Clean Cut (Adaptive, Multimodal Surgical Infection Prevention Programme) For Low-Resource Settings: A Prospective Quality Improvement Study

Background Clean Cut is an adaptive, multimodal programme to identify improvement opportunities and safety changes in surgery by enhancing outcomes surveillance, closing gaps in surgical infection prevention standards, and strengthening underlying processes of care. Surgical-site infections (SSIs) are common in low-income countries, so this study assessed a simple intervention to improve perioperative infection prevention practices in one. Methods Clean Cut was implemented in five hospitals in Ethiopia from August 2016 to October 2018. Compliance data were collected from the operating room focused on six key perioperative infection prevention standards. Process-mapping exercises were employed to understand barriers to compliance and identify locally driven improvement opportunities. Thirty-day outcomes were recorded on patients for whom intraoperative compliance information had been collected. Results Compliance data were collected from 2213 operations (374 at baseline and 1839 following process improvements) in 2202 patients. Follow-up was completed in 2159 patients (98 center dot 0 per cent). At baseline, perioperative teams complied with a mean of only 2 center dot 9 of the six critical perioperative infection prevention standards; following process improvement changes, compliance rose to a mean of 4 center dot 5 (P < 0 center dot 001). The relative risk of surgical infections after Clean Cut implementation was 0 center dot 65 (95 per cent c.i. 0 center dot 43 to 0 center dot 99;P = 0 center dot 043). Improved compliance with standards reduced the risk of postoperative infection by 46 per cent (relative risk 0 center dot 54, 95 per cent c.i. 0 center dot 30 to 0 center dot 97, for adherence score 3-6versus0-2;P = 0 center dot 038). Conclusion The Clean Cut programme improved infection prevention standards to reduce SSI without infrastructure expenses or resource investments.