the performance measurement processes of healthcare facilities is important for effective management. However, many factors influence this process. Therefore, prioritization is necessary so that managers know which factors address. Accordingly, the purpose of this study is to develop priority strategies to enable the use of new technologies in performance measurement processes in healthcare institutions.</p><p><strong>Design/methodology/approach: </strong>Within the scope of the research, factors affecting the use of new technologies in performance measurement processes in healthcare facilities were determined through the literature. The relevant factors were classified according to the dimensions of the Balanced Scorecard. Subsequently, expert opinion was obtained and weighted using Analytic Hierarchy Process (AHP) with Koch Snowflake Fuzzy Sets.</p><p><strong>Findings: </strong>The analyses conducted as part of the research revealed that the most important criteria are, in order: \"Investment and Implementation Costs,\" \"Senior Management Support and Strategic Vision\" and \"Data Security and Quality\".</p><p><strong>Originality/value: </strong>Studies focusing on integrating innovative technologies into the performance measurement process in healthcare organizations are quite limited. Furthermore, the use of the AHP-Koch Snowflake Fuzzy integrated approach represents a significant innovation for the healthcare sector.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-17"},"PeriodicalIF":2.4,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148978393","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":"Performance measurement dimensions in Jordanian private hospitals: organizational and environmental determinants using PLS-SEM.","authors":"Ayman Mohammad Aburumman, Norazlina Ilias","doi":"10.1108/JHOM-05-2026-0545","DOIUrl":"https://doi.org/10.1108/JHOM-05-2026-0545","url":null,"abstract":"<p><strong>Purpose: </strong>This study examines how organizational strategy, organizational structure, market competition and environmental uncertainty are associated with the use of performance measurement dimensions (PMDs) in Jordanian private hospitals.</p><p><strong>Design/methodology/approach: </strong>A quantitative cross-sectional survey was conducted using 187 usable responses from managers representing all 69 private hospitals in Jordan. Data were analysed using partial least squares structural equation modelling (PLS-SEM) with SmartPLS 3.2.9.</p><p><strong>Findings: </strong>All four contextual factors were positively associated with the use of PMDs. Market competition showed the strongest association, followed by organizational strategy, environmental uncertainty and organizational structure. The model explained 26.3% of the variance in PMD use (R2 = 0.263), indicating that internal and external contingency factors differ in their relative explanatory relevance.</p><p><strong>Practical implications: </strong>Hospital managers should adopt integrated performance dashboards combining financial, efficiency, effectiveness, flexibility and sustainability measures. PMDs should be aligned with strategic priorities, organizational arrangements and changing environmental conditions. These findings relate to the use of performance information and should not be interpreted as evidence that PMD use necessarily improves hospital performance or patient outcomes.</p><p><strong>Originality/value: </strong>This study extends contingency-based performance measurement research by providing evidence from Jordanian private hospitals. It demonstrates how four established contextual factors differ in their association with the use of multidimensional financial and non-financial performance information in an under-researched healthcare setting.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-27"},"PeriodicalIF":2.4,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957015","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":"Customer healthcare experience: a communication-based perspective on healthcare service quality.","authors":"Caglar Samsa, Nazan Korucuk","doi":"10.1108/JHOM-03-2026-0287","DOIUrl":"https://doi.org/10.1108/JHOM-03-2026-0287","url":null,"abstract":"<p><strong>Purpose: </strong>In today's healthcare landscape, the patient experience has become a key issue. Despite numerous studies, research examining how these experiences influence perceptions of healthcare quality remains limited. This limitation also applies to studies investigating how these experiences influence behavioural intentions. Against this backdrop, this study aims to incorporate patient experience into its research framework, examining the direct and indirect effects of a doctor's communication skills on the quality of healthcare services and patients' behavioural intentions.</p><p><strong>Design/methodology/approach: </strong>Data were collected from 343 participants who had experienced hospital services within the past year via a random sampling technique. The relationships between the variables were also tested via partial least squares structural equation modelling (PLS-SEM) via Smart PLS 4 software and the Statistical Package for the Social Sciences (SPSS) version 20.</p><p><strong>Findings: </strong>The findings reveal that doctors' communication skills are crucial for a positive experience of hospital services. These skills are particularly key for improving patients' service quality perceptions and shaping behavioral intentions. The study found that doctors' communication skills influence patients' service quality perceptions and their behavioral intentions. Furthermore, the significance of service quality is emphasised. The findings demonstrate that doctors' communication skills affect patients' behavioral intentions and enhance this influence through service quality.</p><p><strong>Originality/value: </strong>The research examines the factors that influence patients' behaviour while they are in hospital. The primary focus is on doctor-patient communication and healthcare quality. To the best of our knowledge, no similar studies have been conducted. Therefore, this study is expected to fill an existing gap in the literature.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-23"},"PeriodicalIF":2.4,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148913474","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":"Examining the work experiences of women in healthcare leadership in Canada: a cross-sectional study.","authors":"Ruby Gidda, Rani Srivastava, Kim Sears, Jaya Sawhney, Monakshi Sawhney","doi":"10.1108/JHOM-01-2026-0075","DOIUrl":"https://doi.org/10.1108/JHOM-01-2026-0075","url":null,"abstract":"<p><strong>Purpose: </strong>Women's representation in healthcare leadership roles in Canada is increasing, yet limited prospective data exist on their perceptions of empowerment, organizational support, job satisfaction, engagement and well-being. This study explored how women in director-level or higher positions describe their work experience.</p><p><strong>Design/methodology/approach: </strong>A quantitative cross-sectional study was conducted from February to May 2025. Participants held director-level positions or higher and were recruited from Health Authorities across British Columbia. A total of 185 participants who self-identified as a woman completed an online questionnaire including demographic items and the Picker Employee Questionnaire (PEQ). Data were exported from Qualtrics© and analyzed using SPSS (IBM version 27). Descriptive statistics were used to analyze demographic information and their work experience. Inferential statistics was used to examine relationships and group differences.</p><p><strong>Findings: </strong>Overall, women reported positive, compassionate and inclusive work environments with strong safety and health scores. Engagement was lower than morale and teamwork. Protective factors against intent to leave included compassion, inclusivity, voice and safety. Organizational support, empathy and psychological safety promoted engagement, while excessive work pressure was a major risk factor.</p><p><strong>Originality/value: </strong>Women healthcare leaders generally experience supportive workplaces, but reducing work pressure and enhancing engagement remain critical for retention and well-being.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-12"},"PeriodicalIF":2.4,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898106","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":"Validity and reliability of measures of burnout, resilience, leadership and interprofessional relationships in a Frontline Healthcare Workers Crisis Survey (FHWCS) and Healthcare Leaders Crisis Survey (HLCS).","authors":"David Besong Tataw, Nana Arthur-Mensah, Sandra Spataro, Deborah Patten, Stephen Robert Poulin, Kinsey Bryant-Lee","doi":"10.1108/JHOM-05-2025-0268","DOIUrl":"https://doi.org/10.1108/JHOM-05-2025-0268","url":null,"abstract":"<p><strong>Purpose: </strong>The COVID-19 pandemic challenged and transformed the healthcare workplace and the interconnections between leaders and frontline workers, and interprofessional configurations thus necessitated holistic psychometric studies that encompassed frontline workers and leaders. Within a conceptual framework combining job demands-resources and open systems theories, two studies (2023 and 2025) assessed the validity and reliability of measures of burnout, resilience, leadership behavior, interprofessional relationships, workplace environment and outcomes (turnover, job satisfaction, patient outcomes and performance) for frontline healthcare workers (N = 209) and leaders (N = 101).</p><p><strong>Design/methodology/approach: </strong>In study 1 (2023) we assessed validity and tested reliability evidence using exploratory and confirmatory factor analysis (EFA/CFA), convergent validity, discriminant validity, Cronbach's alpha, intercorrelation analysis and composite reliability for burnout and resilience in phase 1. EFA, convergent validity, discriminant validity, Cronbach's alpha and intercorrelation analysis, for interprofessional relationships and leadership behaviors covering frontline healthcare workers in phase 2; and healthcare leaders in phase 3, respectively. In study 2 (2025), we assessed the content and face validity of each question.</p><p><strong>Findings: </strong>We established evidence of validity and reliability for measures of burnout and resilience for frontline healthcare workers and leaders, interprofessional practice and perceived leadership behavior scales among frontline workers and interprofessional healthcare practice leadership and managers' leadership behavior scales. Further, content and face validity were confirmed for all constructs.</p><p><strong>Originality/value: </strong>Our contributions include the following: a more comprehensive and integrated psychometric toolkit with crisis-assessment utility, the extension of validation work across two healthcare groups and role-specific, validated measures of burnout, resilience and interprofessional practice leadership for healthcare leaders.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1-40"},"PeriodicalIF":2.4,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882241","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 future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.","authors":"Tugce Schmitt, Marie Delnord, Emilie Cauët, Els Van Valckenborgh, Marc Van den Bulcke","doi":"10.1108/JHOM-05-2024-0202","DOIUrl":"10.1108/JHOM-05-2024-0202","url":null,"abstract":"<p><strong>Purpose: </strong>Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care.</p><p><strong>Design/methodology/approach: </strong>Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium.</p><p><strong>Findings: </strong>The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine.</p><p><strong>Originality/value: </strong>To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1173-1186"},"PeriodicalIF":2.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568438","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":"Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.","authors":"A Subaveerapandiyan, Dalitso Mvula, Naved Ahmad, Amreen Taj, Mohammed Gulzar Ahmed","doi":"10.1108/JHOM-04-2024-0154","DOIUrl":"https://doi.org/10.1108/JHOM-04-2024-0154","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice.</p><p><strong>Design/methodology/approach: </strong>A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare.</p><p><strong>Findings: </strong>The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology.</p><p><strong>Originality/value: </strong>This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":"40 6","pages":"1065-1082"},"PeriodicalIF":2.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876371","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 influencing the enhancement of the new iron triangle in healthcare organisations.","authors":"Albi Thomas, M Suresh","doi":"10.1108/JHOM-05-2024-0196","DOIUrl":"10.1108/JHOM-05-2024-0196","url":null,"abstract":"<p><strong>Purpose: </strong>A new paradigm, \"healthcare's new iron triangle,\" has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations.</p><p><strong>Design/methodology/approach: </strong>The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed \"Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis\" to address the \"why\" and \"how\" the factors interact and prioritise the identified factors.</p><p><strong>Findings: </strong>The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study.</p><p><strong>Research limitations/implications: </strong>The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas.</p><p><strong>Practical implications: </strong>Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations.</p><p><strong>Originality/value: </strong>In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1187-1208"},"PeriodicalIF":2.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477297","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 fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.","authors":"Francisca Arboh, Xiaoxian Zhu, Samuel Atingabili, Elizabeth Yeboah, Emmanuel Kwateng Drokow","doi":"10.1108/JHOM-06-2024-0229","DOIUrl":"10.1108/JHOM-06-2024-0229","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design/methodology/approach: &lt;/strong&gt;The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Findings: &lt;/strong&gt;The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Research limitations/implications: &lt;/strong&gt;While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Practical implications: &lt;/strong&gt;The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Originality/value: &lt;/strong&gt;The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the ","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1148-1172"},"PeriodicalIF":2.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059993","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":"Artificial intelligence and big data from digital health applications: publication trends and analysis.","authors":"Selma Arslantaş","doi":"10.1108/JHOM-06-2024-0241","DOIUrl":"10.1108/JHOM-06-2024-0241","url":null,"abstract":"<p><strong>Purpose: </strong>The integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using big data obtained in the provision of health services are being added to each passing day. There are also some problems related to the use of AI technologies in health service delivery. In this respect, it is aimed to understand the use of digital health, AI and big data technologies in healthcare services and to analyze the developments and trends in the sector.</p><p><strong>Design/methodology/approach: </strong>In this research, 191 studies published between 2016 and 2023 on digital health, AI and its sub-branches and big data were analyzed using VOSviewer and Rstudio Bibliometrix programs for bibliometric analysis. We summarized the type, year, countries, journals and categories of publications; matched the most cited publications and authors; explored scientific collaborative relationships between authors and determined the evolution of research over the years through keyword analysis and factor analysis of publications. The content of the publications is briefly summarized.</p><p><strong>Findings: </strong>The data obtained showed that significant progress has been made in studies on the use of AI technologies and big data in the field of health, but research in the field is still ongoing and has not yet reached saturation.</p><p><strong>Research limitations/implications: </strong>Although the bibliometric analysis study conducted has comprehensively covered the literature, a single database has been utilized and limited to some keywords in order to reach the most appropriate publications on the subject.</p><p><strong>Practical implications: </strong>The analysis has addressed important issues regarding the use of developing digital technologies in health services and is thought to form a basis for future researchers.</p><p><strong>Originality/value: </strong>In today's world, where significant developments are taking place in the field of health, it is necessary to closely follow the development of digital technologies in the health sector and analyze the current situation in order to guide both stakeholders and those who will work in this field.</p>","PeriodicalId":47447,"journal":{"name":"Journal of Health Organization and Management","volume":" ","pages":"1083-1106"},"PeriodicalIF":2.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142677315","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}