Speaker: Pradeep Mutalik, MD, Associate Research Scientist in Biomedical Informatics and Data Science at Yale University
Title of Talk: Combining Rule-based NLP-lite with Rapid Iterative Chart Adjudication for Creation of a Large Gold Standard Cohort from EHR data for a Clinical Trial Emulation
When: Wednesday, October 3, 4:30pm-5:30pm
Location: 100 College Street, 11th Floor, Workshop 1167
Recording Link: https://www.youtube.com/watch?v=jwrcviGdOdk
Speaker bio:
The aim of this work was to create a gold-standard curated cohort of 10,000+ cases from the Veteran Affairs (VA) corporate data warehouse (CDW) for virtual emulation of a randomized clinical trial (CSP#592). The trial had six inclusion/exclusion criteria lacking adequate structured data. We therefore used a hybrid computer/human approach to extract information from clinical notes. Rulebased NLP output was iteratively adjudicated by a panel of trained non-clinician content experts and non-experts using an easy-to-use spreadsheetbased rapid adjudication display. This groupadjudication process iteratively sharpened both the computer algorithm and clinical decision criteria, while simultaneously training the non-experts. The cohort was successfully created with each inclusion/exclusion decision backed by a source document. Less than 0.5% of cases required referral to specialist clinicians. It is likely that such curated datasets capturing specialist reasoning and using a process-supervised approach will acquire greater importance as training tools for future clinical AI applications.
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