Trends in antipsychotic prescribing among community-dwelling older adults with dementia, 2010-2018
Bibliographic record
Abstract
Abstract Due to an FDA “black box” warning for heightened risk of death, Choosing Wisely (CW) recommends avoiding antipsychotic prescription drugs as first-line treatment for dementia-related agitation. Yet, post-CW trends among community-dwelling patients with dementia remain unknown. In this retrospective cohort study, we used nationally representative Health and Retirement Study survey data linked to Medicare fee-for-service claims (January 1, 2010-December 31, 2018) to analyze prescribing trends during the pre-publication (2010-2012), publication (2013-2015), and post-publication (2016-2018) periods of CW recommendations. We included community-dwelling adults aged ≥65 years with dementia. We utilized multivariable mixed regression models to determine the percentage of patients prescribed any, potentially low-value, and potentially indicated antipsychotics. Among an estimated 2.4-2.7 million patients with dementia, any antipsychotic prescribing increased from 9.4% (95% CI, 6.4%-12.3%) during the pre-publication period (2010-2012) to 15.8% (95% CI, 12.8%-18.8%) (P < 0.001) during the publication period (2013-2015). Potentially low-value and potentially indicated prescriptions also increased. Post-publication period (2016-2018) prescribing of 16.0% (95% CI, 13.0%-19.1%) (P < 0.001) remained higher than pre-publication. Among older Americans with dementia, antipsychotic prescriptions increased after the publication of CW recommendations and held steady in the subsequent post-publication period. Stronger interventions, such as electronic clinical decision support tools and financial incentives, are needed to curb low-value antipsychotic prescribing for this vulnerable population.
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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 | 0.025 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".