Using Administrative Data in Primary Care to Evaluate the Effectiveness of a Continuing Professional Development Program Focused on the Management of Patients Living With Obesity
Bibliographic record
Abstract
Abstract Introduction: There are guidelines for referral to medical and/or surgical weight loss interventions (MSWLI) in Ontario; however, only about one-third of eligible patients in our region are being referred for consideration of MSWLI. Methods: A planning committee, including a registered dietician, psychiatrist, endocrinologist, bariatric surgeon, family physician, and educationalists, developed an interdisciplinary continuing professional development (CPD) program focused on practical approaches to the management of patients living with obesity. The Kirkpatrick model was used to evaluate the educational outcomes of the CPD program specifically focusing on Level-2, -3, and -4 outcomes based on self-reported questionnaire and health administrative data. Results: Eighteen primary care providers from the CPD program agreed to participate in this study, and 16 primary care providers (89%) completed the postintervention questionnaire and granted us access to their MSWLI referral data; 94% of study participants reported changes to their knowledge, comfort, and confidence (Level 2), as well as expected change in their future behaviour (Level 3) following the CPD program. However, there was no change in Kirkpatrick Level-4 outcomes, despite more than 90% of participants indicating that they will be making changes to their practice after the program. Discussion: The CPD program in our study was overwhelmingly well received and participants reported knowledge (Level 2) and behavioural (Level 3) changes following participation; however, there was no detectable change in their clinical practice (Level 4). The methodology described in our proof-of-concept study can be modified and adopted to evaluate Level-4 outcomes in other studies of effectiveness of CPD interventions.
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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 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".