Facilitators and barriers to clinical practice guideline-consistent supportive care at pediatric oncology institutions: a Children’s Oncology Group study
Bibliographic record
Abstract
BACKGROUND: Clinical practice guideline (CPG)-consistent care improves patient outcomes, but CPG implementation is poor. Little is known about CPG implementation in pediatric oncology. This study aimed to understand supportive care CPG implementation facilitators and barriers at pediatric oncology National Cancer Institute (NCI) Community Oncology Research Program (NCORP) institutions. METHODS: Healthcare professionals at 26 pediatric, Children's Oncology Group-member, NCORP institutions were invited to participate in face-to-face focus groups. Serial focus groups were held until saturation of ideas was reached. Supportive care CPG implementation facilitators and barriers were solicited using nominal group technique (NGT), and implementation of specific supportive care CPG recommendations was discussed. Notes from each focus group were analyzed using a directed content analysis. The top five themes arising from an analysis of NGT items were identified, first from each focus group and then across all focus groups. RESULTS: Saturation of ideas was reached after seven focus groups involving 35 participants from 18 institutions. The top five facilitators of CPG implementation identified across all focus groups were organizational factors including charging teams with CPG implementation, individual factors including willingness to standardize care, user needs and values including mentorship, system factors including implementation structure, and implementation strategies including a basis in science. The top five barriers of CPG implementation identified were organizational factors including tolerance for inconsistencies, individual factors including lack of trust, system factors including administrative hurdles, user needs and values including lack of inclusivity, and professional including knowledge gaps. CONCLUSIONS: Healthcare professionals at pediatric NCORP institutions believe that organizational factors are the most important determinants of supportive care CPG implementation. They believe that CPG-consistent supportive care is most likely to be delivered in organizations that prioritize evidence-based care, provide structure and resources to implement CPGs, and eliminate implementation barriers. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02847130. Date of registration: July 28, 2016.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".