Navigating Change: How Outreach Facilitators Can Help Clinicians Improve Patient Outcomes
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe outreach facilitation as an effective method of assisting and supporting primary care practices to improve processes and delivery of care. METHODS: We spent 4 years working with 83 practices in Eastern Ontario, Canada, on the Improved Delivery of Cardiovascular Care through the Outreach Facilitation program. RESULTS: Primary care practices, even if highly motivated, face multiple challenges when providing quality patient care. Outreach facilitation can be an effective method of assisting and supporting practices to make the changes necessary to improve processes and delivery of care. Multiple jurisdictions use outreach facilitation for system redesign, improved efficiencies, and advanced access. CONCLUSIONS: The development and implementation of quality improvement programs using practice facilitation can be challenging. Our research team has learned valuable lessons in developing tools, finding resources, and assisting practices to reach their quality improvement goals. These lessons can lead to improved experiences for the practices and overall improved outcomes for the patients they serve.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".