Health Systems最新文献

From theory to therapy: integrating artificial intelligence for transformative healthcare innovation. 从理论到治疗：整合人工智能实现变革性医疗创新。

IF 2.2

Health Systems Pub Date : 2026-01-29 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2599121

Julia Kulkova, Ignat Kulkov, Ahmed Zahlan, René Rohrbeck, Loick Menvielle

{"title":"From theory to therapy: integrating artificial intelligence for transformative healthcare innovation.","authors":"Julia Kulkova, Ignat Kulkov, Ahmed Zahlan, René Rohrbeck, Loick Menvielle","doi":"10.1080/20476965.2025.2599121","DOIUrl":"10.1080/20476965.2025.2599121","url":null,"abstract":"The rapid evolution of artificial intelligence (AI) is reshaping healthcare by improving diagnostics, patient outcomes, and operational efficiency. Yet, many frameworks for AI adoption overlook the complex and iterative nature of healthcare systems. This study introduces the AI Healthcare Symbiosis Cycle (AI-HSC), a novel framework based on Dynamic Capabilities Theory, Systems Theory, and Kotter's 8-Step Change Model, conceptualising AI adoption as a continuous and adaptive process. Dynamic Capabilities Theory highlights the need for organisations to sense opportunities, seize resources, and change processes in response to AI advancements. Systems Theory focuses on optimising interdependencies within healthcare organisations, while Kotter's model ensures a structured approach to managing change. The AI-HSC aligns phases of AI integration - initiation, integration, evolution, and revolution - with Kotter's steps, promoting a systematic and scalable adoption strategy. Key recommendations include implementing pilot programs, fostering interdisciplinary coalitions, embedding AI literacy into organisational culture, and developing robust ethics and compliance frameworks. By bridging theory with practice, the AI-HSC provides actionable strategies for sustainable AI integration, addressing critical barriers and fostering continuous innovation. This research contributes to the digital change discourse, offering valuable insights for academia and healthcare practitioners.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 3","pages":"189-206"},"PeriodicalIF":2.2,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The mediating effect of patient satisfaction in the relationship between service quality and revisiting intentions: the case of two public emergency departments (EDs). 患者满意度在服务质量与重访意愿关系中的中介作用：以两个急诊科为例。

IF 2.2

Health Systems Pub Date : 2026-01-19 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2026.2613886

Dimitrios Chatzoudes, Prodromos Chatzoglou, Vasiliki Amarantou

引用次数: 0

IT-enabled medicine dispensing in the community pharmacy: an action design research project. 社区药房的资讯科技配药：行动设计研究计划。

IF 1.2

Health Systems Pub Date : 2026-01-18 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2591042

João Barata, Mateus Mendes, Ana Paula Melo Santos, Maria João Melo Neves, Kamil Woźniak, Anna Drozdz, José Sousa

{"title":"IT-enabled medicine dispensing in the community pharmacy: an action design research project.","authors":"João Barata, Mateus Mendes, Ana Paula Melo Santos, Maria João Melo Neves, Kamil Woźniak, Anna Drozdz, José Sousa","doi":"10.1080/20476965.2025.2591042","DOIUrl":"https://doi.org/10.1080/20476965.2025.2591042","url":null,"abstract":"This paper presents a community pharmacy information system to assist with medication dispensing and monitoring medication adherence. The proposed prototype uses artificial intelligence (AI), cloud, and mobile technology to support patient medication records, reduce medication errors when preparing pillboxes, and provide personalized information to end-users. Action design research was selected to understand how innovative dispensing processes can be deployed in community pharmacies. The results include design guidelines for AI-enabled medicine dispensing and an evaluation of digital transformation success factors in this vital healthcare sector. AI-enabled systems can contribute to (1) prevent errors in filling pillbox compartments, (2) provide an additional cross-check in medication dispensing, and (3) identify medication adherence problems in more demanding scenarios of institutions with multiple patients. However, there are also relevant challenges, making the replacement of non-critical manual tasks, complementary checkpoints, and pre-validation stages of medicine dispensing the most promising use cases for artificial intelligence adoption.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 2","pages":"174-187"},"PeriodicalIF":1.2,"publicationDate":"2026-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13188575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147989421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On-demand therapy 24/7! Mental mHealth app features and social metrics as predictors of use. 全天候按需治疗！心理移动健康应用的功能和社交指标作为使用的预测指标。

IF 2.2

Health Systems Pub Date : 2026-01-10 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2609995

Panagiota Galetsi, Korina Katsaliaki, Sameer Kumar, Neha Kumar

{"title":"On-demand therapy 24/7! Mental mHealth app features and social metrics as predictors of use.","authors":"Panagiota Galetsi, Korina Katsaliaki, Sameer Kumar, Neha Kumar","doi":"10.1080/20476965.2025.2609995","DOIUrl":"10.1080/20476965.2025.2609995","url":null,"abstract":"This study investigates social metrics and features of mental health mobile applications (mHealth apps), a growing digital health tool used by individuals often facing social stigma, barriers to care, and the need for privacy-preserving support. Drawing on an app-derived dataset of 434 mental mHealth apps, we developed a conceptual framework to examine a comprehensive set of 35 app metrics and feature characteristics relevant to mHealth apps' user ratings, functionality, ease-of-use, credibility, privacy assurance, and monetization and test whether these app attributes can explain the patients' intention-to-use (download) these apps. Data collection provides a detailed map of these apps current state-of-the-art. Results indicate that app downloads positively relate to stars rating and user evaluations, app's description length, number of screenshots and readability in the app store, app's age, recent updates and developer information. Interestingly, features related to functional support, privacy, monetization and expert endorsement are not found significant. These findings offer preliminary guidance for developers and organizations aiming to create effective mental mHealth apps, while also advancing the dialogue on assessment criteria to support informed choices by patients and clinicians. By emphasizing objective app data and design features, we highlight how digital health tools shape help-seeking behaviours, particularly among vulnerable populations.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 3","pages":"243-260"},"PeriodicalIF":2.2,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysing the drivers of unnecessary caesarean sections in developing countries: a systems approach. 分析发展中国家不必要剖腹产的驱动因素：一种系统方法。

IF 2.2

Health Systems Pub Date : 2025-12-21 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2601100

Seyed Hossein Hosseini, Sharif Torkaman Nejad, Seyedehfatemeh Golrizgashti, Masoud Fakhimi

{"title":"Analysing the drivers of unnecessary caesarean sections in developing countries: a systems approach.","authors":"Seyed Hossein Hosseini, Sharif Torkaman Nejad, Seyedehfatemeh Golrizgashti, Masoud Fakhimi","doi":"10.1080/20476965.2025.2601100","DOIUrl":"10.1080/20476965.2025.2601100","url":null,"abstract":"The World Population Prospects (2022) report by the United Nations highlights a decline in global population growth, underscoring the critical role of healthcare systems in reducing maternal and infant mortality rates. While birth rates vary across high-income and low- and middle-income countries, ensuring safe childbirth remains a fundamental healthcare objective. Despite the known risks associated with unnecessary caesarean sections, their prevalence continues to rise in developing countries. This study examines the underlying factors contributing to this trend, using Iran as a case study. A systems approach is employed, incorporating Causal Loop Diagrams (CLDs) and the Decision Making Trial and Evaluation Laboratory (DEMATEL) to identify and prioritise key influencing factors. The findings suggest that societal and cultural dynamics play a more significant role in the increasing rates of unnecessary caesarean sections than technical medical considerations and individual preferences. Notably, the influence of word-of-mouth and support from reference groups underscores the importance of a community-focused approach in addressing this challenge.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 3","pages":"223-242"},"PeriodicalIF":2.2,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diagnosis of polycystic ovary syndrome (PCOS) using TabNet and BiLSTM with attention model. TabNet与BiLSTM结合注意模型诊断多囊卵巢综合征（PCOS）。

IF 2.2

Health Systems Pub Date : 2025-12-21 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2601099

Imran Khan, Brajesh Kumar Khare

引用次数: 0

Correction. 修正。

IF 1.2

Health Systems Pub Date : 2025-12-01 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2593760

引用次数: 0

Drowning in data, starving for access: unlocking the bottleneck in molecular medicine and cancer research. 淹没在数据中，渴望获取：解开分子医学和癌症研究的瓶颈。

IF 1.2

Health Systems Pub Date : 2025-11-26 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2591052

Kate Manley, Jerry Sh Lee

引用次数: 0

Reliability of ChatGPT-4o in analysing medical data: a test case study on patients at risk for limb amputation. chatgpt - 40在分析医疗数据方面的可靠性：对截肢风险患者的测试案例研究

IF 1.2

Health Systems Pub Date : 2025-11-14 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2580977

Liat Toderis, Iris Reychav, Roger McHaney, Bernice Oberman, Chen Speter, Ronen Loebstein

{"title":"Reliability of ChatGPT-4o in analysing medical data: a test case study on patients at risk for limb amputation.","authors":"Liat Toderis, Iris Reychav, Roger McHaney, Bernice Oberman, Chen Speter, Ronen Loebstein","doi":"10.1080/20476965.2025.2580977","DOIUrl":"https://doi.org/10.1080/20476965.2025.2580977","url":null,"abstract":"Purpose: This research investigates ChatGPT-4o reliability in analyzing medical data for diabetic patients at risk of limb loss. It evaluates whether a generative AI tool can serve as a viable alternative to traditional statistical methods for predictive medical analysis. The research question is: How does ChatGPT-4o perform in answering predictive questions about patient outcomes compared with a professional statistician using conventional tools?Methods: Data were drawn from Sheba Medical Center's diabetic foot clinic, focusing on mortality and amputation risk. ChatGPT-4o's predictive responses were compared with those produced by a professional statistician. The study emphasized the importance of prompt design and required substantial human involvement in data cleaning to ensure accuracy.Results: ChatGPT-4o produced accuracy comparable to traditional statistical methods when prompts were well-designed. Findings highlight the central role of prompt engineering in obtaining reliable outputs. Human intervention in preparing the dataset remained necessary, underscoring current limitations in fully automating the process.Conclusion: The study demonstrates the potential of generative AI-specifically ChatGPT-4o-as a tool enabling clinicians to analyse medical data without advanced technical training. With proper instruction and careful prompt engineering, generative AI can help democratize access to predictive medical analysis as a user-friendly alternative to conventional methods.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 2","pages":"125-139"},"PeriodicalIF":1.2,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13188532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147989433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-site big data analysis of factors impacting the time to disposition in pediatric mental and behavioural health emergency department visits. 影响儿童精神和行为健康急诊科就诊时间的因素的多站点大数据分析

IF 1.2

Health Systems Pub Date : 2025-10-25 eCollection Date: 2026-01-01 DOI: 10.1080/20476965.2025.2577093

Samuel N Koscelny, David M Neyens, Farzad Zeinali, Kevin Taaffe, Anjali Joseph, Ann Dietrich

{"title":"A multi-site big data analysis of factors impacting the time to disposition in pediatric mental and behavioural health emergency department visits.","authors":"Samuel N Koscelny, David M Neyens, Farzad Zeinali, Kevin Taaffe, Anjali Joseph, Ann Dietrich","doi":"10.1080/20476965.2025.2577093","DOIUrl":"https://doi.org/10.1080/20476965.2025.2577093","url":null,"abstract":"The increasing prevalence of mental and behavioural health (MBH) conditions in children has posed significant strain on emergency departments (EDs) to provide adequate and timely care. This study analysed factors associated with time to disposition (TTD) for this patient population. The study utilised electronic health record (EHR) data for pediatric ED visits from 11 ED facilities in South Carolina between October 2017 to March 2023. We identified the MBH patients in our dataset based on ICD-10 codes. In total, 289,721 pediatric ED visits were analysed in a mixed-effects regression model predicting TTD. Male patients (p < .0001), weekend visits (p < .0001), and multiple ED visits (p < .0001) were associated with decreased TTD, but interactions between MBH-related visits and repeat ED visits significantly prolonged TTD (p < .0001) and nighttime and presenting during the fall season also influenced TTD (p < .001). Pediatric MBH-related ED visits have significantly longer TTD than non-MBH ED visits (p < .01). MBH patients with two or more previous ED visits also resulted in significantly longer TTD (p < .0001). Our analysis demonstrated system-level and patient-level factors significantly impact the TTD in an ED. These findings highlight the need to design and evaluate new interventions to improve care for pediatric MBH patients as well as overall ED performance.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"15 2","pages":"111-124"},"PeriodicalIF":1.2,"publicationDate":"2025-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13188533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147989463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0