Impact of a pharmaceutical care model for non-institutionalised elderly: results of a randomised, controlled trial
Bibliographic record
Abstract
Abstract Objectives To measure the impact of a community-based geriatric pharmaceutical care model on specific process measures. Methods The model was evaluated using a prospective, randomised, controlled study design. Clients who self-presented or were referred by Home Care were eligible if they were 65 years of age or older, non-institutionalised, taking two or more prescribed or non-prescribed medications, and willing to provide signed informed consent. A pharmacist conducted a comprehensive drug therapy review on test clients, then addressed issues with the client and/or the client's physician, with follow-up as required. Measurements included number of drugs, drug knowledge, adherence to therapy, cost of prescribed medicines, and number of reported symptoms obtained from a home medication history conducted by trained volunteers, the provincial prescription claims database, and response to a physician survey. Setting The pharmaceutical care model was situated within a community-based interdisciplinary health clinic targeting non-institutionalised elderly. Key findings One hundred and thirty-five clients were randomised to test (n=69) or control (n=66). A mean of 14.4 (SD 4.6) potential or actual issues were identified in test clients. Ninety-four per cent of physicians agreed with at least one of the pharmacist's recommendations but only 230 of 794 recommendations by the pharmacist (29 per cent) resulted in a change. There was no difference in overall number of prescribed or over-the-counter medications, drug costs, symptoms reported, drug knowledge or medication adherence between test and control groups post-intervention. Future research Further research is needed to identify barriers to changing drug use behaviour and facilitating acceptance of pharmaceutical care in the community.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".