Drug‐Related‐Problem Outcomes and Program Satisfaction from a Comprehensive Brown Bag Medication Review
Bibliographic record
Abstract
OBJECTIVES: To classify and quantify drug-related problems (DRPs), determine acceptance of DRP recommendations, and assess medication review satisfaction. DESIGN: Comprehensive brown bag medication reviews. SETTING: Six senior centers and three senior high-rises. PARTICIPANTS: Individuals aged 60 and older (mean age 75.9 ± 8.5) taking five or more medications (n = 85). MEASUREMENTS: Two investigators independently classified DRPs using modified Pharmaceutical Care Network Europe classification scheme and severity of medication error and value of service scales. Two other investigators adjudicated classification differences. Satisfaction surveys were administered immediately and 3 months after review. A DRP recommendation implementation survey was completed at least 3 months after the review. RESULTS: Participants had a mean of 4.3 ± 2.8 DRPs (range 0-10). DRPs were classified as adverse reactions (30%), treatment effectiveness (28%), treatment costs (13%), information need (8%), and other (21%). Causes included drug selection (40%), wrong dosage (23%), participant problems (e.g., adherence, lack of medication knowledge, 16%), drug use process problems (12%), drug formulation (0.5%), treatment duration (0.5%), and other (7%). Interventions required drug changes (44%), prescriber input (37%), individual counseling (18%), or other (1%). DRP severities were significant (59%) or minor (35%). Participants expressed satisfaction with the program because they were able to ask questions, trusted the answers, and knew more about their medications. After 3 months, they had implemented 63% of the DRP recommendations. CONCLUSION: Older adults found the medication review helpful and implemented 63% of the DRP recommendations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".