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Rapid review: Identification of digital health interventions in atherosclerotic-related cardiovascular disease populations to address racial, ethnic, and socioeconomic health disparities.
Thomas Craig, Kelly J; Fusco, Nicole; Lindsley, Kristina; Snowdon, Jane L; Willis, Van C; Arriaga, Yull E; Dankwa-Mullan, Irene.
Afiliação
  • Thomas Craig KJ; Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
  • Fusco N; Life Sciences, IBM Watson Health, Cambridge, Massachusetts.
  • Lindsley K; Life Sciences, IBM Watson Health, Cambridge, Massachusetts.
  • Snowdon JL; Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
  • Willis VC; Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
  • Arriaga YE; Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
  • Dankwa-Mullan I; Center for AI, Research, and Evaluation, IBM Watson Health, Cambridge, Massachusetts.
Cardiovasc Digit Health J ; 1(3): 139-148, 2020.
Article em En | MEDLINE | ID: mdl-35265886
ABSTRACT
Disparities in cardiovascular disease (CVD) and associated health and healthcare delivery outcomes have been partially attributed to differential risk factors, and to prevention and treatment inequities within racial and ethnic (including language) minority groups and low socioeconomic status (SES) populations in urban and rural settings. Digital health interventions (DHIs) show promise in promoting equitable access to high-quality care, optimal utilization, and improved outcomes; however, their potential role and impact has not been fully explored. The role of DHIs to mitigate drivers of the health disparities listed above in populations disproportionately affected by atherosclerotic-related CVD was systematically reviewed using published literature (January 2008-July 2020) from multiple databases. Study design, type and description of the technology, health disparities information, type of CVD, outcomes, and notable barriers and innovations associated with the technology utilized were abstracted. Study quality was assessed using the Oxford Levels of Evidence. Included studies described digital health technologies in a disparity population with CVD and reported outcomes. DHIs significantly improved health (eg, clinical, intermediate, and patient-reported) and healthcare delivery (eg, access, quality, and utilization of care) outcomes in populations disproportionately affected by CVD in 24 of 38 included studies identified from 2104 citations. Hypertension control was the most frequently improved clinical outcome. Telemedicine, mobile health, and clinical decision support systems were the most common types of DHIs identified. DHIs improved CVD-related health and healthcare delivery outcomes in racial/ethnic groups and low SES populations in both rural and urban geographies globally.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Aspecto: Determinantes_sociais_saude Idioma: En Revista: Cardiovasc Digit Health J Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Aspecto: Determinantes_sociais_saude Idioma: En Revista: Cardiovasc Digit Health J Ano de publicação: 2020 Tipo de documento: Article