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Assessing Equality of Touch to Guide Targeted Implementation of Post-induction Surface Disinfection Cleaning and
Randy W Loftus1, Franklin Dexter2, Matthew D Koff3
1From the Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota.
Background:
Improved cleaning in the anesthesia workspace is important for surgical site infection prevention. We sought to identify high-priority cleaning targets to guide post-induction surface disinfection and use of a triangular ultraviolet-C (UV-C) configuration involving placement of one emitter at the head and one on each side of the surgical bed.
Methods:
The 20 sites most frequently touched by anesthesia practitioners, previously identified via video-based workflow analysis, were filtered to remove disposable (eg, stopcocks) and transient (eg, the patient bed) sites, leaving durable cleaning targets amenable to repeated surface disinfection and UV-C irradiation within and/or between cases. Inequality in the distribution of cleaning target touches was quantified using the Gini coefficient, and uncertainty was estimated using bootstrap resampling (10,000 iterations). We then assessed residual contamination after standard terminal cleaning across three operating rooms and 171 sites to evaluate the difficulty of cleaning high-touch surfaces and the efficacy of UV-C disinfection. Simulations using medical devices composed of materials representative of cleaning targets contaminated with high-level Clostridium difficile were conducted to evaluate generalizability to more resistant pathogens.
Results:
There were 13 of 20 frequently touched sites that were considered durable cleaning targets. Touches were relatively equal among the 13 cleaning targets (Gini coefficient 0.16, 95% confidence interval [CI], 0.12-0.20). Cleaning targets included components of the anesthesia cart (first and second drawer handles); anesthesia machine (reservoir bag, circuit ventilator control, oxygen dial, vaporizer dial, adjustable pressure-limiting valve), monitoring equipment (screen buttons/knob, electrocardiogram leads); and room infrastructure (intravenous pole, operating room table and chair). Residual contamination after cleaning was identified at 4% (7/171) of sites, mostly (6/7) within the anesthesia workspace, involving the anesthesia cart (N = 2), machine (N = 3), and monitor (N = 1). Only one site outside of the anesthesia workspace, the circulating nurse's mouse, had residual contamination. Triangular UV-C reduced mean (standard deviation [SD]) colony-forming units (CFU) from 60.47 (542.22) to 0.12 (1.08), achieving a 2.7-log reduction. Simulation with high-level C. difficile contamination demonstrated ≥3-log reductions on surfaces representative of high-touch sites, confirming applicability to resistant pathogens.
Conclusions:
Thirteen durable cleaning targets in the anesthesia workspace are largely equivalent in terms of risk of touch. They are amenable to UV-C augmentation of surface disinfection in the real-world clinical environment. These findings can guide targeted post-induction cleaning and use of triangular UV-C, particularly for surfaces with substantial contamination or resistant pathogens.
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