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1.
Stud Health Technol Inform ; 312: 3-8, 2024 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-38372303

RESUMO

The current corpus of evidence-based information for chronic disease prevention and treatment is vast and growing rapidly. Behavior change theories are increasingly more powerful but difficult to operationalize in the current healthcare system. Millions of Canadians are unable to access personalized preventive and behavior change care because our in-person model of care is running at full capacity and is not set up for mass education and behavior change programs. We propose a framework to utilize data from electronic medical records to identify patients at risk of developing chronic disease and reach out to them using digital health tools that are overseen by the primary care team. The framework leverages emerging technologies such as artificial intelligence, digital health tools, and patient-generated data to deliver evidence-based knowledge and behavior change to patients across Canada at scale. The framework is flexible to enable new technologies to be added without overwhelming providers, patients or implementers.


Assuntos
Inteligência Artificial , Atenção à Saúde , População Norte-Americana , Humanos , Canadá , Doença Crônica
2.
Stud Health Technol Inform ; 294: 614-618, 2022 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-35612162

RESUMO

Many patients with Type 2 Diabetes (T2D) have difficulty in controlling their disease despite wide-spread availability of high-quality guidelines, T2D education programs and primary care follow-up programs. Current diabetes education and treatment programs translate knowledge from bench to bedside well, but underperform on the 'last-mile' of converting that knowledge into action (KTA). Two innovations to the last-mile problem in management of patients with T2D are introduced. 1) Design of a platform for peer-to-peer groups where patients can solve KTA problems together in a structured and psychologically safe environment using all the elements of the Action Cycle phase of the KTA framework. The platform uses Self-Determination Theory as the behavior change theory. 2) A novel patient segmentation method to enable the formation of groups of patients who have similar behavioral characteristics and therefore who are more likely to find common cause in the fight against diabetes.


Assuntos
Diabetes Mellitus Tipo 2 , Diabetes Mellitus Tipo 2/terapia , Educação em Saúde , Humanos , Conhecimento , Grupo Associado
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