Surgical site infections (SSIs) are the most common and costly of hospital acquired infections. An important step in reducing SSIs is accurate SSI detection, which enables measurement and quality improvement, but currently remains expensive through manual chart review. Building off of previous work for automated and semi-automated SSI detection using expert-derived "strong features" from clinical notes, we hypothesized that additional SSI phrases may be contained in clinical notes. We systematically characterized phrases and expressions associated with SSIs. While 83% of expert-derived original terms overlapped with new terms and modifiers, an additional 362 modifiers associated with both positive and negative SSI signals were identified and 62 new base observations and actions were identified. Clinical note queries with the most common base terms revealed another 49 modifiers. Clinical notes contain a wide variety of expressions describing infections occurring among surgical specialties which may provide value in improving the performance of SSI detection algorithms.
|Original language||English (US)|
|Title of host publication||MEDINFO 2017|
|Subtitle of host publication||Precision Healthcare through Informatics - Proceedings of the 16th World Congress on Medical and Health Informatics|
|Editors||Zhao Dongsheng, Adi V. Gundlapalli, Jaulent Marie-Christine|
|Number of pages||5|
|State||Published - 2017|
|Event||16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 - Hangzhou, China|
Duration: Aug 21 2017 → Aug 25 2017
|Name||Studies in Health Technology and Informatics|
|Other||16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017|
|Period||8/21/17 → 8/25/17|
Bibliographical noteFunding Information:
This research was supported by the University of Minnesota Academic Health Center Faculty Development Award (GS, GM), Agency for Healthcare Research and Quality (R01HS24532), National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program (UL1TR000114), Fairview Health Services, and University of Minnesota Physicians.
© 2017 International Medical Informatics Association (IMIA) and IOS Press.
- Quality and safety
- Surgical wound infection