Multidisciplinary Medication Review in Long-Term Care: A Review of Clinical Utility, Cost-Effectiveness and Guidelines [Internet]
Bibliographic record
Abstract
“Polypharmacy” refers to the use of two or more medications, and commonly refers to the use of five or more medications. Polypharmacy is more prevalent among those aged 65 years and over than in younger populations., Polypharmacy occurs more frequently among those residing in long-term care facilities than those living in communities and can be due to duplicate or redundant medications for similar diseases. The use of multiple medications can lead to toxicity and decrease drug compliance. The adverse effects of certain medications may induce clinicians to prescribe more drugs to treat them. In a 2008 survey that interviewed 3,132 Canadians aged 65 years and over, 27% of the respondents were regularly taking five or more medications and 12% of them had experienced drug-related adverse events, in comparison to 5% of Canadians taking one or two medications.To prevent inappropriate use of medications among the elderly, there are guidelines aiming at deprescribing certain classes of medications, or avoiding potentially inappropriate medications in populations with specific conditions. One prominent example is the Beers criteria last updated by the American Geriatrics Society in 2019. There are recommendations on the medications that should be avoided in general or specific to health conditions. To put these guidelines into practice requires medication reviews to screen and deprescribe the medications among the elderly, particularly those residing in long-term care facilities.Pharmacist-led medication reviews have been implemented in countries such as the US, the UK, and Canada. In a systematic review, pharmacist-led and team-based medication reviews were found to improve the quality of medication use in long-term care facilities. Team-based reviews involve professionals from different disciplines and often consist of pharmacists, clinicians, and nurses., In a 2011 Canadian Agency for Drugs and Technologies in Health report, low-quality evidence from two systematic reviews and two non-randomized studies showed that team-based medication reviews (every three months in one primary study, unspecified in others) were associated with less use of inappropriate medications and better patient health outcomes, in comparison to usual care. However, it remains unclear whether more frequent medication reviews, such as every three months, can improve medication use and reduce adverse events., This report aims to review the evidence regarding the clinical utility and cost-effectiveness of multidisciplinary medication reviews in long-term care facilities, as well as clinical guidelines on multidisciplinary medication reviews.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".