Artificial Intelligence in Healthcare: A Narrative Review of Recent Clinical Applications, Implementation Strategies, and Challenges.
Clinical documentation demands are increasingly eroding clinician time and morale. Large language models (LLMs) are emerging as practical allies, drafting notes in real-time and laying the groundwork for decision support. This narrative review examines both recent clinical applications of AI across...
| Publicado en: | Journal of Healthcare Leadership Vol. 17; pp. 863 - 877 |
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| Autores principales: | , , , , , , , |
| Formato: | pictorial review tables/charts Journal Article |
| Publicado: |
Dove Medical Press Ltd
Dec2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190717152&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190717152 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11793201 EH44 jtl: Journal of Healthcare Leadership issn: 11793201 maglogo: N pubinfo: dt: Dec2025 vid: 17 pid: 45064 pub: Dove Medical Press Ltd place: Auckland, <Blank> artinfo: ui: 190717152 190717152 190717152 10.2147/JHL.S553748 190717152 ppf: 863 ppct: 14 formats: tig: atl: Artificial Intelligence in Healthcare: A Narrative Review of Recent Clinical Applications, Implementation Strategies, and Challenges. aug: au: Elechi, Ubalaeze Orobator, Enibokun Theresa Udoh, Kuseme Eziokwu-Oluebube-Ngozi Chizoba-Agbasionye-E-Uzoma Forson, Kwesi Akonu Adom Mensah Akanbi, Olukunle O Tarawallie, Mohamed Albert sug: subj: Health Care Industry Artificial Intelligence Utilization Health Care Delivery Implementation Science Ambulatory Care Leadership Documentation Natural Language Processing Decision Support Systems, Clinical Multidisciplinary Care Team Patient Safety Audit Attitude of Health Personnel Quality of Health Care Workflow Communication Professional Regulation Cost Effectiveness Analysis Healthcare Disparities Program Planning Diagnostic Imaging Ophthalmology Sensitivity and Specificity Prediction Models Emergency Service Time Factors Behavioral and Mental Disorders Diagnosis Speech-Language Pathology Diagnosis, Laboratory Machine Learning Risk Assessment Adverse Health Care Event Equipment Alarm Systems Telemedicine Electronic Health Records Readmission Appointments and Schedules Patient Satisfaction Patient Compliance Physical Therapy Surgery, Operative Robotics Utilization Remote Patient Monitoring Privacy and Confidentiality Data Analysis ab: Clinical documentation demands are increasingly eroding clinician time and morale. Large language models (LLMs) are emerging as practical allies, drafting notes in real-time and laying the groundwork for decision support. This narrative review examines both recent clinical applications of AI across healthcare domains and leadership strategies for implementing these technologies in hospitals and ambulatory networks. We conducted a narrative review of recent literature and high-quality practice reports published, focusing on leadership strategies for implementing LLMs in hospitals and ambulatory networks. Evidence shows that when executives establish multidisciplinary AI committees, run quickly iterated pilots, and embed continuous bias and safety audits, LLM deployments improve workflow efficiency and clinician satisfaction without compromising quality. Effective programs pair clear vendor scorecards with transparent communication to staff and patients and align metrics with broader equity goals. Recent regulatory frameworks in North America and Europe reinforce the need for life-cycle governance and performance monitoring. The review concludes with a leadership roadmap linking strategic vision to practical actions that sustain safe, equitable, and financially sound LLM integration. pubtype: Academic Journal doctype: pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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