The Impact of Pharmacist Interventions on Quality Use of Medicines, Quality of Life, and Health Outcomes in People with Dementia and/or Cognitive Impairment: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Medication use in people with dementia and/or cognitive impairment (PWD/CI) is challenging. As medication experts, pharmacists have an important role in improving care of this vulnerable population. OBJECTIVE: Systematically review evidence for the effectiveness of pharmacist-led interventions on quality use of medicines, quality of life, and health outcomes of PWD/CI. METHODS: A systematic review was conducted using MEDLINE, EMBASE, PsycINFO, Allied and Complementary Medicine (AMED) and Cumulative index to Nursing and Allied Health Literature (CINAHL) databases from conception to 20 March 2017. Full articles published in English were included. Data were synthesized using a narrative approach. RESULTS: Nine studies were eligible for inclusion. All studies were from high-income countries and assessed pharmacist-led medication management services. There was great variability in the content and focus of services described and outcomes reported. Pharmacists were found to provide a number of cognitive services including medication reconciliation, medication review, and medication adherence services. These services were generally effective with regards to improving quality use of medicines and health outcomes for PWD/CI and their caregivers, and for saving costs to the healthcare system. Pharmacist-led medication and dementia consultation services may also improve caregiver understanding of dementia and the different aspects of pharmacotherapy, thus improving medication adherence. CONCLUSION: Emerging evidence suggests that pharmacist-led medication management services for PWD/CI may improve outcomes. Future research should confirm these findings using more robust study designs and explore additional roles that pharmacists could undertake in the pursuit of supporting PWD/CI.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 |
| 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".