| Literature DB >> 32209005 |
Monica M Bertagnolli1, Brian Anderson2, Kelly Norsworthy3, Steven Piantadosi1, Andre Quina2, Richard L Schilsky4, Robert S Miller4, Sean Khozin3.
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.Entities:
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Year: 2020 PMID: 32209005 PMCID: PMC7213586 DOI: 10.1200/JCO.19.03094
Source DB: PubMed Journal: J Clin Oncol ISSN: 0732-183X Impact factor: 44.544