Related Experiment Video
Updated: Mar 2, 2026
05:07
CO2-Lasertonsillotomy Under Local Anesthesia in Adults
Published on: November 6, 2019
26.5K
Comparison of Automated Posttonsillectomy Bleed Capture With Self-report
D Ryan Phillips1, Susan E Ellsperman2, Bruce H Matt1
1Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indianapolis.
JAMA Otolaryngology-- Head & Neck Surgery
|May 12, 2017
Summary
Automated systems can effectively track pediatric tonsillectomy bleeding, improving accuracy over manual reports. This method enhances complication capture and provides valuable feedback for surgeons.
Area of Science:
- Otolaryngology
- Health Informatics
- Pediatric Surgery
Background:
- Tonsillectomy is a common procedure with significant postoperative bleeding risk.
- Current bleed rate monitoring relies on self-reporting, which may lack accuracy.
Purpose of the Study:
- To assess the feasibility and accuracy of automated post-tonsillectomy bleeding detection.
- To compare automated reporting with traditional self-reporting methods.
Main Methods:
- Developed an automated complication-reporting algorithm using health information exchange data.
- Compared algorithm findings with self-reported bleeding data from 1017 pediatric tonsillectomies over 19 months.
- Algorithm utilized ICD codes and free-text analysis for complication identification.
Main Results:
- The algorithm showed high agreement with self-reports (96.95%) with a kappa of 0.69.
- Sensitivity for detecting bleeding complications was 60.53%, with a specificity of 98.30%.
- The system demonstrated feasibility in capturing post-tonsillectomy bleeding events.
Conclusions:
- Automated medical record searching can capture post-tonsillectomy bleeding.
- Refinement of the algorithm is needed for optimal performance.
- Leveraging health information exchange data can improve complication capture across institutions.
