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Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE).
Elbers, Danne C; Fillmore, Nathanael R; La, Jennifer; Tosi, Hannah M; Ajjarapu, Samuel; Dhond, Rupali; Murray, Karen; Valley, Danielle; Shannon, Colleen; Brophy, Mary T; Do, Nhan V.
Afiliación
  • Elbers DC; VA Boston Healthcare System, Boston MA, USA.
  • Fillmore NR; Harvard Medical School, Boston MA, USA.
  • La J; VA Boston Healthcare System, Boston MA, USA.
  • Tosi HM; Harvard Medical School, Boston MA, USA.
  • Ajjarapu S; VA Boston Healthcare System, Boston MA, USA.
  • Dhond R; VA Boston Healthcare System, Boston MA, USA.
  • Murray K; VA Boston Healthcare System, Boston MA, USA.
  • Valley D; Harvard Medical School, Boston MA, USA.
  • Shannon C; VA Boston Healthcare System, Boston MA, USA.
  • Brophy MT; Boston University School of Medicine, Boston MA, USA.
  • Do NV; VA Boston Healthcare System, Boston MA, USA.
Stud Health Technol Inform ; 310: 1131-1135, 2024 Jan 25.
Article en En | MEDLINE | ID: mdl-38269991
ABSTRACT
In this manuscript, we outline our developed version of a Learning Health System (LHS) in oncology implemented at the Department of Veterans Affairs (VA). Transferring healthcare into an LHS framework has been one of the spearpoints of VA's Central Office and given the general lack of evidence generated through randomized control clinical trials to guide medical decisions in oncology, this domain is one of the most suitable for this change. We describe our technical solution, which includes a large real-world data repository, a data science and algorithm development framework, and the mechanism by which results are brought back to the clinic and to the patient. Additionally, we propose the need for a bridging framework that requires collaboration between informatics specialists and medical professionals to integrate knowledge generation into the clinical workflow at the point of care.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Aprendizaje Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Aprendizaje Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos