Author Interviews, Electronic Records, JAMA, NYU, Technology / 07.10.2016
Machine Learning and Free-Text Analysis of Notes Improves Patient Identification
MedicalResearch.com Interview with:
Saul Blecker, MD, MHS
Department of Population Health
New York University Langone School of Medicine,
New York, NY 10016
[email protected]
MedicalResearch.com: What is the background for this study? What are the main findings?
Response: The identification of conditions or diseases in the electronic health record (EHR) is critical in clinical practice, for quality improvement, and for clinical interventions. Today, a disease such as heart failure is typically identified in real-time using a “problem list”, i.e., a list of conditions for each patient that is maintained by his or her providers, or using simple rules drawn from structured data. In this study, we examined the comparative benefit of using more sophisticated approaches for identifying hospitalized patients with heart failure.
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