Formative evaluation of the development and implementation of the automated surveillance of postoperative infections tool

• Published in: Surgery 2023-10, Vol.174 (4), p.886-892
• Main Authors: Myers, Quintin W.O., Lambert-Kerzner, Anne, Colborn, Kathryn L., Dyas, Adam R., Henderson, William G., Meguid, Robert A.
• Format: Article
• Language: English
• Subjects: Databases, Factual; Fear; Focus Groups; Humans; Postoperative Complications - diagnosis; Postoperative Complications - epidemiology; Postoperative Complications - etiology; Surgeons
• ISSN: 0039-6060; 1532-7361; 1532-7361
• DOI: 10.1016/j.surg.2023.06.023

The gold standard for detecting postoperative complications uses databases like the American College of Surgeons National Surgical Quality Improvement Program, a multi-centered database based on manual chart review. However, their limitations and costs have led many centers to discontinue participation. Novel techniques to detect postoperative complications must be developed and implemented with surgeon involvement, which is paramount to their adoption. We sought to assess surgeons’ opinions of a newly developed postoperative complication detection tool, the Automated Surveillance of Postoperative Infections, within the contextual clinical environment. This was a multi-site qualitative formative evaluation of surgeon perceptions of the Automated Surveillance of Postoperative Infections. We conducted semi-structured interviews and focus groups with surgeons and presented the Automated Surveillance of Postoperative Infections concept. Important domains and constructs, as categorized by Consolidated Framework for Implementation Research, were identified to support the successful adoption and implementation of the Automated Surveillance of Postoperative Infections. Twenty-four surgeons with 10 surgical subspecialties were interviewed. The following 4 main themes were found: (1) perception of the Automated Surveillance of Postoperative Infections tool—to provide important data that can improve and support clinical outcomes; (2) environment for implementation—description of factors to support or impede implementation; (3) adaptability of the Automated Surveillance of Postoperative Infections—to work with the complexity of surgical cases; and (4) the Automated Surveillance of Postoperative Infections report format and details. We successfully captured the perspectives and suggestions of surgeons to improve the Automated Surveillance of Postoperative Infections and potential barriers during the initial development phase. Barriers included fear of punitive action from reports and complex surgical cases. Facilitators identified were the need to improve clinical outcomes and organizational support. The results of this formative evaluation will be used to further develop Automated Surveillance of Postoperative Infections, starting with a prototype, the Automated Surveillance of Postoperative Infections 1.0.