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How acceptable is rapid whole genome sequencing for infectious disease management in hospitals? Perspectives of those involved in managing nosocomial SARS-CoV-2 (preprint)
medrxiv; 2022.
Preprint
in English
| medRxiv | ID: ppzbmed-10.1101.2022.06.15.22276423
ABSTRACT
Structured summary Background Whole genome sequencing (WGS) for managing healthcare associated infections (HCAIs) has developed considerably through experiences with SARS-CoV-2. We interviewed various healthcare professionals (HCPs) with direct experience of using WGS in hospitals (within the COG-UK Hospital Onset COVID-19 Infection (HOCI) study) to explore its acceptability and future use. Method An exploratory, cross-sectional, qualitative design employed semi-structured interviews with 39 diverse HCPs between December 2020 and June 2021. Participants were recruited from five sites within the larger clinical study of a novel genome sequencing reporting tool for SARS-CoV-2 (the HOCI study). All had experience, in their diverse roles, of using sequencing data to manage nosocomial SARS-CoV-2 infection. Deductive and inductive thematic analysis identified themes exploring aspects of the acceptability of sequencing. Findings The analysis highlighted the overall acceptability of rapid WGS for infectious disease using SARS-CoV-2 as a case study. Diverse professionals were largely very positive about its future use and believed that it could become a valuable and routine tool for managing HCAIs. We identified three key themes ‘1) ‘Proof of concept achieved’; 2) ‘Novel insights and implications’; and 3) ‘Challenges and demands’. Conclusion Our qualitative analysis, drawn from five diverse hospitals, shows the broad acceptability of rapid sequencing and its potential. Participants believed it could and should become an everyday technology capable of being embedded within typical hospital processes and systems. However, its future integration into existing healthcare systems will not be without challenges (e.g., resource, multi-level change) warranting further mixed methods research.
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Collection:
Preprints
Database:
medRxiv
Language:
English
Year:
2022
Document Type:
Preprint
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