Reply to Berlanga et al. (DOI 10.1515/cclm-2014-0420)

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Hospital-acquired anemia is highly prevalent and largely preventable complication of hospitalization, affecting up to 40-74 % of patients and up to 90 % of intensive care units patients. Excessive diagnostic blood loss from routine phlebotomy represents a significant and modifiable contributor, with cumulative blood collection volumes independently associated with increased risk of moderate to severe anemia and subsequent transfusion. This narrative review examines the magnitude, clinical consequences, and systemic drivers of diagnostic blood loss, and positions sample volume management (SVM) as a critical, laboratory-led component of patient blood management. Evidence demonstrates that diagnostic sampling frequently exceeds analytical requirements multiple-fold, resulting not only in avoidable patient harm but also in substantial environmental and economic burden. SVM is presented as a structured, system-level framework encompassing demand management, reduction of per-sample volume, workflow optimization, and improvement of preanalytical quality. Interventions such as reduced-volume blood collection tubes, closed sampling systems, capillary and microsampling techniques, and total laboratory automation have consistently been shown to reduce phlebotomy-related blood loss and transfusion requirements without compromising analytical quality or patient safety. Furthermore, strengthening preanalytical processes and leveraging automation can minimize errors and prevent unnecessary recollection. Despite strong evidence and clear alignment with international standards, implementation remains inconsistent. Immediate, coordinated action is therefore required to embed SVM into routine practice through multidisciplinary collaboration, standardized protocols, continuous monitoring, and sustained change management. Integrating SVM into clinical workflows represents a high-value strategy to improve patient outcomes, enhance sustainability, and advance value-based laboratory medicine.

Abstract: PubMed · Datensatz