Applying a logistic regression-clustering joint model to analyze the causes of prolonged pre-analytic turnaround time for urine culture testing in hospital wards
The joint model effectively identified workflow bottlenecks. Targeted interventions (dynamic transport scheduling, standardized training, and IoT alert systems) significantly optimized pre-TAT and specimen quality, providing a framework for improving clinical laboratory processes.
Authors
- Huan Ye (ORCID: https://orcid.org/0009-0004-3516-1602)
- Jian Zhang (ORCID: https://orcid.org/0000-0002-6558-791X)
- Yuan Li (ORCID: https://orcid.org/0000-0003-1418-5715)
- Shuangshuang Lv
Institutions
- Wenzhou Medical University (CN)
- Dongyang People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2025-06-30
- DOI
- https://doi.org/10.3389/fdgth.2025.1603314
- Primary Topic
- Clinical Laboratory Practices and Quality Control
- Type
- article
- Field-Weighted Citation Impact
- 0.00