Impact of pharmacist-led home medicines review services on drug-related problems among the elderly population: a systematic review
Bibliographic record
Abstract
OBJECTIVES: To address and elucidate the impact of pharmacist-led home medicines review (HMR) services on identifying drug-related problems (DRPs) among the elderly population in home care settings. METHODS: A comprehensive systematic search was performed using electronic scientific databases such as PubMed, Scopus, Embase, and Web of Science for studies published between January 1, 2008 and December 31, 2018, pertaining to HMR services by pharmacists for identifying DRPs. RESULTS: In total, 4,292 studies were retrieved from the searches, of which 24 were excluded as duplicates. Titles and abstracts were screened for the remaining 4,268 studies, of which 4,239 were excluded due to the extraneous nature of the titles and/or abstracts. Subsequently, 29 full-text articles were assessed, and 19 were removed for lacking the outcome of interest and/or not satisfying the study's inclusion criteria. Finally, 10 studies were included in the review; however, publication bias was not assessed, which is a limitation of this study. In all studies, pharmacists identified a highly significant amount of DRPs through HMR services. The most common types of DRPs were potential drug-drug interactions, serious adverse drug reactions, need for an additional drug, inappropriate medication use, non-adherence, untreated indications, excessive doses, and usage of expired medications. CONCLUSIONS: HMR is a novel extended role played by pharmacists. The efficiency of such programs in identifying and resolving DRPs could minimize patients' health-related costs and burden, thereby enhancing the quality of life and well-being among the elderly.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| 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 | 0.001 |
| 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".