Operating room blood delivery turnaround time: a College of American Pathologists Q-Probe Study of 12647 units of blood components in 466 institutions.
Notice bibliographique
Résumé
Objectives To determine the normative distribution of time elapsed for blood bank personnel to fill nonscheduled operating room (OR) blood component orders in hospital communities throughout the United States, and to examine hospital blood bank practices associated with faster blood component delivery times. Design Participants in the College of American Pathologists Q-Probes laboratory quality improvement program collected data prospectively on the times elapsed for blood bank personnel to fill nonscheduled emergent orders from hospital ORs for red blood cell (RBC) products, fresh frozen plasma (FFP), and platelets (PLTs). Participants also completed questionnaires describing their hospitals' and blood banks' laboratory and transfusion practices. Setting and participants Four hundred sixty-six public and private institutions located in 48 states in the United States (n = 444), Canada (n = 9), Australia (n = 8), the United Kingdom (n = 4), and Spain (n = 1). Main outcome measures The median time elapsed between requests for blood components by OR personnel and the retrieval of those components by blood component transport personnel, and the median time elapsed between requests for blood components by OR personnel and the arrival of those components in ORs. Results Participants submitted data on 12 647 units of RBCs, FFP, and PLTs. The median aggregate request-to-retrieval turnaround times (TATs) for RBCs, FFP, and PLTs ranged from 30 to 35 minutes, and the median aggregate request-to-arrival TATs for RBCs, FFP, and PLTs ranged from 33 to 39 minutes. Most of the TAT was consumed by events occurring prior to, rather than after release of components from blood banks. Shorter prerelease TATs were associated with having surgical schedules that listed patients' names and procedures available to blood bank personnel prior to surgeries, and having adequate clotted specimens in the blood bank and completed type-and-screen procedures performed before requests for blood components were submitted to blood banks. Among the fastest-performing 10% of participants (90th percentile and above), request-to-retrieval TATs ranged from 12 to 24 minutes for the 3 blood components, whereas among the slowest-performing 10% of participants (10th percentile and below), request-to-retrieval TATs ranged from 63 to 115 minutes for the 3 components. Median TATs ranged from 33 to 37 minutes for the 3 components. Institutions with TATs in the fastest-performing 25th percentile more frequently stored cross-matched RBCs in the OR daily, stocked PLTs for unexpected surgical use, stored PLTs in or near the OR, and had laboratory rather than nonlaboratory personnel deliver components to the OR than did those institutions with TATs in the slowest-performing 25th percentile. Conclusions Hospital blood bank personnel can deliver blood components to the OR in slightly longer than 30 minutes, measured from the time that those units are requested by OR personnel. Practices aimed at saving time before components are released from blood banks will be more efficient in reducing overall TAT than those practices aimed at saving time after components are released from blood banks. Specific practices associated with shorter blood delivery TATs included providing blood bank personnel with access to the names of surgical patients potentially requiring blood components, having pretransfusion testing completed on those patients prior to surgery, having ample blood products on hand, and having laboratory personnel control blood product delivery.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,003 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».