Reliability of a Modified Medication Appropriateness Index in Community Pharmacies
Bibliographic record
Abstract
BACKGROUND: The medication appropriateness index (MAI) has demonstrated reliability in selected outpatient clinics where medical data were easily accessible from medical charts. However, its use in the community setting where patient data may be limited has not been examined. OBJECTIVE: To evaluate the usefulness of a modified MAI for use in the community pharmacy setting by testing interrater reliability using 3 different rating schemes. METHODS: Two raters evaluated 160 medications for 32 elderly ambulatory patients. Patient information was acquired using community pharmacist-collected medication histories. A summated MAI score, percent agreement, kappa, positive agreement, negative agreement, and intraclass correlation coefficient were calculated for each criterion using 3 scoring schemes. A paired samples t-test (95% CI) was used to test interrater reliability. RESULTS: The kappa statistics were >0.75 for indication and effectiveness, but good (0.41-0.66) for the remaining criteria using the Hanlon scoring scheme. The intraclass coefficients (0.82, 0.86, 0.87) and overall kappa (0.65, 0.66, 0.61) were similar for the 3 schemes. CONCLUSIONS: This study suggests that the modified MAI has the potential to detect medication appropriateness and inappropriateness in the community pharmacy setting; however, it is not without limitations. Because the MAI has the most clinimetric and psychometric data available, the instrument should be studied further to increase its reliability and generalizability.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".