The Value Proposition for Complex Abdominal Wall Reconstruction: How to Make It Work
Related Experiment Video
Updated: Feb 6, 2026

Procurement for a Vascularized and Reinnervated Abdominal Wall Allotransplantation
Published on: July 18, 2025
Bruce Ramshaw1, Brandie Forman1, Elizabeth Barker1
1From the Department of Surgery, University of Tennessee Medical Center, Graduate School of Medicine; and Department of Mechanical, Aerospace and Biomedical Engineering, Tickle College of Engineering, University of Tennessee.
Background:
The challenge for health care in the 21st century is to understand how to measure and improve value in the context of each patient care process for the entire cycle of care. For patients who undergo an abdominal wall reconstruction, there is a great opportunity to improve value because of the high cost and variability in outcomes for this complex operation.
Methods:
For almost a decade, our hernia team has been applying the principles of systems and data science to actual patient care. Tools from systems and data science applied to patient care include clinical quality improvement and nonlinear analytical methods such as factor analysis. The most important outcome to measure and improve is the value of care provided for the entire cycle of care.
Results:
Many measurement and improvement ideas have been applied to the abdominal wall reconstruction process in our hernia program, including the use of a less costly long-term resorbable mesh, multimodal pain management and enhanced recovery process improvement ideas, and surgical technique improvements that have led to decreased wound complications and the elimination of abdominal wall drains. More recently, the data analysis has shown an opportunity to improve outcomes through a robust prehabilitation program, including cognitive therapy to induce neural rewiring before surgery.
Conclusions:
Improving value for patients who undergo abdominal wall reconstruction and for all patients in our global health care system should be a unifying goal. Understanding and applying systems and data science tools appropriately are necessary to achieve this goal.
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