Reducing Central Nervous System–Active Medications to Prevent Falls and Injuries Among Older Adults
Bibliographic record
Abstract
Importance: High-risk medications that contribute to adverse health outcomes are frequently prescribed to older adults. Deprescribing interventions reduce their use, but studies are often not designed to examine effects on patient-relevant health outcomes. Objective: To test the effect of a health system-embedded deprescribing intervention targeting older adults and their primary care clinicians for reducing the use of central nervous system-active drugs and preventing medically treated falls. Design, Setting, and Participants: In this cluster randomized, parallel-group, clinical trial, 18 primary care practices from an integrated health care delivery system in Washington state were recruited from April 1, 2021, to June 16, 2022, to participate, along with their eligible patients. Randomization occurred at the clinic level. Patients were community-dwelling adults aged 60 years or older, prescribed at least 1 medication from any of 5 targeted medication classes (opioids, sedative-hypnotics, skeletal muscle relaxants, tricyclic antidepressants, and first-generation antihistamines) for at least 3 consecutive months. Intervention: Patient education and clinician decision support. Control arm participants received usual care. Main Outcomes and Measures: The primary outcome was medically treated falls. Secondary outcomes included medication discontinuation, sustained medication discontinuation, and dose reduction of any and each target medication. Serious adverse drug withdrawal events involving opioids or sedative-hypnotics were the main safety outcome. Analyses were conducted using intent-to-treat analysis. Results: Among 2367 patient participants (mean [SD] age, 70.6 [7.6] years; 1488 women [63%]), the adjusted cumulative incidence rate of a first medically treated fall at 18 months was 0.33 (95% CI, 0.29-0.37) in the intervention group and 0.30 (95% CI, 0.27-0.34) in the usual care group (estimated adjusted hazard ratio, 1.11 (95% CI, 0.94-1.31) (P = .11). There were significant differences favoring the intervention group in discontinuation, sustained discontinuation, and dose reduction of tricyclic antidepressants at 6 months (discontinuation adjusted rate: intervention group, 0.23 [95% CI, 0.18-0.28] vs usual care group, 0.13 [95% CI, 0.09-0.17]; adjusted relative risk, 1.79 [95% CI, 1.29-2.50]; P = .001) and secondary time points (9, 12, and 15 months). Conclusions and Relevance: In this randomized clinical trial of a health system-embedded deprescribing intervention targeting community-dwelling older adults prescribed central nervous system-active medications and their primary care clinicians, the intervention was no more effective than usual care in reducing medically treated falls. For health systems that attend to deprescribing as part of routine clinical practice, additional interventions may confer modest benefits on prescribing without a measurable effect on clinical outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT05689554.
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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 | 0.001 |
| 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".