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Record W4387115130 · doi:10.1111/hae.14878

A national assessment of standards of care for inherited bleeding disorders in Canada

2023· article· en· W4387115130 on OpenAlexaffabout
David Page, S. Crymble, Lawrence Jardine, JoAnn Nilson, Kathy Mulder, Natasha Pardy, Bojan Pirnat, Milena Pirnat, Wendy Quinn, Karen Sims, Marie‐Hélène Thompson, Pam Wilton

Bibliographic record

VenueHaemophilia · 2023
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsSt. Paul's HospitalCentre Hospitalier Universitaire de SherbrookeNewfoundland and Labrador Centre for Applied Health ResearchSt. John’s Health Sciences CentreUniversity of SaskatchewanSt. Michael's HospitalCanadian Hemophilia Society
Fundersnot available
KeywordsMedicineStaffingChecklistPsychosocialHealth careFamily medicineNursingPsychiatry

Abstract

fetched live from OpenAlex

AIM: The Canadian Integrated and Comprehensive Care Standards for Inherited Bleeding Disorders were adopted in June 2020. In early 2023, a self-assessment of each of the 26 Canadian inherited bleeding disorder treatment centre's (IBDTCs) capacity to meet the Standards was conducted. The goal was to validate the standards by assessing appropriateness and adherence. As a result, centres can compare their own practices and capacity against those of all centres, identify barriers to adherence, identify opportunities for remedial actions and use the results locally as evidence for needed resources. METHODS: Healthcare providers (HCPs) in the 26 IBDTCs were provided with a checklist to assess adherence to each of the 66 standards of care. Centre participation was voluntary but strongly encouraged by the healthcare provider and patient associations. RESULTS: All 26 centres completed the self-assessments. Collectively, centres reported meeting 88.8% of the standards. Adherence to each standard ranged from 40% to 100%. Forty-one (41) of the standards were adhered to by 90% or more of the centres, 12 by 80%-89% of the centres and 13 by fewer than 80% of the centres. A report consolidating all the assessments was sent to the 26 centres. CONCLUSION: None of the comments received in the self-assessment reports indicated that a given standard was irrelevant, unrealistic or unnecessary. These data are strong indicators that the standards, as written, are appropriate. The self-assessments, however, reveal alarming deficiencies in staffing levels, notably in physiotherapy, psychosocial support and data entry and data management. These constitute a barrier to comprehensive care for many centres. The findings echo similar conclusions from a previous assessment conducted in 2015.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.882
Threshold uncertainty score0.855

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.007
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.371
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes2
Has abstractyes

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