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Abstract
Objective: Surgical site infection (SSI) surveillance is time-consuming and hard. Identifying high-risk patients and focusing on these patients will be cost and time effective. This study aims to develop a model to identify high-risk patients for the development of SSI after hip replacement surgery and to estimate the utility of the model.
Methods: Logistic regression model was created to determine the risk of SSI development using the National Health Service Associated Surveillance Network (USHİİSA) data. The stability of the model was tested using the Bootstrap resampling method. The individual probability of developing SSI was determined for each patient by using the model. The threshold probability to be used in distinguishing high-risk patients was found 1.2% by ROC analysis. For hospitals with different SSI rates and surveillance sensitivity, the utility of the model has been estimated by various parameters.
Results: Female gender (OR:1.52; 95% CI:1.22-1.88), being over 65 years of age (OR:2.06; 95% CI:1.63-2.62), procedure duration longer than 75th percentile (OR:1.32; 95% CI:1.07-1.63), ASA score over 3 (OR:2.10; 95% CI:1.48-2.99), and surgery performed in a hospital other than a private hospital (p<0.001) were found to be independent risk factors for the development of SSI. When focusing on high-risk patients, as the rate of SSI of a hospital increases, the number of patients that need to be focused on detecting one more SSI decreased, and the number of additional SSIs increased. As the surveillance sensitivity of the hospitals decreases, the new rate obtained differs more from the old rate.
Conclusions: Focusing on high-risk patients identified using the model caused to eliminate approximately half of the patients, thus saving labor and time. Using this model can be particularly beneficial for hospitals with a high SSI burden and low surveillance capacity. The model can be integrated into the national surveillance system so that high-risk patients can be prioritized. Modeling may be considered for the other surgeries.