Barriers and supports to implementation of MDI/spacer use in nine Canadian pediatric emergency departments: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Despite recent research supporting the use of metered dose inhalers with spacer devices (MDI/spacers) in pediatric emergency departments (PEDs) for acute exacerbations of asthma, uptake of this practice has been slow. The objectives of this study were to determine the barriers and supports to implementing MDI/spacer research and to identify factors associated with early and late adoption of MDI/spacers in Canadian PEDs. METHODS: Using a comparative case study design, we classified nine tertiary care pediatric hospital PEDs based on their stage of implementation. Data were collected using focus group interviews with physicians, registered nurses (RNs), and respiratory therapists (RTs), and individual interviews with both patient care and medical directors at each site. Initial coding was based on the Ottawa Model of Research Use (OMRU) categories of elements known to influence the uptake of innovations. RESULTS: One hundred and fifty healthcare professionals from nine different healthcare institutions participated in this study. Lack of leadership in the form of a research champion, a lack of consensus about the benefits of MDI/spacers among staff, perceived resistance from patients/parents, and perceived increased cost and workload associated with MDI/spacer use were the most prevalent barriers to the adoption of the MDI/spacer. Common strategies used by early-adopting sites included the active participation of all professional groups in the adoption process in addition to a well-planned and executed educational component for staff, patients, and families. Early adopter sites were also more likely to have the MDI/spacer included in a clinical protocol/pathway. CONCLUSION: Potential barriers and supports to implementation have been identified that will help EDs adopt MDI/spacer use. Future interventions intended to increase MDI/spacer use in PEDs will need to be sensitive to the barriers identified in this study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".