Precision in Prevention: Tailoring Single-Use Negative Pressure Wound Therapy Utilization Through Artificial Intelligence-Based Surgical Site Complications Risk and Cost Modeling.
Barrett J Larson, Ashley Roakes, Steve Yurick, Nathan A Netravali
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引用次数: 0
Abstract
Background: Surgical site complications (SSCs) are common, yet preventable hospital-acquired conditions. Single-use negative pressure wound therapy (sNPWT) has been shown to be effective in reducing rates of these complications. In the era of value-based care, strategic allocation of sNPWT is needed to optimize both clinical and financial outcomes. Materials and Methods: We conducted a retrospective analysis using data from the Premier Healthcare Database (2017-2021) for 10 representative open procedures in orthopedic, abdominal, cardiovascular, cesarean delivery, and breast surgery. After separating data into training and validation sets, various machine learning algorithms were used to develop pre-operative SSC risk prediction models. Model performance was assessed using standard metrics and predictors of SSCs were identified through feature importance evaluation. Highest-performing models were used to simulate the cost-effectiveness of sNPWT at both the patient and population level. Results: The prediction models demonstrated good performance, with an average area under the curve of 76%. Prominent predictors across subspecialities included age, obesity, and the level of procedure urgency. Prediction models enabled a simulation analysis to assess the population-level cost-effectiveness of sNPWT, incorporating patient and surgery-specific factors, along with the established efficacy of sNPWT for each surgical procedure. The simulation models uncovered significant variability in sNPWT's cost-effectiveness across different procedural categories. Conclusions: This study demonstrates that machine learning models can effectively predict a patient's risk of SSC and guide strategic utilization of sNPWT. This data-driven approach allows for optimization of clinical and financial outcomes by strategically allocating sNPWT based on personalized risk assessments.
期刊介绍:
Surgical Infections provides comprehensive and authoritative information on the biology, prevention, and management of post-operative infections. Original articles cover the latest advancements, new therapeutic management strategies, and translational research that is being applied to improve clinical outcomes and successfully treat post-operative infections.
Surgical Infections coverage includes:
-Peritonitis and intra-abdominal infections-
Surgical site infections-
Pneumonia and other nosocomial infections-
Cellular and humoral immunity-
Biology of the host response-
Organ dysfunction syndromes-
Antibiotic use-
Resistant and opportunistic pathogens-
Epidemiology and prevention-
The operating room environment-
Diagnostic studies