Developing a tool to measure contributions to medication-related processes in family practice
Bibliographic record
Abstract
Successful team care requires a shared understanding of roles and expertise. This paper describes the development and preliminary exploration of the psychometric properties of a tool designed to measure contributions to family practice medication-related processes. Our team identified medication-related processes commonly occurring in family practice. We assessed clinical appropriateness using a sensibility questionnaire and pilot-tested with 11 pharmacists, nurses and physicians. We performed a simulated exercise to group the processes and assessed the internal consistency of the groupings using Cronbach's alpha coefficient. We examined test-retest reliability using intra-class coefficient (ICC). Following three revisions, the final Medication Use Processes Matrix (MUPM) included 22 medication-related processes and scale descriptors reflecting contribution to each process. Mean sensibility ratings were high for each component. We developed five theoretical groupings (diagnosis & prescribing, monitoring, administrative/documentation, education, medication review) and found their overall internal consistency was good (alpha > 0.80). The test-retest reliability was strong (ICC > 0.80). Preliminary validation showed significant differences in how health professionals view interprofessional contributions toward medication-related processes. Interprofessional care requires a negotiated understanding of processes and contributions. The MUPM provides an explicit description of medication-related processes in primary care, measures perceived contributions and emerges as a new tool to measure collaborative care in family practices.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".