Effectiveness and Cost Effectiveness of Pharmacist-led Deprescribing Interventions in Nursing Homes and Ambulatory Care Settings in Elderly Patients: A Systematic Review
Bibliographic record
Abstract
Background: Potentially Inappropriate Medications (PIMs) are drugs in which the adverse risks exceed the clinical benefits, lacking evidence-based indications, potentially interact with other medications.PIM use is common in older adults who are frequently treated with multiple medications.PIM use in older adults is associated with many complications.Aim: To critically appraise and systematically evaluate the existing studies on the effectiveness of pharmacist-led deprescribing in health service utilization, clinical effectiveness, cost effectiveness and cost utility.In nursing home and ambulatory care settings and patients aged 65 years and above.Methods: PubMed, Medline, CINAHL, Embase, and Cochrane Library were searched between 1st to 2nd July 2021 and updated on 25 th December 2021 to select studies that compare pharmacist-led deprescribing in nursing home and ambulatory care settings with usual care.Outcomes related to health service utilization, clinical effectiveness, cost effectiveness and cost utility were evaluated.Results: A total of 3944 relevant records were identified through database searching.A further ten records were identified by following up citations and reference lists of the selected studies.After assessment, nine studies were included in the review.Four of the included studies reported outcomes relating to both health service utilization and clinical effectiveness, three studies reported only health service utilization, and the two economic studies reported cost effectiveness and cost utility respectively.Six out of seven studies that reported health service utilization outcomes found improvement in health service utilization after the implementation of the pharmacist-led deprescribing.However, there is no positive clinical effectiveness outcomes, and no worldwide studies for the economic outcomes.Conclusion: This evidence of moderate to high quality.Pharmacist-led deprescribing was effective only in reducing PIMs usage and medication burden for older adults in nursing home and ambulatory care setting, but with no clinical effectiveness outcomes.It is essential to evaluate the economic outcomes in different countries other than Canada (high-income county).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".