To evaluate practice change after initiation of a robotic surgery program using a clinical algorithm to determine the optimal surgical approach to benign hysterectomy.
A retrospective postrobot cohort of benign hysterectomies (2009–2013) was identified and the expected surgical route was determined from an algorithm using vaginal access and uterine size as decision tree branches. We excluded the laparoscopic hysterectomy route. A prerobot cohort (2004–2005) was used to evaluate a practice change after the addition of robotic technology (2007). Costs were estimated.
Cohorts were similar in regard to uterine size, vaginal parity, and prior laparotomy history. In the prerobot cohort (n=473), 320 hysterectomies (67.7%) were performed vaginally and 153 (32.3%) through laparotomy with 15.1% (46/305) performed abdominally when the algorithm specified vaginal hysterectomy. In the postrobot cohort (n=1,198), 672 hysterectomies (56.1%) were vaginal; 390 (32.6%) robot-assisted; and 136 (11.4%) abdominal. Of 743 procedures, 38 (5.1%) involved laparotomy and 154 (20.7%) involved robotic technique when a vaginal approach was expected. Robotic hysterectomies had longer operations (141 compared with 59 minutes, P<.001) and higher rates of surgical site infection (4.7% compared with 0.2%, P<.001) and urinary tract infection (8.1% compared with 4.1%, P=.05) but no difference in major complications (P=.27) or readmissions (P=.27) compared with vaginal hysterectomy. Algorithm conformance would have saved an estimated $800,000 in hospital costs over 5 years.
When a decision tree algorithm indicated vaginal hysterectomy as the route of choice, vaginal hysterectomy was associated with shorter operative times, lower infection rate, and lower cost. Vaginal hysterectomy should be the route of choice when feasible.
Supplemental Digital Content is Available in the Text.An algorithm can be used for decision-making in determining the most appropriate route of hysterectomy to optimize patient outcomes and lower health care delivery costs.
Divisions of Gynecologic Surgery, Biomedical Statistics and Informatics, Health Care Policy and Research, Mayo Clinic, Rochester, Minnesota.
Corresponding author: John B. Gebhart, MD, Division of Gynecologic Surgery, Mayo Clinic, 200 First Street SW, Rochester, MN 55905; email: email@example.com.
Supported by Clinical and Translational Science Awards Grant Number UL1 TR000135 from the National Center for Advancing Translational Science. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.
Presented at the annual meeting of the Society of Gynecologic Surgeons, April 10–13, 2016, Palm Springs, California.
Financial Disclosure Dr. Gebhart has served on the advisory board for Astora and received royalties from UpToDate, Inc, and Elsevier BV. The other authors did not report any potential conflicts of interest.
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