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Published on: December 18, 2010
Predictive accuracy of the complex 30-day model for colon surgical site infections in emergent operations
SaeRam Oh1, Annmarie Butare1, William Irish2
1Department of Surgery, Brody School of Medicine at East Carolina University, Greenville, NC, USA.
Background:
Surgical site infections (SSI) following colon surgery continue to pose a significant clinical and financial impact on a healthcare system. The National Healthcare Safety Network (NHSN) utilizes the Complex 30-day SSI model to report the predictive number of infections for a hospital, which is submitted to the Centers for Medicare and Medicaid Services. However, this model does not account for patient acuity. The primary aim of the study was to determine the predictive accuracy of the model for predicting colon SSI in patients undergoing urgent and emergent general surgical procedures.
Methods:
The National Surgery Quality Improvement Program (NSQIP) database was queried for variables used in the NHSN Complex 30-day SSI model from 2016 to 2022. Patients ≥18 years old who underwent an urgent/emergent general surgery colon operation were included. Utilizing model variables and coefficients, the predicted number of infections was calculated. A receiver-operating characteristic (ROC) curve was generated and the area under the curve (AUC) calculated to evaluate the model's predictive accuracy.
Results:
Of the 476,178 patients included, 51 % were female with a mean age of 58 (±24), 15.7 % had diabetes, 35.2 % had body mass index (BMI) ≥ 30mg/kg2 and 61.1 % has ASA classification of 3/4/5. The overall infection rate was 4.3 %. In patients sustaining an SSI, 16.6 % had diabetes, 36.7 % had BMI ≥30mg/kg2, and 68.0 % had an ASA class of 3/4/5. The ROC curve revealed an AUC of 0.554 (95 % CI: 0.5498, 0.5577.) CONCLUSIONS: Our findings demonstrate the Complex 30-day SSI model currently has a predictive accuracy only slightly better than chance in patients undergoing urgent or emergent general surgical colon operations. This may have significant impact on hospitals caring for patients with a higher acuity. Future models should take into consideration the acuity of the operation in efforts to improve the predictive accuracy in this patient population.
Insights
The Complex 30-day Surgical Site Infection (SSI) model shows poor predictive accuracy for urgent colon surgeries. Future models need to account for patient acuity to improve predictions for high-risk patients.
Area of Science:
- Healthcare quality improvement
- Surgical outcomes research
- Infectious disease epidemiology
Background:
- Surgical site infections (SSI) after colon surgery present significant clinical and financial burdens.
- The National Healthcare Safety Network (NHSN) Complex 30-day SSI model is used for hospital reporting but doesn't account for patient acuity.
- Urgent and emergent colon surgeries represent a population with potentially higher acuity and risk.
Purpose of the Study:
- To evaluate the predictive accuracy of the NHSN Complex 30-day SSI model for colon surgery patients.
- To determine if the model's predictions align with actual infection rates in urgent/emergent cases.
- To identify limitations of the current model in diverse surgical populations.
Main Methods:
- Utilized the National Surgery Quality Improvement Program (NSQIP) database (2016-2022).
- Included adult patients undergoing urgent/emergent general surgery colon operations.
- Calculated predicted infections using NHSN model variables and coefficients; assessed predictive accuracy via Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC).
Main Results:
- Analyzed 476,178 patients; overall SSI rate was 4.3%.
- Patients with SSI had higher rates of diabetes (16.6%), obesity (BMI ≥30kg/m², 36.7%), and severe comorbidities (ASA 3/4/5, 68.0%).
- The model's predictive accuracy, measured by AUC, was 0.554, indicating performance only slightly better than chance.
Conclusions:
- The NHSN Complex 30-day SSI model demonstrates limited predictive accuracy for urgent/emergent colon surgery.
- This inaccuracy may disproportionately affect hospitals managing higher-acuity patient populations.
- Future SSI prediction models should incorporate surgical acuity to enhance accuracy for at-risk patients.
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