Strengthening the Learning Health System in Cardiovascular Disease Prevention: Time to Leverage Big Data and Digital Solutions

Anjali A. Wagle, Nino Isakadze, Khurram Nasir, Seth Shay Martin

Research output: Contribution to journalReview article

Abstract

Purpose of Review: The past few decades have seen significant technologic innovation for the treatment and diagnosis of cardiovascular diseases. The subsequent growing complexity of modern medicine, however, is causing fundamental challenges in our healthcare system primarily in the spheres of patient involvement, data generation, and timely clinical implementation. The Institute of Medicine advocated for a learning health system (LHS) in which knowledge generation and patient care are inherently symbiotic. The purpose of this paper is to review how the advances in technology and big data have been used to further patient care and data generation and what future steps will need to occur to develop a LHS in cardiovascular disease. Recent Findings: Patient-centered care has progressed from technologic advances yielding resources like decision aids. LHS can also incorporate patient preferences by increasing and standardizing patient-reported information collection. Additionally, data generation can be optimized using big data analytics by developing large interoperable datasets from multiple sources to allow for real-time data feedback. Summary: Developing a LHS will require innovative technologic solutions with a patient-centered lens to facilitate symbiosis in data generation and clinical practice.

Original languageEnglish (US)
Article number19
JournalCurrent Atherosclerosis Reports
Volume23
Issue number5
DOIs
StatePublished - May 2021

Keywords

  • Big data
  • Learning health systems
  • Patient-centered
  • Patient-reported outcomes
  • Shared decision-making

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

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