Retrospective evaluation of clinical decision support for within-laboratory optimization of SARS-CoV-2 NAAT workflow.

COVID-19 SARS-CoV-2 ask at order entry questions business intelligence clinical decision support computerized provider order entry informatics turnaround time

Journal

Journal of clinical microbiology
ISSN: 1098-660X
Titre abrégé: J Clin Microbiol
Pays: United States
ID NLM: 7505564

Informations de publication

Date de publication:
22 Dec 2023
Historique:
medline: 22 12 2023
pubmed: 22 12 2023
entrez: 22 12 2023
Statut: aheadofprint

Résumé

We describe a novel approach to clinical decision support (CDS) for triaging specimens within the clinical laboratory for severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) nucleic acid amplification tests (NAAT). The use of our CDS tool could help clinical laboratories prioritize and process specimens efficiently, especially during times of high demand. There were significant differences in the turnaround time for specimens differentiated by icons on specimen labels. Further studies are needed to evaluate the impact of our CDS tool on overall laboratory efficiency and patient outcomes.

Identifiants

pubmed: 38132702
doi: 10.1128/jcm.00785-23
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0078523

Auteurs

Thomas J S Durant (TJS)

Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut, USA.

David R Peaper (DR)

Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

Classifications MeSH