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Record W4412463053 · doi:10.1016/j.tru.2025.100218

Exploring experiences of patients attending an outpatient thrombosis service in Canada

2025· article· en· W4412463053 on OpenAlexafffundabout
Gabriela Carrillo-Balam, Tiffany Lee, Stephanie Young

Bibliographic record

VenueThrombosis Update · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsNewfoundland and Labrador Centre for Applied Health ResearchMemorial University of Newfoundland
FundersBayer CanadaMitacsSanofi
KeywordsThrombosisService (business)MedicineMedical emergencyFamily medicineBusinessInternal medicineMarketing

Abstract

fetched live from OpenAlex

ABSTRACT Background There is limited information on patients’ experiences that influence their satisfaction and perception of the quality of care received at comprehensive thrombosis and anticoagulation management services. However, in order to provide patient-centred care, patients’ input is fundamental. Therefore, we aimed to explore the views and experiences of people who received care at an Adult Outpatient Thrombosis Service to identify aspects that are valued as well as areas for improvement. Methods This is an analysis of free-text data from an anonymous survey sent to all adult patients who received care from a multidisciplinary Thrombosis Service in Newfoundland and Labrador, Canada between October 2017 and May 2019. Thematic analysis was used to analyze the open-ended free text responses and identify common themes. Findings In total, 40.7% (n=229) of survey respondents (N=563) provided comments to the free-text question. Respondents made more positive comments than negative comments. Four common themes were identified: feeling seen, heard, and cared for; the information received filled the gap and sometimes missed the mark; service organization and follow-up: smooth for some, frustrating for others; and, accessing care: virtual options, travel burden, and waiting. Conclusion This analysis highlights the positive effect of receiving clear information and having a respectful patient-provider relationship on patients’ perceived quality of care. Conversely, the need for alternative consultation-delivery modes, such as virtual care, was identified as an area of opportunity to improve patients’ care experience.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0100.005
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.211
GPT teacher head0.416
Teacher spread0.205 · 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 designQualitative
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 routes3
Has abstractyes

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