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Surgical site infection surveillance following ambulatory surgery
Chanu Rhee1, Susan S Huang2, Sandra I Berríos-Torres3
11Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
Abstract:
We assessed 4045 ambulatory surgery patients for surgical site infection (SSI) using claims-based triggers for medical chart review. Of 98 patients flagged by codes suggestive of SSI, 35 had confirmed SSIs. SSI rates ranged from 0 to 3.2% for common procedures. Claims may be useful for SSI surveillance following ambulatory surgery.
Insights
Claims data can effectively identify surgical site infections (SSIs) in ambulatory surgery patients. This surveillance method aids in monitoring infection rates and improving patient safety outcomes.
Area of Science:
- Infection control
- Public health surveillance
- Ambulatory surgery outcomes
Background:
- Surgical site infections (SSIs) are a significant concern in healthcare settings.
- Effective surveillance methods are crucial for monitoring and reducing SSIs.
- Ambulatory surgery centers present unique challenges for infection tracking.
Purpose of the Study:
- To evaluate the utility of claims-based triggers for identifying surgical site infections (SSIs) in ambulatory surgery patients.
- To determine the feasibility of using administrative data for SSI surveillance in this population.
Main Methods:
- A retrospective review of 4045 ambulatory surgery patients was conducted.
- Claims data were analyzed using specific codes suggestive of SSI as triggers for chart review.
- Confirmed SSIs were identified through detailed medical record examination.
Main Results:
- Out of 98 patients flagged by claims data, 35 were confirmed to have SSIs.
- Observed SSI rates varied, ranging from 0% to 3.2% across common surgical procedures.
- The positive predictive value of claims-based triggers warrants further investigation.
Conclusions:
- Claims data can serve as a valuable tool for surgical site infection surveillance in ambulatory surgery.
- This approach may enhance the efficiency and scope of post-operative infection monitoring.
- Further research can refine claims-based methods for more accurate SSI detection.
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