Sustainability and cost-avoidance of reduced inappropriate red cell transfusion at community hospitals in niagara region: A follow-up analysis on a quality improvement initiative.
Notice bibliographique
Résumé
Abstract Introduction: Red blood cell transfusions (RBC) are a vital component of medical treatment in Canada. Yet, RBC units are expensive resources with clinical risks that are often inappropriately used, incurring unnecessary costs to the healthcare system. There is paucity of scientific information surrounding the economic implications and potential cost savings from implementing quality improvement programs aimed at reducing the inappropriate RBC utilization. We aim to share the sustainability of a previous quality improvement project promoting appropriate RBC utilization, and review the cost avoidance/saving gained from this initiative. Methods: An initial Quality Improvement project aimed at reducing inappropriate RBC transfusions was conducted through various interventions (i.e., technologist-led screening). We will be providing an overview of the original QIP as well as updated sustainability data until Sept 2024.This study applied an activity-based costing model to estimate cost avoidance based on the Choosing Wisely Canada guidelines for RBC utilization in three acute care facilities within the Niagara Health System. A secondary data analysis was conducted on RBC utilization from May 2018 to September 2024. The unit cost of an RBC transfusion was derived from a previous study and corroborated with Canadian Blood Services, factoring in all direct costs and overhead functions (approximately $1500 per transfusion). Descriptive and forecasting statistics were used to estimate cost avoidance and analyze time trends in RBC inappropriate utilization, comparing pre- and post-intervention periods. Results: Following intervention, adherence to guidelines of pre-transfusion hemoglobin (Hb) of 80 g/L or less and single unit rose from 85% and 54% to 90% and 71%, respectively. Appropriate rates of RBC transfusion were sustained for over 2 years since the intervention was implemented. We observed a significant decrease in total RBC utilization when comparing the pre-intervention period (2018-2021) to the post-intervention period (2022-2024). The total financial spending was $11,481,000 in the pre-intervention, which dropped to $6,429,000, resulting in a $5,052,000 cost avoidance in the post-intervention. This represents a 56% reduction in RBC utilization and 44% cost avoidance, suggesting substantial savings after adjusting for expected RBC units. Some variation was noted between the three sites, indicating the differential effectiveness of the quality improvement program across sites. Interestingly, local data on transfusion adverse reactions did not change with the implementation of this QIP. Discussion: Previously, there have been few validated interventions yielding significant improvement in appropriate RBC usage. This study demonstrates a reduction in inappropriate RBC utilization aligning with national accreditation benchmarks, translating into substantial savings for the healthcare system. Moreover, our intervention demonstrates that appropriate RBC usage and cost avoidance can be sustained, likely related to continued technologist-led screening. We suspect that the lack of reduction in transfusion adverse reactions concurrent with this project is related to the underreporting of these events. Further research is needed to investigate site-specific variations, focusing on facilitators and barriers to implementation across hospitals within the Niagara region.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».