Strategies to simplify complex medication regimens
Bibliographic record
Abstract
BACKGROUND: Older people use increasingly complex medication regimens. Complex regimens are challenging to administer, particularly for those with cognitive impairment, frailty, poor eyesight or limited dexterity. Complex regimens have been linked to non-adherence, medication errors and hospital admissions. OBJECTIVE: The aim of this article is to describe strategies to reduce the complexity of medication regimens in community and residential aged care settings. DISCUSSION: Medication regimen simplification is the process of reducing medication burden through strategies such as consolidating dosing times, standardising routes of administration, using long-acting rather than shorter-acting formulations, and switching to combination products in place of single-ingredient products. Obtaining a best possible medication history, ensuring appropriateness of current therapy, and deprescribing are important steps prior to implementing regimen simplification. Implementing such strategies should be based on a discussion and consideration of patient preferences, and include clinical judgement to limit the risk of unintended consequences for patients or carers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".