Redesigning a More Actionable, Service Line Specific, Surgical Performance Dashboard for an Academic Referral Hospital by Adding Severity of Post-Operative Complications

The Institute of Medicine’s To Err is Human Report states that “98 000 people die in a given year frommedical errors that occur in hospitals. ” This report focused on systemlevel errors rather than addressing individual behavior. Their recommendations included establishing a national focus on errors, initiating voluntary reporting systems, and instituting performance and safety standards. From these initiatives, the Agency for Healthcare Research and Quality, National Quality Form, and other professional groups such as The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) were born. NSQIP is a registry that provides a “data driven, riskadjusted, outcomes-based program to measure and improve the quality of surgical care. ” This voluntary database currently includes over 800 U.S.-based hospitals. This benchmarking allows for standardized comparisons between different organizations. In theory, by identifying high performing organizations, best practices can be recognized and disseminated to improve overall outcomes at an organizational and national level. Utilizing reports from NSQIP, hospitals can undertake quality improvement (QI) projects in areas of underperformance. Traditionally, when focusing on QI, a variation analysis is used amongst institutions, which can lead to top quartile institutions becoming complacent despite having opportunities to improve surgical outcomes. Quality measures from NSQIP are available as a dashboard for institutions to benchmark against one another. However, this data does not account for the severity of complications as the current dashboards give equal weight to each complication irrespective of severity (eg, superficial surgical site infection (SSI) is treated the same as organ/ space SSI). Additionally, these dashboards do not allow for rapid connections in data such as the concept of failure to rescue, where one complication progresses to another. Also, NSQIP does not provide a robust means of visualizing by service line. For example, the dashboard provides the number of SSIs by different subcategories (ie, specific procedure and team) and benchmark site infections against other peer institutions nationally but does not attribute them to institution-specific service lines. Consequently, these weaknesses can result in surgeons lacking an optimized dashboard that promotes action and allows them to institute change based on the severity or sequela of complications to improve care delivered. TheClavien-Dindo classification scheme iswell-documented and utilized in some areas of surgical literature such as Urology. While surgical outcomes are currently based on morbidity and mortality, it is difficult to establish causation between them. One strength of the Clavien-Dindo classification scheme is by utilizing the treatment used to treat a complication, it can be linked to severity. In surgical literature, a well-validated and universally applied schema for rating complications is lacking. Thus, it becomes difficult to understand the impact of various complications, visualize trends, compare different institutions, and even evaluate different publications. Therefore, a more comprehensive dashboard should integrate severity and complication sequela and then be organized by service line to allow providers to optimally address quality. The first goal is to make a clinically actionable dashboard (two-dimensional) by utilizing the Clavien-Dindo classification scheme by service line. The next goal is to determine focus areas for each service line using benchmarks, to make the dashboard more actionable. By providing this information to clinicians, they will then be able to focus on best practices to implement to address each deficient area. We hypothesized that implementing a standardize scale such as Clavien-Dindo would improve