Facilitators and Barriers to Recruiting Ambulatory Oncology Practices Into a Large Multisite Study: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Practice-based research is essential to generate the data necessary to understand outcomes in ambulatory oncology care. Although there is an increased interest in studying ambulatory oncology care, given the rising patient volumes and complexity in those settings, little guidance is available on how best to recruit ambulatory oncology practices for research. OBJECTIVE: This paper aimed to describe the facilitators and barriers to recruiting ambulatory oncology practices into a large multisite study. METHODS: Using a mixed methods design, we sought to recruit 52 ambulatory oncology practices that have participated in a state-wide quality improvement collaborative for the quantitative phase. We used 4 domains of the Consolidated Framework for Implementation Research (CFIR) to describe facilitators and barriers to recruitment. RESULTS: We successfully recruited 28 of the 52 collaborative-affiliated practices, collecting survey data from 2223 patients and 297 clinicians. Intervention attributes included multimodal outreach and training activities to assure high fidelity to the data collection protocol. The implementation process was enhanced through interactive training and practice-assigned champions responsible for data collection. External context attributes that facilitated practice recruitment included partnership with a quality improvement collaborative and the inclusion of a staff member from the collaborative in our team. Key opinion leaders within each practice who could identify challenges to participation and propose flexible solutions represented internal context attributes. We also reported lessons learned during the recruitment process, which included navigating diverse approaches to human subjects protection policies and understanding that recruitment could be a negotiated process that took longer than anticipated, among others. CONCLUSIONS: Our experience provides other researchers with challenges to anticipate and possible solutions for common issues. Using the CFIR as a guide, we identified numerous recruitment barriers and facilitators and devised strategies to enhance recruitment efforts. In conclusion, researchers and clinicians can partner effectively to design and implement research protocols that ultimately benefit patients who are increasingly seeking care in ambulatory practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".