USING CLINICAL DECISION INTELLIGENCE APPLICATIONS TO IMPROVE PATHWAYS FOR EARLIER DETECTION OF UNDERRECOGNIZED COGNITIVE DISORDERS
A.S. Khachaturian, B. Cassin, G.R. Finney
J Aging Res & Lifestyle 2023;12:14-17
Cost estimates for care for those with dementia and other cognitive impairments are rising globally, estimated to reach US $1 trillion by 2025. Lack of specialized personnel, infrastructure, diagnostic capabilities, and healthcare access impedes the timely identification of patients progressing to dementia, particularly in underserved populations. International healthcare infrastructure may be unable to handle existing cases in addition to a sudden increase due to undiagnosed cognitive impairment and dementia. Healthcare bioinformatics offers a potential route for quicker access to healthcare services; however, a better preparedness plan must be implemented now if expected demands are to be met. The most critical consideration for implementing artificial intelligence/machine learning (AI/ML) -driven clinical decision intelligence applications (CDIA) is ensuring patients and practitioners take action on the information provided.
A.S. Khachaturian ; B. Cassin ; G.R. Finney ; (2023): Using Clinical Decision Intelligence Applications to Improve Pathways For Earlier Detection Of Underrecognized Cognitive Disorders. The Journal of Aging and Lifestyle (JARLife). http://dx.doi.org/10.14283/jarlife.2023.3