Accepted for/Published in: JMIR Diabetes
Date Submitted: Mar 21, 2024
Open Peer Review Period: Mar 21, 2024 - May 16, 2024
Date Accepted: Sep 4, 2024
(closed for review but you can still tweet)
Lightening the Load: Generative AI to mitigate the burden of the new era of obesity medical therapy
ABSTRACT
Highly effective anti-obesity and diabetes medications such as glucagon-like peptide 1 (GLP-1) agonists and glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 (dual) receptor agonists (RAs) have ushered in a new era of treatment of these highly prevalent, morbid conditions that have increased across the globe. However, the rapidly escalating use of GLP-1/dual RA medications is poised to overwhelm an already overburdened clinician workforce and healthcare delivery system; stifling its potentially dramatic benefits. Relying on existing systems and resources to address the oncoming rise in GLP-1/dual RA use will be insufficient. Generative artificial intelligence (GenAI) has the potential to offset the clinical and administrative demands associated with the management of patients on these medication types. Early adoption of GenAI to facilitate the management of these GLP-1/dual RAs has the potential to improve health outcomes while decreasing its concomitant workload. Research and development efforts are urgently needed to develop GenAI obesity medication management tools, as well as ensure their accessibility and utility by encouraging their integration into healthcare delivery systems.
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