82 Exploring Healthcare Provider’s Perceptions on Implementing Patient-Reported Outcome Measures in Pediatric Asthma Care: A Theoretical Domains Framework Guided Qualitative Study
Bibliographic record
Abstract
Abstract Background Patient-reported outcome measures (PROMs) play an important role in promoting and supporting patient and family-centered care (PFCC). To deliver, improve, and sustain PFCC, it is crucial to empower children, families, and communities to identify their self-reported outcomes and experiences with the care received. PROMs play an important role in promoting and supporting PFCC. Asthma is the most common chronic condition in pediatrics requiring complex care plans and is a leading cause of hospitalization. Implementing interventions like PROMs in routine clinical care for asthma would require key stakeholders to change their behaviour. This qualitative descriptive study is part of a larger multi-phase project to develop the KidsPRO program, an electronic platform to administer, collect, and use PROMs in pediatrics. Objectives The objective of this study is to identify barriers and enablers to the implementation of PROMs in outpatient asthma clinics using the Theoretical Domains Framework (TDF). Design/Methods TDF guided this qualitative descriptive study design. TDF is one of the frameworks used in implementation sciences, which provides a theoretical basis to understanding potential barriers for the slow uptake of evidence into practice and the enablers that may influence the phenomenon. Semi-structured qualitative interviews were conducted with 17 participants from outpatient asthma clinics, which included general pediatricians, pediatric respirologists, nurses, allied health providers, and clinic staff. All the interviews were transcribed, deductively coded, inductively grouped in themes, and categorized into barriers and enablers. Results We identified 33 themes within 14 TDF domains, which were further categorized and tabulated into 16 barriers and 17 enablers to implementing PROMs in asthma clinics. Seventeen barriers to behavioural change identified in our study were attributed to personal, clinical, non-clinical, and other system-level factors and ranged from limited awareness of PROMs to language barriers and a patient’s complex family background. Clinicians’ commitment to providing patient and family-centered care, excitement, high importance, and optimism about using PROMs to provide comprehensive healthcare were identified as the major enablers. Compatibility of using electronic PROMs with current practice, competency in communication around psychosocial questions, confidence in self-abilities, demonstrate feasibility of implementing PROMs in asthma clinics. Conclusion The implementation of PROMs in pediatrics is lagging compared to adult populations. This implementation science-based systematic inquiry captured the complexity of PROMs implementation in pediatric outpatient clinical care for asthma. Considering the consistency in barriers and enablers to implementing PROMs across patient populations and care settings, many findings of this study will be directly applicable to other pediatric healthcare settings in Canada and beyond.
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 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 | 0.038 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".