A validated, risk assessment tool for predicting readmission after open ventral hernia repair

Abstract

Background/purpose: To present a validated model that reliably predicts unplanned readmission after open ventral hernia repair (open-VHR).

Study design: A total of 17,789 open-VHR patients were identified using the 2011-2012 ACS-NSQIP databases. This cohort was subdivided into 70 and 30% random testing and validation samples, respectively. Thirty-day unplanned readmission was defined as unexpected readmission for a postoperative occurrence related to the open-VHR procedure. Independent predictors of 30-day unplanned readmission were identified using multivariable logistic regression on the testing sample (n = 12,452 patients). Subsequently, the predictors were weighted according to β-coefficients to generate an integer-based Clinical Risk Score (CRS) predictive of readmission, which was validated using receiver operating characteristics (ROC) analysis of the validation sample (n = 5337 patients).

Results: The rate of 30-day unplanned readmission was 4.7%. Independent risk factors included inpatient status at time of open-VHR, operation time, enterolysis, underweight, diabetes, preoperative anemia, length of stay, chronic obstructive pulmonary disease, history of bleeding disorders, hernia with gangrene, and panniculectomy (all P < 0.05). ROC analysis of the validation cohort rendered an area under the curve of 0.71, which demonstrates the accuracy of this prediction model. Predicted incidence within each 5 risk strata was statistically similar to the observed incidence in the validation sample (P = 0.18), further highlighting the accuracy of this model.

Conclusion: We present a validated risk stratification tool for unplanned readmissions following open-VHR. Future studies should determine if implementation of our CRS optimizes safety and reduces readmission rates in open-VHR patients.

Keywords: Hospital readmission; Incisional hernia; Prediction model; Prediction tool; Risk assessment; Ventral hernia.