Interventions to Address Potentially Inappropriate Prescribing for Older Primary Care Patients
Bibliographic record
Abstract
Importance: Prescriptions for potentially inappropriate medications are common and, by definition, may carry risks that outweigh benefits. Objective: To determine whether interventions to address potentially inappropriate prescribing for older primary care patients are associated with changes in the number of medications prescribed, drug-related harms, hospitalizations, and mortality. Data Sources: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were searched from inception to September 6, 2024. Study Selection: Randomized clinical trials of interventions to address potentially inappropriate prescribing for older primary care patients (aged ≥65 years) residing in the community or in long-term care facilities, such as nursing homes or assisted-living facilities, were included. Data Extraction and Synthesis: Two researchers independently screened the records and abstracted data using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Data were pooled using random-effects models. Main Outcomes and Measures: The planned outcomes were the number of medications, nonserious adverse drug reactions, injurious falls, quality of life, medical visits, emergency department visits, hospitalizations, and all-cause mortality. Random-effects meta-analyses were performed using the inverse variance method for similar studies, reporting risk ratios (RRs) or standardized mean differences (SMDs). Heterogeneity was assessed with I2 values, and publication bias was assessed with funnel plots and the Egger regression test. Results: Of the 14 649 records identified, 118 randomized clinical trials (comprising 417 412 patients) were included in this review. Interventions to address potentially inappropriate prescribing were associated with a reduction in the number of medications prescribed (SMD, -0.25 [95% CI, -0.38 to -0.13]), equivalent to approximately 0.5 fewer medications per patient. However, there were no substantial differences in the other outcomes, including nonserious adverse drug reactions (RR, 0.92 [95% CI, 0.58-1.46]), injurious falls (SMD, 0.01 [95% CI, -0.12 to 0.14]), quality of life (SMD, 0.09 [95% CI, -0.04 to 0.23]), medical visits (SMD, 0.02 [95% CI, -0.02 to 0.07]), emergency department admissions (RR, 1.02 [95% CI, 0.96-1.08]), hospitalizations (RR, 0.95 [95% CI, 0.89-1.02]), or all-cause mortality (RR, 0.94 [95% CI, 0.85-1.04]). Conclusions and Relevance: In this systematic review and meta-analysis, interventions to address potentially inappropriate prescribing were associated with reductions in the number of medications prescribed, with no substantial change in other outcomes. These findings suggest that inappropriate prescribing interventions may be implemented to safely reduce the number of medications prescribed to older adults in the primary care setting. Future studies should continue to evaluate these interventions using standardized criteria and consistently report potential harms to support data synthesis and capture key outcomes such as quality of life, hospitalization, and mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".