Implementation of Preoperative Optimization Algorithms to Minimize Elective Surgery Cancellations

Abstract

Problem & Purpose: Between January of 2019 and May of 2021 at a community-based hospital in the mid-Atlantic region nearly 400 surgical procedures were cancelled on the intended day of surgery, resulting in significant loss of revenue. This quality improvement (QI) project intended to reduce the incidence of preventable same day surgical cancellation (SDSC) due to either incomplete or inadequate patient testing by incorporating a standardized comorbidity screening algorithm tool (CSAT) into the clinical workflow for nursing staff at the hospital’s pre-anesthesia testing (PAT) center. Methods: The most up-to-date PAT guidelines from numerous professional societies were consolidated into a single-page CSAT. PAT center clinical staff received a copy of the CSAT and completed an educational training session prior to implementation of the practice change. CSAT compliance data was collected during weekly PAT center site visits. The SDSC rate was tracked both immediately prior to and for 15 weeks following the practice change. Results: The CSAT was successfully utilized during 22% of PAT center patient encounters. The median 12% incidence of preventable SDSCs attributable to either incomplete or inadequate PAT remained unchanged. Run chart analyses demonstrated common-cause random variation. Conclusions: Throughout the CSAT implementation period the incidence of preventable SDSCs attributable to PAT remained unchanged. Unprecedented COVID-19 pandemic related infection control restrictions and staffing policy changes likely contributed to sub-optimal CSAT compliance rates. Incorporating the CSAT into the electronic medical record and standardizing its utilization during every patient encounter through the PAT center is perhaps the best way to ensure the long-term sustainability of this QI intervention.