Trends in outpatient antibiotic use and prescribing practice among US older adults, 2011-15: observational study
Bibliographic record
Abstract
OBJECTIVE: To identify temporal trends in outpatient antibiotic use and antibiotic prescribing practice among older adults in a high income country. DESIGN: Observational study using United States Medicare administrative claims in 2011-15. SETTING: Medicare, a US national healthcare program for which 98% of older adults are eligible. PARTICIPANTS: 4.5 million fee-for-service Medicare beneficiaries aged 65 years old and older. MAIN OUTCOME MEASUREMENTS: Overall rates of antibiotic prescription claims, rates of potentially appropriate and inappropriate prescribing, rates for each of the most frequently prescribed antibiotics, and rates of antibiotic claims associated with specific diagnoses. Trends in antibiotic use were estimated by multivariable regression adjusting for beneficiaries' demographic and clinical covariates. RESULTS: The number of antibiotic claims fell from 1364.7 to 1309.3 claims per 1000 beneficiaries per year in 2011-14 (adjusted reduction of 2.1% (95% confidence interval 2.0% to 2.2%)), but then rose to 1364.3 claims per 1000 beneficiaries per year in 2015 (adjusted reduction of 0.20% over 2011-15 (0.09% to 0.30%)). Potentially inappropriate antibiotic claims fell from 552.7 to 522.1 per 1000 beneficiaries over 2011-14, an adjusted reduction of 3.9% (3.7% to 4.1%). Individual antibiotics had heterogeneous changes in use. For example, azithromycin claims per beneficiary decreased by 18.5% (18.2% to 18.8%) while levofloxacin claims increased by 27.7% (27.2% to 28.3%). Azithromycin use associated with each of the potentially appropriate and inappropriate respiratory diagnoses decreased, while levofloxacin use associated with each of those diagnoses increased. CONCLUSION: Among US Medicare beneficiaries, overall antibiotic use and potentially inappropriate use in 2011-15 remained steady or fell modestly, but individual drugs had divergent changes in use. Trends in drug use across indications were stronger than trends in use for individual indications, suggesting that guidelines and concerns about antibiotic resistance were not major drivers of change in antibiotic use.
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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 | 0.000 | 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".