ArticleStudies in health technology and informatics2017
Characterizing Surgical Site Infection Signals in Clinical Notes.
Article in Studies in health technology and informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- No more tears from surgical site infections in interventional pain management.The Korean journal of pain · 2023Review
- Diagnosis and management of postoperative wound infections in the head and neck region.Oncoscience · 2023Article
- Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.Journal of the American College of Surgeons · 2021Article
- Laparoscopic common bile duct exploration in patients with previous abdominal biliary tract operations.Surgical endoscopy · 2020Article
- Characterizing Functional Health Status of Surgical Patients in Clinical Notes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
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 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.
Indexed as
Identifiers
29295241PMC6197986What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.