Status Update on Data Required to Build a Learning Health System

Author:

Bertagnolli Monica M.1,Anderson Brian2,Norsworthy Kelly3,Piantadosi Steven1,Quina Andre2,Schilsky Richard L.4,Miller Robert S.4,Khozin Sean3

Affiliation:

1. Brigham and Women’s Hospital, and the Alliance for Clinical Trials in Oncology, Boston, MA

2. MITRE Corporation, Bedford, MA

3. US Food and Drug Administration, Silver Spring, MD

4. American Society of Clinical Oncology, Alexandria, VA

Abstract

Wide adoption of electronic health records (EHRs) has raised the expectation that data obtained during routine clinical care, termed “real-world” data, will be accumulated across health care systems and analyzed on a large scale to produce improvements in patient outcomes and the use of health care resources. To facilitate a learning health system, EHRs must contain clinically meaningful structured data elements that can be readily exchanged, and the data must be of adequate quality to draw valid inferences. At the present time, the majority of EHR content is unstructured and locked into proprietary systems that pose significant challenges to conducting accurate analyses of many clinical outcomes. This article details the current state of data obtained at the point of care and describes the changes necessary to use the EHR to build a learning health system.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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