Prospective Outcome Based Robotic Colorectal Surgery Registry
Summary: We seek to develop a robotic colorectal surgery specific data registry with collection of core variables. This data, collected by attending surgeons will include preoperative, intraoperative, and postoperative variables including those specific to Robotic surgery.
Description of Problem/Background: Prospective, outcome based database collection and analysis is scarce if not lacking in robotic colorectal surgery. While there have been robotic publications on robotic colorectal cases, most focus on rectal operations and/or are plagued by faulty design and biases. Most regional and national databases are collected and maintained by nurses or administrative staff interfering with the accuracy of the data and credence of its value.
Purpose, Hypothesis, and Methods of Research: Given the ever growing number of robotic colorectal cases performed, we feel that there is a need for prospectively gathered, surgeon centered, thorough registry focusing on wide array of robotic colorectal operations. We look to gather information about patient demographics, preoperative comorbidities, intraoperative variables, and anesthesia related factors. In addition, we included several colorectal specific factors such as steroid and immunomodulator use in patients with inflammatory bowel disease, type of bowel preparation, type and method of anastomosis and formation of stoma. Robot specific variables will be of focus. These will include: generation of robot, number of arms used, robotic time, use of vessel sealer or stapler, use of I Spy, intracorporial versus extracorporeal anastomosis, conversion to laparoscopic or open operation, etc. Postoperative complications will be categorized as major surgical, minor surgical, major medical, and minor medical. All data will be collected by attending surgeons and analyzed prospectively. Data collected will be reviewed and analyzed to determine which preoperative or intraoperative events/factors are contributors to development of postoperative complications. This will allow us to optimize or eliminate those factors in order to improve outcome. The data will also help to shed light on the benefits of robotic surgery in these cases, demonstrate length of learning curve and ultimately result in efficient robotic colorectal surgery with maximal reduction in complications.