1. Predictive Analytics for the KMAP-O Model in Design and Evaluation of Diabetes Care Management Research
- Author
-
Thomas T. H. Wan
- Subjects
comparative effectiveness evaluation ,and methods ,Medicine (General) ,Knowledge management ,Epidemiology ,business.industry ,Computer science ,Health Policy ,030209 endocrinology & metabolism ,Predictive analytics ,predictive analytics ,03 medical and health sciences ,AI research in diabetes care and control ,R5-920 ,0302 clinical medicine ,Commentary ,Management research ,030212 general & internal medicine ,Public aspects of medicine ,RA1-1270 ,behavioral components of selfcare intervention ,business - Abstract
This is a commentary on methodological challenges and analytical requirements in designing an evaluation of the knowledge, motivation, attitude, preventive practice-outcome (KMAP-O) model for selfcare management of diabetes. Critical issues pertaining to an investigation of the dose-response relationship between the intervention program and outcomes, the comparative effectiveness evaluation, and the lengths of observation were noted. Although numerous publications on factors influencing diabetes care and control were systematically reviewed and documented in the literature, scientific results on artificial intelligence research remain to be uncovered. To optimizing the knowledge and clinical practice in selfcare management, specific methodological approaches to predictive analytics are suggested for future clinical studies, using a comprehensive behavioral system such as the KMAP-O model.
- Published
- 2021
- Full Text
- View/download PDF