Objectives: This article aims to examine how generative artificial intelligence (AI) can be adopted with the most value in health systems, in response to the Executive Order on AI.
Materials And Methods: We reviewed how technology has historically been deployed in healthcare, and evaluated recent examples of deployments of both traditional AI and generative AI (GenAI) with a lens on value.
Results: Traditional AI and GenAI are different technologies in terms of their capability and modes of current deployment, which have implications on value in health systems.
Discussion: Traditional AI when applied with a framework top-down can realize value in healthcare. GenAI in the short term when applied top-down has unclear value, but encouraging more bottom-up adoption has the potential to provide more benefit to health systems and patients.
Conclusion: GenAI in healthcare can provide the most value for patients when health systems adapt culturally to grow with this new technology and its adoption patterns.
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http://dx.doi.org/10.1093/jamia/ocae043 | DOI Listing |
JAMA
January 2025
Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT, Washington, DC.
Importance: Health information technology, such as electronic health records (EHRs), has been widely adopted, yet accessing and exchanging data in the fragmented US health care system remains challenging. To unlock the potential of EHR data to improve patient health, public health, and health care, it is essential to streamline the exchange of health data. As leaders across the US Department of Health and Human Services (DHHS), we describe how DHHS has implemented fundamental building blocks to achieve this vision.
View Article and Find Full Text PDFJ Occup Rehabil
January 2025
Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Purpose: This qualitative study investigated the needs, barriers, and facilitators that affect primary care providers' involvement in supporting patients' stay-at-work and return-to-work following injury or illness. It also aims to understand the lived experiences of primary care providers who participated in the Extension for Community Healthcare Outcomes training program for Occupational and Environmental Medicine (ECHO OEM). By examining both the structural and experiential aspects of the program, this study seeks to provide insights into how ECHO OEM influences providers' approaches to occupational health challenges.
View Article and Find Full Text PDFEpigenetics
December 2025
Department of Anthropology, Dartmouth College, Hanover, NH, USA.
Menstrual effluent cell profiles have potential as noninvasive biomarkers of female reproductive and gynecological health and disease. We used DNA methylation-based cell type deconvolution (methylation cytometry) to identify cell type profiles in self-collected menstrual effluent. During the second day of their menstrual cycle, healthy participants collected menstrual effluent using a vaginal swab, menstrual cup, and pad.
View Article and Find Full Text PDFCancer Control
January 2025
Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Dariyah, Riyadh, Saudi Arabia.
Introduction: Cancer patients often face challenges in managing their disease, particularly with regard to contraindications related to medications, foods, and physical activity, which can negatively affect treatment outcomes. This study aimed to evaluate cancer patients' awareness of these contraindications and to explore the influence of sociodemographic factors, support systems, comorbidities, and medication use on their knowledge.
Methods: A cross-sectional prospective study was conducted with 125 cancer patients in Saudi Arabia between December 2022 and February 2023.
Health Informatics J
January 2025
Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC, Australia.
The HIV epidemic in Indonesia is one of the fastest growing in Southeast Asia and is characterised by a number of geographic and sociocultural challenges. Can large language models (LLMs) be integrated with telehealth (TH) to address cost and quality of care? A literature review was performed using the PRISMA-ScR (2018) guidelines between Jan 2017 and June 2024 using the PubMed, ArXiv and semantic scholar databases. Of the 694 records identified, 12 studies met the inclusion criteria.
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