Towards optimal electronic medical record use: perspectives of advanced users
Bibliographic record
Abstract
Background: While primary health care electronic medical record (EMR) adoption has increased in Canada, the use of advanced EMR features is limited. Realizing the potential benefits of primary health care EMR use is dependent not only on EMR acquisition, but also on its comprehensive use and integration into practice; yet, little is known about the advanced use of EMRs in primary health care. Objective: To explore the views of advanced primary health care EMR users practising in a team-based environment. Methods: A descriptive qualitative approach was used to explore the views of primary health care practitioners who were identified as advanced EMR users. Twelve individual semi-structured interviews were held with primary health care practitioners in Southwestern Ontario, Canada. Field notes were created after each interview. Interviews were audio recorded and transcribed verbatim. Researchers independently coded the transcripts and then met to discuss the results of the coding. We used a thematic approach to data analysis. Results: Three themes emerged from the data analysis: advanced EMR users as individuals with signature characteristics, advanced EMR users as visionaries and advanced EMR users as agents of change. In any one participant, these elements could overlap, illuminating the important interplay between these themes. Taken together, these themes defined advanced use among this group of primary health care practitioners. Conclusions: To realize the potential benefits of EMR use in improved patient care and outcomes, we need to understand how to support EMR use. This study provides a necessary building block in furthering this understanding.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".