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  • September 2009
  • Article
  • Plastic and Reconstructive Surgery

A Detailed Analysis of the Reduction Mammaplasty Learning Curve: A Statistical Process Model for Approaching Surgical Performance Improvement

By: Matthew Carty MD, Rodney Chan, Robert S. Huckman, Daniel C. Snow and Dennis Orgill
  • Format:Print
  • | Pages:9
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Abstract

Background: The increased focus on quality and efficiency improvement within academic surgery has met with variable success among plastic surgeons. Traditional surgical performance metrics, such as morbidity and mortality, are insufficient to improve the majority of today's plastic surgical procedures. In-process analyses that allow rapid feedback to the surgeon based on surrogate markers may provide a powerful method for quality improvement.

Methods: The authors reviewed performance data from all bilateral reduction mammaplasties performed at their institution by eight surgeons between 1995 and 2007. Multiple linear regression analyses were conducted to determine the relative impact of key factors on operative time. Explanatory learning curve models were generated, and complication data were analyzed to elucidate clinical outcomes and trends.

Results: A total of 1,068 procedures were analyzed. The mean operative time for bilateral reduction mammaplasty was 134 ± 34 minutes, with a mean operative experience of 11 ± 4.7 years and total resection volume of 1,680 ± 930 g. Multiple linear regression analyses showed that operative time (R = 0.57) was most closely related to surgeon experience and resection volume. The complication rate diminished in a logarithmic fashion with increasing surgeon experience and in a linear fashion with declining operative time.

Conclusions: The results of this study suggest a three-phase learning curve in which complication rates, variance in operative time, and operative time all decrease with surgeon experience. In-process statistical analyses may represent the beginning of a new paradigm in academic surgical quality and efficiency improvement in low-risk surgical procedures.

Keywords

Experience and Expertise; Health Care and Treatment; Medical Specialties; Outcome or Result; Performance Efficiency; Performance Improvement

Citation

Carty, Matthew, MD, Rodney Chan, Robert S. Huckman, Daniel C. Snow, and Dennis Orgill. "A Detailed Analysis of the Reduction Mammaplasty Learning Curve: A Statistical Process Model for Approaching Surgical Performance Improvement." Plastic and Reconstructive Surgery 124, no. 3 (September 2009): 706–714.
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About The Author

Robert S. Huckman

Technology and Operations Management
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    • February 2023
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    How Will Amazon Approach U.S. Primary Care?

    By: Robert S. Huckman and Bradley Staats
More from the Authors
  • The Brigham and Women’s Hospital Innovation Hub: Driving Internal Innovation By: Ariel Dora Stern, Robert S. Huckman and Sarah Mehta
  • Investigating the Association Between Telemedicine Use and Timely Follow-Up Care After Acute Cardiovascular Hospital Encounters By: Mitchell Tang, A Jay Holmgren, Erin E. McElrath, Ankeet S. Bhatt, Anubodh S. Varshney, Simin Gharib Lee, Muthiah Vaduganathan, Dale S. Adler and Robert S. Huckman
  • How Will Amazon Approach U.S. Primary Care? By: Robert S. Huckman and Bradley Staats
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