Your browser doesn't support javascript.
loading
A proposed approach to accelerate evidence generation for genomic-based technologies in the context of a learning health system.
Lu, Christine Y; Williams, Marc S; Ginsburg, Geoffrey S; Toh, Sengwee; Brown, Jeff S; Khoury, Muin J.
Afiliação
  • Lu CY; Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
  • Williams MS; Genomic Medicine Institute Geisinger Health System, Danville, Pennsylvania, USA.
  • Ginsburg GS; Center for Applied Genomics & Precision Medicine, Duke University, Durham, North Carolina, USA.
  • Toh S; Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
  • Brown JS; Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.
  • Khoury MJ; Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Genet Med ; 20(4): 390-396, 2018 Apr.
Article em En | MEDLINE | ID: mdl-28796238
ABSTRACT
Genomic technologies should demonstrate analytical and clinical validity and clinical utility prior to wider adoption in clinical practice. However, the question of clinical utility remains unanswered for many genomic technologies. In this paper, we propose three building blocks for rapid generation of evidence on clinical utility of promising genomic technologies that underpin clinical and policy decisions. We define promising genomic tests as those that have proven analytical and clinical validity. First, risk-sharing agreements could be implemented between payers and manufacturers to enable temporary coverage that would help incorporate promising technologies into routine clinical care. Second, existing data networks, such as the Sentinel Initiative and the National Patient-Centered Clinical Research Network (PCORnet) could be leveraged, augmented with genomic information to track the use of genomic technologies and monitor clinical outcomes in millions of people. Third, endorsement and engagement from key stakeholders will be needed to establish this collaborative model for rapid evidence generation; all stakeholders will benefit from better information regarding the clinical utility of these technologies. This collaborative model can create a multipurpose and reusable national resource that generates knowledge from data gathered as part of routine care to drive evidence-based clinical practice and health system changes.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Testes Genéticos / Genômica / Atenção à Saúde / Prática Clínica Baseada em Evidências Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Testes Genéticos / Genômica / Atenção à Saúde / Prática Clínica Baseada em Evidências Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article