Building an Automated Problem List Based on Natural ...
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Building an Automated Problem List Based on Natural ...
However, physicians rarely maintain problem lists. Our team is building a system using MetaMap and. UMLS to automatically populate the problem list. We.
Building an Automated Problem List Based on Natural Language Processing: Lessons Learned in the Early Phase of Development Imre Solti, MD, PhD1, Barry Aaronson, MD1, Grant Fletcher, MD, MPH1, Magdolna Solti, MD, MSc2, John H. Gennari, PhD1, Melissa Cooper1, Thomas Payne, MD1 1 University of Washington, Seattle, WA; 2Northwest Cancer Specialists, Vancouver, WA Abstract Detailed problem lists that comply with JCAHO requirements are important components of electronic health records. Besides improving continuity of care electronic problem lists could serve as foundation infrastructure for clinical trial recruitment, research, biosurveillance and billing informatics modules. However, physicians rarely maintain problem lists. Our team is building a system using MetaMap and UMLS to automatically populate the problem list. We report our early results evaluating the application. Three physicians generated gold standard problem lists for 100 cardiology ambulatory progress notes. Our application had 88% sensitivity and 66% precision using a non-modified UMLS dataset. The system’s misses concentrated in the group of ambiguous problem list entries (Chi-square=27.12 p
