Capturing and Improving Case Charge Accuracy in Robotic Surgery Programs

William D. Gerull, Andrew Pierce, Jessica Mody, Michael M. Awad, Jackie Martin, Jason R. Wellen

Research output: Contribution to journalArticlepeer-review


The robotic platform offers many benefits to patients and surgeons; however, incorporating this new surgical tool has also introduced challenges in intraoperative documentation accuracy. In 2019, we began to investigate our institution's robotic intraoperative supply documentation accuracy. We identified a 60% case error rate between the robotic items logged by the operating room staff in the electronic medical record and the true robotic items used for a case as logged on the Intuitive platform. This can be a widespread and unrecognized problem for other organizations as well. We then addressed this problem through patient safety and quality improvement-based interventions including error notification to operating room personnel, a barcode scanning system, peer-to-peer education, improving robotic item descriptions, and procedure receipt messaging. These interventions helped us decrease our institution's case error rate from 60% to 16.9% during the past 2 years, which generated a cumulative 2.1% net increase in our billed robotic items, through the addition and/or subtraction of robotic items from each case. Through our multiple interventions, we have created a robust, flexible, and efficient item-capturing system for robotic surgery cases.

Original languageEnglish
Pages (from-to)964-968
Number of pages5
JournalJournal of the American College of Surgeons
Issue number5
StatePublished - May 1 2022


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