The Role of the Champion in Primary Care Change Efforts: From the State Networks of Colorado Ambulatory Practices and Partners (SNOCAP)
Bibliographic record
Abstract
BACKGROUND: Change champions are important for moving new innovations through the phases of initiation, development, and implementation. Although research attributes positive health care changes to the help of champions, little work provides details about the champion role. METHODS: Using a combination of immersion/crystallization and matrix techniques, we analyzed qualitative data, which included field notes of team meetings, interviews, and transcripts of facilitator meetings, from a sample of 8 practices. RESULTS: Our analysis yielded insights into the value of having 2 discrete types of change champions: (1) those associated with a specific project (project champions) and (2) those leading change for entire organizations (organizational change champions). Relative to other practices under study, those that had both types of champions who complemented each other were best able to implement and sustain diabetes care processes. We provide insights into the emergence and development of these champion types, as well as key qualities necessary for effective championing. CONCLUSIONS: Practice transformation requires a sustained improvement effort that is guided by a larger vision and commitment and assures that individual changes fit together into a meaningful whole. Change champions--both project and organizational change champions--are critical players in supporting both innovation-specific and transformative change efforts.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".