Physician perspectives on a tailored multifaceted primary care practice facilitation intervention for improvement of cardiovascular care
Bibliographic record
Abstract
BACKGROUND: Practice facilitation is an effective way to help physicians implement change in their clinics, but little is known about physicians' perspectives on this service. OBJECTIVES: To examine physicians' responses to a practice facilitation program, focussing on their overall satisfaction, perceived most significant clinical changes, and interactions with the facilitator. METHODS: The Improved Delivery of Cardiovascular Care program investigated the impact of practice facilitation on improving the quality of cardiovascular primary care in Eastern Ontario, Canada, from 2007 to 2011. We conducted a qualitative content analysis of post-intervention surveys completed by participating physicians, using a constant comparison approach framed around the Chronic Care Model. RESULTS: Ninety-five physicians completed the survey. Physicians overwhelmingly viewed the program positively, though descriptions of its benefits and impact varied widely. Facilitators filled three key roles for physicians, acting as a resource centre, motivator and outside perspective. Physicians adopted a number of changes in their practices. These changes include adoption of clinical information systems (diabetes registries), decision support tools (chart audits, guideline documents, flow sheets) and delivery system design (community resources). CONCLUSIONS: Most physicians appreciated having access to a practice facilitator and viewed the intervention positively. Insight into physicians' perspectives on practice facilitation provides a valuable counterpoint to outcomes-based evaluations of such services. Further research should investigate potential obstacles in the group of physicians who make fewer practice changes, as well as the sustainability of this type of facilitation intervention.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".