Using program evaluation to support knowledge translation in an interprofessional primary care team: a case study
Bibliographic record
Abstract
BACKGROUND: Evaluation is a fundamental component in building quality primary care and is ideally situated to support individual, team and organizational learning by offering an accessible form of participatory inquiry. The evaluation literature has begun to recognize the unique features of KT evaluations and has described attributes to consider when evaluating KT activities. While both disciplines have focused on the evaluation of KT activities neither has explored the role of evaluation in KT. The purpose of the paper is to examine how participation in program evaluation can support KT in a primary care setting. METHODS: A mixed methods case study design was used, where evaluation was conceptualized as a change process and intervention. A Memory Clinic at an interprofessional primary care clinic was the setting in which the study was conducted. An evaluation framework, Pathways of Influence provided the theoretical foundation to understand how program evaluation can facilitate the translation of knowledge at the level of the individual, inter-personal (Memory Clinic team) and the organization. Data collection included questionnaires, interviews, evaluation log and document analysis. Questionnaires and interviews were administered both before and after the evaluation: Pattern matching was used to analyze the data based on predetermined propositions. RESULTS: Individuals gained program knowledge that resulted in changes to both individual and program practices. One of the key themes was the importance clinicians placed on local, program based knowledge. The evaluation had less influence on the broader health organization. CONCLUSIONS: Program evaluation facilitated individual, team and organizational learning. The use of evaluation to support KT is ideally suited to a primary care setting by offering relevant and applicable knowledge to primary care team members while being sensitive to local context.
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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 | 0.028 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| 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".