Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

Main|Search|PHGKB
Search PHGKB:

Last Posted: Apr 02, 2024
spot light Highlights

Organizational Factors in Clinical Data Sharing for Artificial Intelligence in Health Care.
Alaa Youssef et al. JAMA Netw Open 2023 12 (12) e2348422

From the abstract: "Are organizational factors associated with the motivation of health organizations to share clinical data for artificial intelligence (AI) development? In this qualitative study, 27 leaders from 18 health organizations were interviewed, and a predominant concern among them was data privacy risks. Most stakeholders viewed these as a substantial barrier for public health data sharing due to potential liability and reputational consequences; however, they identified external incentives as key factors for enhancing organizational motivation and fostering both within and across-sector data-sharing collaborations for AI development. The findings of this study suggest that data-sharing policies should be rooted in feasibility and incentivization strategies to promote responsible and equitable AI development in the health care sector. "

Risk perception and intended behavior change after uninformative genetic results for adult-onset hereditary conditions in unselected patients.
Nandana D Rao et al. Eur J Hum Genet 2023 9

From the abstract: "Overall, 2761 people received uninformative results and 1352 (49%) completed survey items. Respondents averaged 41 years old, 62% were female, and 56% were Non-Hispanic Asian. Results from the FACToR instrument showed mean (SD) scores of 0.92 (1.34), 7.63 (3.95), 1.65 (2.23), and 0.77 (1.50) for negative emotions, positive emotions, uncertainty, and privacy concerns, respectively, suggesting minimal psychosocial harms from genetic screening. Overall, 12.2% and 9.6% of survey respondents believed that their risk of cancer or heart disease, respectively, had changed after receiving their uninformative genetic screening results. Further, 8.5% of respondents planned to make healthcare changes and 9.1% other behavior changes. "

AI in Public Health
J Pina, ASTHO Blog, August 2023

Generative Artificial Intelligence (AI) tools have become increasingly available and accessible in recent years, empowering individuals and organizations to harness the potential of AI and machine learning. These newly available resources have sparked great curiosity within the public health community, and ASTHO members are considering the value of these tools in practice. Through ASTHO’s work in public health data modernization, and broadly in population health innovation, we’ve received many requests to address, recognize, and expound on the value and potential of AI in our field. However, as with any disruptive technology, responsible and ethical use is essential to ensure that these tools are employed in a manner that respects privacy, avoids misinformation, minimizes bias and inequities, and upholds societal well-being.

AI and Medical Education — A 21st-Century Pandora’s Box
A Cooper et al, NEJM, August 3, 2023

Many valid concerns have been raised about AI’s effects on medicine, including the propensity for AI to make up information that it then presents as fact (termed a “hallucination”), its implications for patient privacy, and the risk of biases being baked into source data. But we worry that the focus on these immediate challenges obscures many of the broader implications that AI could have for medical education — in particular, the ways in which this technology could affect the thought structures and practice patterns of medical trainees and physicians for generations to come.


Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

TOP