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Learning curve or learning loop? A tale of innovation, failure, and redemption in abdominal wall reconstruction
Winnie T. Tong, John L. Clayton, MD, Clara N. Lee, MD, MPP, Eric G. Halvorson, MD, Wayne Overby, MD, Charles S. Hultman, MD, MBA.
University of North Carolina, Chapel Hill, NC, USA.
PURPOSE: Learning curves are characterized by incremental improvement of a process, through repetition and reduction in variability, but can be disrupted with the emergence of new techniques and technologies. Abdominal wall reconstruction continues to evolve, with the introduction of components separation in the 1990s and biologic mesh in the 2000s. As such, attempts at innovation may impact the success of reconstructive outcomes and yield a changing set of complications. The purpose of this paper is to describe the paradigm shift that has occurred in abdominal wall reconstruction over the past ten years, focusing on the incorporation of new methodologies.
We performed a retrospective review of 150 consecutive patients who underwent abdominal wall reconstruction with components separation, for midline hernia defects, from 2000-2010, at an academic medical center. The following data points were collected: age, gender, medical co-morbidities, smoking history, number of previous hernia repairs, body mass index (BMI), albumin and pre-albumin, type of biologic mesh and location of placement (underlay, inlay, overlay), intra-operative blood loss, size of hernia defect, length of stay, length of follow-up, and incidence of postoperative complications, such as hernia recurrence, time to recurrence, seroma, infection, bulge, and reoperation. To identify risk factors for complications, we used Student’s T test, chi-square analysis, and Fisher’s exact test in our initial univariate and bivariate models, followed by a backwards, conditional, stepwise, multivariate logistic regression analysis, utilizing SPSS software. To assess the hypothesis that outcomes were linked to location on a learning curve, we stratified patients into the following periods: early (2000-2003), middle (2004-2006), and late (2007-2010).
From 2000-2010, we performed 150 abdominal wall reconstructions with components separation (mean age 50.4 years, BMI 30.4, size of defect 357 cm2, length of stay 9.6 days, follow-up 2.3 years). Biologic mesh was used in 107 patients in the following locations: overlay (n=28), inlay (n=27), underlay (n=52). Complications occurred in a bimodal distribution and were highest in 2001 (when we introduced biologic mesh into our practice) and 2008 (when we changed our mesh location from underlay to onlay). Risk factors for recurrence of hernia (n=26, 17.3%) were history of smoking (p=0.06), low preoperative pre-albumin (p=0.04), use of underlay mesh (p=0.05), and early portion of the learning curve (p=0.02); recurrence occurred a mean of 273 days after repair, with a standard deviation of 329 days. Risk factors for seroma formation (n=25, 16.7%) were elevated BMI (p=0.001), # of previous hernia repairs (p=0.06), use of overlay mesh (p=0.05), and late portion of the learning curve (p<0.001)). Age, gender, blood loss, size of defect, and length of stay were not associated with incidence of complications.
CONCLUSION: The overall learning curve for a specific procedure, such as abdominal wall reconstruction, can be quite volatile, especially as innovative techniques and new technologies are introduced and incorporated into the surgeon’s practice. This process of outcome improvement is not gradual but is often punctuated by periods of failure and rapid redemption.
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