Language used to describe medication review activities: does it require standardisation? A narrative synthesis
Bibliographic record
Abstract
Abstract Introduction Medication review (MR) is a health care professional’s systematic assessment of a patient’s medications with recommendations for improvement (1). To enable comparison between different evaluations of medication review-based interventions to determine whether the nature of activity differs, it is important that standardised language is used. Currently, there is no accepted international taxonomy for describing medication review activities. Therefore, we undertook a systematic review of literature with narrative synthesis to determine whether standardisation may be appropriate. Aim To determine the range of terms used to describe medication review activities. Method A PROSPERO registered systematic review (CRD 42020215992) was performed using search terms according to the Population, Intervention, Comparison and Outcome (PICO) framework. ‘Population’ & ‘Comparison’ were not used. Synonyms for medication review activities were used for both ‘Intervention’ and ‘Outcomes’, e.g., stop, start, change, alter. We included all papers reporting medication review activities in English with empirical data. Papers not using language to describe medication review activities were excluded. Two researchers reviewed all titles, abstracts, and full-text papers independently; discussion resolved any disagreement. Data extraction was carried out independently as per Cochrane Effective Practice and Organisation of Care (EPOC) as follows: The papers were assessed using the Mixed Method Appraisal Tool (MMAT). The research team themed the extracted terms. Results After deleting duplicates, 9746 titles were screened. Twenty-one studies were included: eight quantitative non-randomised trials, eight randomised controlled trials, and five quantitative descriptive studies. The studies covered the UK, Netherlands, Australia, Sweden, Norway, Belgium, Canada, and Jordan. The table summarises the medication review activities reported in these papers. Conclusion Various authors reported medication review activities. ‘Alter’ and ‘adaptation’ are examples of ambiguous terms. Determining whether actions are related with activities to reduce or increase doses is difficult due to such terminology. As a result, comparing medication review approaches may be difficult. Limiting the search strategy to English-language only may have missed some studies. A taxonomy to describe and define medication review activities, thereby standardising MR reporting, should improve the presentation of data from process evaluations and the ability to compare activity between studies. Reference (1) Christensen M, Lundh A. Medication review in hospitalised patients to reduce morbidity and mortality. Cochrane Database Syst Rev [Internet]. 2016 Feb 20; Available from: https://doi.wiley.com/10.1002/14651858.CD008986.pub3
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".