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Record W4280495796 · doi:10.1136/bmjopen-2021-058950

Facilitators and barriers to the implementation of the Primary Care Asthma Paediatric Pathway: a qualitative analysis

2022· article· en· W4280495796 on OpenAlexafffundabout
Heather Sharpe, Melissa L. Potestio, Andrew Cave, David W. Johnson, Shannon D. Scott

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryUniversity of Alberta
FundersAlberta Innovates
KeywordsMedicinePrimary careQualitative researchAsthmaFamily medicinePublic healthNursingImmunology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this qualitative study was to use a theory-based approach to understand the facilitators and barriers that impacted the implementation of the Primary Care Asthma Paediatric Pathway. DESIGN: Qualitative semistructured focus groups following a randomised cluster-controlled design. SETTING: 22 primary care practices in Alberta, Canada. PARTICIPANTS: 37 healthcare providers participated in four focus groups to discuss the barriers and facilitators of pathway implementation. INTERVENTION: An electronic medical record (EMR) based paediatric asthma pathway, online learning modules, in-person training for allied health teams in asthma education, and a clinical dashboard for patient management. MAIN OUTCOME MEASURES: Our qualitative findings are organised into three themes using the core constructs of the normalisation process theory: (1) Facilitators of implementation, (2) Barriers to implementation, and (3) Proposed mitigation strategies. RESULTS: Participants were positive about the pathway, and felt it served as a reminder of paediatric guideline-based asthma management, and an EMR-based targeted collection of tools and resources. Barriers included a low priority of paediatric asthma due to few children with asthma in their practices. The pathway was not integrated into clinic flow and there was not a specific process to ensure the pathway was used. Sites without project champions also struggled more with implementation. Despite these barriers, clinicians identified mitigation strategies to improve uptake including developing a reminder system within the EMR and creating a workflow that incorporated the pathway. CONCLUSION: (an ongoing plan for sustainability) there may have been greater uptake of the pathway. TRIAL REGISTRATION NUMBER: This study was registered at clinicaltrials.gov on 25 June 2015; the registration number is: NCT02481037, https://clinicaltrials.gov/ct2/show/NCT02481037?term=andrew+cave&cond=Asthma+in+Children&cntry=CA&city=Edmonton&draw=2&rank=1.

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)0.024
metaresearch head score (Gemma)0.029
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 score0.036
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.331
GPT teacher head0.659
Teacher spread0.328 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

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