Potentially inappropriate medications in geriatric outpatients with polypharmacy: application of six sets of published explicit criteria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Many different criteria have been developed to detect potentially inappropriate medications (PIMs), with wide variations in prevalence estimates and inconsistent associations with health outcomes. • Without head‐to‐head comparisons, it is difficult to know whether some PIM criteria systematically detect more or fewer PIMs than others in the same cohorts. WHAT THIS STUDY ADDS • Six sets of PIM criteria were applied to a single cohort, with PIM prevalence ranging from 24 to 73%. • Criteria with a higher number of statements and a higher percentage of local market/institution drug availability tended to detect more PIMs. • Caution should be exercised in applying PIM criteria developed in other regions when medication availability in the local market is limited. AIM Our aim was to compare the practicability of six different potentially inappropriate medication (PIM) criteria in geriatric outpatients with polypharmacy. METHODS We analysed baseline data from the Medication Safety Review Clinic in Taiwanese Elders (MSRC‐Taiwan) study. The prevalence and correlates of PIMs were determined on the basis of criteria developed in the USA, Canada, France, Norway, Ireland and Thailand. The percentage of PIMs considered as drug‐related problems and the problem‐solving rate are reported. RESULTS In the 193 participants, the prevalence of PIM varied from 24 to 73%. Application of the criteria revealed that a high number of chronic medications was a common risk factor for having at least one PIM. Of the 1713 medications reviewed, 5.6–14.8% were considered PIMs. Only 30–40% of the identified PIMs were reported as drug‐related problems by the MSRC team experts. Criteria with a higher number of statements and a higher percentage of local market/institution drug availability tended to detect more PIMs. CONCLUSIONS The prevalence of PIM varied significantly when different criteria were applied. Caution should be exercised in applying PIM criteria developed in other regions when medication availability in the local market is limited.
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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 | 0.001 |
| 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) | 0.001 | 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 it