Development of a clinician guide for electronic medication adherence products in older adults
Bibliographic record
Abstract
Background/objectives: The ability to manage medications independently may be affected in older adults due to physical and cognitive limitations. Numerous electronic medication adherence products (eMAPs) are available to aid medication management. Unfortunately, there are no available guidelines to support clinicians in recommending eMAPs. The objective of this study was to create and validate a clinician tool to guide use of eMAPs. Methods: Pharmacists who previously tested the usability of the eMAPs participated in a focus group to provide feedback on 5 metrics of the clinician guide: unassisted task completion, efficiency, usability, workload and an overall eMAP score. Participants were asked semistructured questions on how they would use the tool to inform recommendations of medication aids to patients. The discussions were audio-recorded and transcribed verbatim and qualitatively analyzed. The clinician guide was modified to reflect feedback. Results: Five pharmacists (80% female, mean years of practice: 15.8) participated in the focus group. The clinician guide was modified by removing 2 metrics and adding an additional 8 metrics: maximum number of alarms, number of days the product can accommodate for based on a daily dosing regimen, price, monthly subscription, portability, locking feature, average time to set the device and number of steps required to set the device. The definition and calculation for unassisted task completion were modified. Additional instructions and specific patient case examples were also included in the final clinician guide. Conclusion: Since significant variability exists between eMAPs, it is imperative to have a tool for frontline clinicians to use when appropriately recommending the use of these products for medication management in older adults.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".