Routinely implementing safe deprescribing in primary care: a scoping review
Bibliographic record
Abstract
Abstract Introduction Polypharmacy, the use of ≥5 medicines, continues to increase worldwide and can become problematic potentially leading to adverse drug reactions (ADRs) and poor patient outcomes. Deprescribing - discontinuing medicines where harms outweigh benefits (1) - can help minimise problematic polypharmacy. Although deprescribing is effective in stopping medicines it has not been routinely incorporated into practice, with a lack of evidence on how deprescribing can be implemented in primary care. The support and education patients require and the training that clinicians need, must be established to effectively implement routine safe deprescribing in primary care. This scoping review was conducted to identify research gaps and determine the value of undertaking a systematic review on the barriers and facilitators of implementing deprescribing in primary care. Aim Methods The Arksey and O’Malley framework for scoping reviews was used (2). The Cochrane Library, PubMed, Embase, MEDLINE, Web of Science and International Pharmaceutical Abstracts were searched from 1996 – February 2020. Additional references were identified from reference lists of included articles. Abstracts and titles were screened and potentially relevant articles received full text screening. Inclusion criteria were quantitative, qualitative and mixed-methods literature on deprescribing in primary care. The exclusion criteria were conference papers, non-English language papers and literature on palliative care/life-limiting illness, patient self-discontinuation, withdrawal of medicine due to ADR, substance misuse, and long-term care facilities. For intervention studies; country, study design, aims, population, intervention, education used, follow-up used and findings were collected. For non-interventional studies; study design, aims, population and themes identified were collected. For the deprescribing trials, barriers and facilitators to implementing the intervention were identified. Results 4612 articles were identified and 72 articles included (32 intervention studies; 40 non-intervention). The majority of articles were from the Netherlands (15), Canada (13), USA (10), and UK (seven). Study designs included 12 RCTs, 11 quasi-experimental studies, six follow-up papers, three protocols, 19 surveys studies, eight interview studies, two observational studies, a meta-ethnography, a Q-methodology study, a process evaluation and eight narrative reviews. Five studies documented providing patient support post-deprescribing with little description of what this consisted of. The provision of patient education or clinician training was used in 14 studies. Six of seven studies incorporating patient education into their intervention were able to safely deprescribe for a significant proportion of patients. Research on the barriers and facilitators to implementing deprescribing into primary care was not routinely reported with a greater focus on the process of deprescribing, rather than implementation. Conclusion There is a paucity of research on the fundamental characteristics required for deprescribing to be routinely and safely implemented in primary care. There is a lack of description on what type of education and support patients need, and training that clinicians require, for routine safe deprescribing. Future research is needed to identify and address these factors for the benefits of deprescribing to be realised. References (1) Scott IA, Hilmer SN, Reeve E, Potter K, Le Couteur D, Rigby D, et al. Reducing Inappropriate Polypharmacy: The Process of Deprescribing. JAMA Internal Medicine. 2015;175(5):827-34. (2) Arksey H, O’Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1):19-32.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".