Medical device surveillance with electronic health records

1 code implementation • 3 Apr 2019 • Alison Callahan, Jason A. Fries, Christopher Ré, James I Huddleston III, Nicholas J Giori, Scott Delp, Nigam H. Shah

Using hip replacements as a test case, our methods accurately extracted implant details and reports of complications and pain from electronic health records with up to 96. 3% precision, 98. 5% recall, and 97. 4% F1, improved classification performance by 12. 7- 53. 0% over rule-based methods, and detected over 6 times as many complication events compared to using structured data alone.

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