MétaCan
Menu
Back to cohort
Record W2590539614 · doi:10.1111/trf.14033

An international survey on the role of the hospital transfusion committee

2017· article· en· W2590539614 on OpenAlexaff
Mark H. Yazer, Miquel Lozano, Mark Fung, José Mauro Kutner, Michael Murphy, Torunn Oveland Apelseth, Ryszard Pogłód, Kathleen Selleng, Alan Tinmouth, Silvano Wendel, Vered Yahalom

Bibliographic record

VenueTransfusion · 2017
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineExcellenceTransfusion medicineFamily medicineBlood transfusionQuality (philosophy)Quality assuranceEmergency medicineMedical emergencySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Hospital transfusion committees (HTCs) can oversee all aspects of transfusion practice at a hospital. This survey sought to identify which quality variables were being reported at HTCs around the world. STUDY DESIGN AND METHODS: A working party composed of members of the Biomedical Excellence for Safer Transfusion (BEST) collaborative developed a survey of quality variables that could be potentially presented at HTC meetings. The survey was electronically sent to all BEST members who were encouraged to complete it if they were active on an HTC and to send it to other colleagues with similar experience. An expert panel was convened to determine which quality variables are the most important for review at HTC meetings. RESULTS: There were 121 respondents; the majority were from Europe (52%), Asia (19%), or North America (19%). Most respondents (68%) were at university hospitals. Of the 117 (97%) respondents with an HTC, the committee most often met quarterly (42%) and reviewed transfusion reactions (79%) and risk management-reported events (52%). The HTCs most commonly included transfusion medicine physicians, anesthesiologists, and other physicians who regularly transfuse blood products. Some of the most commonly reported quality variables included number of blood products transfused, wasted, and expired and the number of improperly labeled specimens. The expert panel analysis revealed that some variables that were deemed important were not being frequently reported at HTCs. CONCLUSION: There is variability in the variables being reported at HTCs around the world with some important variables not frequently reported.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.272
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueTransfusionSame topicBlood transfusion and managementFrench-language works237,207