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Record W4409614007 · doi:10.1136/bmjoq-2024-003149

Scaling up thrombectomy care in transitioning health systems: a qualitative study of stroke centres in Canada

2025· article· en· W4409614007 on OpenAlexaffabout
Tanaporn Jaroenngarmsamer, Borwornsom Leerapan, Rosalie McDonough, Vivek Bodani, Syed Uzair Ahmed, Arshia Sehgal, Alexandre Y. Poppe, Mayank Goyal, Timo Krings, Sirintara Singhara Na Ayudhaya

Bibliographic record

VenueBMJ Open Quality · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsWomen's College HospitalUniversity of TorontoToronto Western HospitalUniversity of CalgaryCentre Hospitalier de l’Université de MontréalUniversité de MontréalUniversity of Saskatchewan
Fundersnot available
KeywordsThematic analysisOutreachMedicineMultidisciplinary approachService delivery frameworkNursingWorkflowHealth careProcess managementThrombolysisQualitative researchQuality managementBusinessService (business)MarketingPolitical scienceSociology

Abstract

fetched live from OpenAlex

INTRODUCTION: Endovascular thrombectomy has shown significant benefits for patients with large-vessel ischaemic stroke. However, many countries face challenges establishing effective thrombectomy delivery systems, even when thrombolysis services are already in place. Moreover, there is limited research on implementing thrombectomy care delivery, particularly for scale-ups in low- and middle-income countries. This study identifies the key drivers of enhancing thrombectomy delivery systems in three Canadian regions and provides lessons for health systems in transition. METHODS: A qualitative research design with a phenomenological approach was employed. From January to December 2022, at three comprehensive ischaemic stroke centres in Canada, we involved non-participant observation and in-depth interviews with 91 key informants, including care providers and administrators engaged in large-vessel stroke care. Guided by the Behaviour Change Wheel and Theoretical Domains Framework, the data were transcribed and analysed using thematic content analysis. RESULTS: Three critical themes emerged. First, establishing a cohesive, goal-oriented, multidisciplinary patient care team with an egalitarian culture is vital. Second, integrating specific feedback data is essential for continuous quality improvement and for optimising workflow through collective leadership. Lastly, even with existing thrombolytic services, centralised regional planning and outreach to local thrombectomy implementers is necessary. Development must occur at stroke centres and their associated peripheral hospitals to build effective thrombectomy care delivery systems. CONCLUSIONS: Enhancing thrombectomy care delivery systems requires a stepwise approach: first, establishing multidisciplinary teams at the micro-level; next, fostering collective leadership for continuous quality improvement at the meso-level and finally, coordinating regional outreach and centralised planning at the macro-level. The Canadian experience highlights the importance of addressing these interconnected levels and underscores the critical role of central planning and collaboration between policymakers and care providers. These strategies offer a structured pathway for improving stroke care globally, particularly in transitioning health systems.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.073
GPT teacher head0.469
Teacher spread0.395 · 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 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

Citations2
Published2025
Admission routes2
Has abstractyes

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