Bibliographic record
Abstract
To understand possible medication overprescribing, it would be important to know which classes are the most prescribed, for which indications, for what duration, and for which age groups. Among the 10 most frequently prescribed medication classes for US adults, four were evaluated for overprescribing, and systematically assessed in relation to their primary indication. The assessment included usage patterns, trends, age of recipients, treatment duration, and benefits versus adverse consequences. The findings in this selective review are supported by an extensive search of the medical literature. The four selected medication categories and their most common indication included opioids for chronic pain, proton pump inhibitors for indigestion, levothyroxine for subclinical hypothyroidism, and antidepressants for subsyndromal levels of depression. These medications, grouped by their most frequent indication along with polypharmacy, have experienced major prescription increases in recent years, particularly among older patients. Most concerning is that they have been frequently prescribed for extended periods, usually with inadequate evidence of benefit. High drug usage patterns can aid in quantifying overprescribing within polypharmacy by age group.
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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 | 0.023 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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 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".