Potentially Inappropriate Medication Use by Medicaid+Choice Beneficiaries in the Last Year of Life
Bibliographic record
Abstract
BACKGROUND: Regardless of the payer and the period studied the prevalence of potentially inappropriate medication use in the elderly ranged from 21% to 40%. OBJECTIVE: To look at potentially inappropriate prescribing in a group of Medicare+Choice beneficiaries in their last year of life (LYOL) in a large national managed care organization. RESEARCH DESIGN: Retrospective review of Medicare+Choice decedents' drug claims and enrollment data collected between January 1998 and December 2000, supplemented by the Medicare denominator file and 1990 Census data. SUBJECTS: Four thousand six hundred two beneficiaries in a large national managed care organization. MEASURES: We analyzed the relationship between disagreement with the Beers' criteria and sociodemographic descriptors, insurance characteristics, and cause of death. We used logistic regression techniques to estimate factors associated with the disagreement. RESULTS: Two thousand thirty-one beneficiaries (44%) had at least one claim in the LYOL that disagreed with a Beers' criterion, 15% experienced more than one unique Beers' disagreement. The most common disagreements were for the use of propoxyphene (15.0%), followed by zolpidem (3.8%), and amitriptyline (2.8%). Based on total claims, cancer patients were most likely to receive propoxyphene (35.3%) followed by patients with a heart condition (29.6%). A large proportion of the potentially inappropriate prescribing involves psychoactive drugs. The logistic model showed fewer Beers' criteria breaches associated with being male and being non-white. Beers' breaches were more common if the beneficiary has increasing prescription use or died from cancer. CONCLUSION: This study showed that many beneficiaries have prescriptions that contravene the Beers' criteria.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".