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Record W4415732300 · doi:10.1136/bmjoq-2025-003551

Sustainability and cost avoidance of reduced inappropriate red blood cell transfusion at community hospitals in Niagara Region: a follow-up analysis on a quality improvement initiative

2025· article· en· W4415732300 on OpenAlexaffabout
Alexis Fang, Asif Raza Khowaja, Mohammad Refaei

Bibliographic record

VenueBMJ Open Quality · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsBrock UniversityMcMaster University
Fundersnot available
KeywordsSustainabilityQuality (philosophy)Quality managementBlood transfusionRed blood cellRed Blood Cell Transfusion

Abstract

fetched live from OpenAlex

BACKGROUND: Inappropriate packed red blood cell (pRBC) transfusions increase patient risk and healthcare costs. Initial audits at Niagara Health (Ontario, Canada) revealed only 85% and 54% compliance with Choosing Wisely Canada guidelines for pre-transfusion hemoglobin (≤80 g/L) and single-unit transfusion, respectively. METHODS: We conducted a nonrandomized, interrupted time-series Quality Improvement Project (QIP) using the Model for Improvement. Interventions included technologist-led prospective screening of pRBC orders, policy updates, and educational campaigns. Outcome measures were rates of inappropriate transfusions based on hemoglobin and single-unit criteria; balancing measures included transfusion-related adverse events. Sustainability was assessed using Statistical Process Control charts. Cost analysis estimated savings using an activity-based cost of $C1500 per pRBC unit. RESULTS: Initial implementation improved compliance to 90% (pre-transfusion hemoglobin) and 71% (single-unit) within three months. Extended analysis (2021-2024) demonstrated sustained rates of 90% and 77%, respectively. At the St. Catharines Site, monthly median transfusions decreased from 273 to 173 units, yielding a 56% reduction in RBC utilization and 44% cost savings amounting to $C5052000. CONCLUSIONS: Technologist-led screening achieved sustained improvements in transfusion appropriateness, leading to substantial cost savings. Variability across sites underscores the need for further research on contextual factors influencing future QIP success.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.392
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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