Evaluation of an enhanced service for medication review with follow up in Swiss community pharmacies: Pre-post study protocol
Bibliographic record
Abstract
BACKGROUND: In Switzerland, 20,000 people are hospitalized each year as result of drug related problems (DRPs). The sources of DRPs can be related to patients' behavior (i.e., wrong administration) or to health processes (i.e., drug-drug interaction). No community pharmacy (CP) service focus on DRPs related to patients' behavior is currently recognized or remunerated in Switzerland. A medication review with follow up (MRF) has been developed to evaluate prescription and non-prescription medication. OBJECTIVE: To evaluate the impact of MRF service for the identification and management DRPs associated to patients' behavior and to describe pharmaceutical interventions carried out through MRF. METHODS: A pre-post intervention study with a cluster design and one intervention group will be carried out in CPs in the canton of Vaud (Switzerland) for 15 months. Volunteer pharmacists will be trained on the identification and management of DRPs related to patients' behavior. After training, they will include randomly selected adults taking four or more chronic drugs prescribed for at least three months prior to recruitment. Then, they will conduct three pharmacist-patient face-to-face consultations at 6-month intervals. Tasks will be differentiated by pharmacy technician or pharmacist to triage expired medication or to manage DRPs in a structured manner, respectively. The primary outcome is the identification of DRPs associated to patients' behavior. Secondary outcomes are to assess patients' medication knowledge, number of expired medications, interventions carried out by pharmacists and pharmacists' satisfaction. The study will begin in April 2023 in 19 to 35 pharmacies that will recruit at least 162 patients. A sub analysis will be carried out for patients with 65 years old or over. CONCLUSIONS: The MRF intervention features a training designed for an enhanced evaluation of patient's behavior towards their medication. The study will allow the assessment and management of DRPs in Swiss CPs with the support of the local health authorities and pharmacist association. TRIAL REGISTRATION: Clinicaltrials.gov NCT05348538.
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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 | 0.036 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
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".