379 Improving Flow: A Quality Improvement Project on The Processing of Vascular Surgical Microbiology Samples. (12th October 2021)

• Record Type: Journal Article
• Authors: Wang, L; Gilbert, J; Ireland, D; Samarasinghe, D; Sritharan, G
• Is Part Of: British journal of surgery. Volume 108:Supplement 6(2021)
• Publication Date: 2021-10-12
• Subjects: Surgery -- Periodicals; 617.005
• DOI: 10.1093/bjs/znab259.044
• Languages: English
• ISSNs: 0007-1323

Abstract

Abstract: Aim: Tissue samples taken during vascular surgical operations are commonly sent for microbiological analysis, owing to the relatively high incidence and serious consequences of infection in these cases. Delays in obtaining results from these samples can hinder clinical management, leading to prolonged inpatient stay and adverse clinical outcomes. The aim of this audit was to identify causes for delay in obtaining microbiology results and to improve the service. Method: A closed loop quality improvement project performed at a tertiary vascular centre in London. We initially identified all tissue microbiology samples sent from vascular surgical operations performed during April 2019 and record the time when samples reach microbiology laboratory and the time when results were made available. Re-audit data was collected in November 2019. Results: Initial audit showed that on average, results were available for clinicians 9.1 days after the sample was taken and 7.3 days after the sample had reached the laboratory. Samples required an average of 44 hours to transit to the laboratory and notably there is delay if surgery is performed on Friday (71 hours). Additionally, one sample was missing. Following utilization of the urgent sample pathway and raising awareness amongst staff, re-audit data showed significant reduction in average time of transit (33 hours) with much reduced transit time on Friday (36 hours). Results were available 7.7 days following sample date, compared to 9.1 days before. Conclusions: Utilization of existing pathway and staff training can reduce delays in microbiology sample processing. However, further analysis is necessary to ensure sustained improvement.