Experience with an Adherence Assessment Form
Bibliographic record
Abstract
Background: Nonadherence is so common that the majority of patients taking chronic medications will eventually stop their medication on their own. Pharmacists are in a position to intervene to improve adherence; however, many do not. Such intervention would ideally be accomplished in a total pharmaceutical care approach; however, many pharmacists feel they do not have the time for such interventions. We propose the use of an adherence assessment form which the patient would complete to save pharmacist time; the pharmacist could then react to issues identified in the form. Purpose: The objective of this study was to determine the acceptability of such a form to patients and to dispensary staff, and its potential for impact on adherence. Methods: The author recruited 2 regional groups of pharmacies with pharmacy interns/students, 4 in Hamilton and 15 in Edmonton. Patients presenting with new prescriptions were asked by the intern or the staff to participate via a consent form. Patients completed the adherence assessment form while they waited for their prescription. The pharmacist then intervened on adherence issues identified in the questionnaire. The patient completed a patient satisfaction survey. The pharmacist or the assistant was asked to complete a pharmacy satisfaction survey. Results: A total of 200 patients, 111 in Hamilton and 89 in Edmonton, completed the process. Analysis of patient responses revealed that most patients expect benefits from their medication and would like more information; 2/3 found that the assessment form led to an informative discussion; 1/3 found that it brought up issues they had not thought about; over half learned a lot about their new medication; and over half said that as a result of the dialogue, they will know what do about side effects; 1/5 said they would be more motivated about their health. Analysis from the pharmacies revealed that over half of the pharmacies believed the form improved comprehension of the medication regimen; over half believed it facilitated more consultation for patients; over half found greater satisfaction by patients for their services and 1/3 felt it frequently changed patient outcomes. Despite all this, 2/3 of pharmacies said that the form should not be routinely used, as it did not save pharmacists any time. Conclusion: It was concluded that the form was acceptable to patients and pharmacies and showed sufficient potential impact to warrant a study of its influence on adherence measures.
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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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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".