Interventions to Reduce Benzodiazepine and Sedative-Hypnotic Drug Use in Acute Care Hospitals: A Scoping Review
Bibliographic record
Abstract
Abstract Background Benzodiazepines and sedative-hypnotics (BZD/SHD) are commonly utilized in the acute care setting for insomnia and anxiety and are associated with cognitive impairment, falls, fractures, and increased mortality. Interventions to reduce use of BZD/SHD in hospitals are not well characterized. The objective of the scoping review was to identify and characterize interventions to reduce the use of BZD/SHD by adults for anxiety and sedation in hospitals.Methods We included studies and abstracts published in English that described an intervention to reduce BZD/SHD in adult hospital patients. Six databases (PubMed, EMBASE, CINAHL, PsycINFO, Scopus, and Web of Science) and the grey literature (Opengrey, Grey Matters, Google Advanced) were searched up to July 2018. Titles and abstracts were screened and full-text articles were reviewed for potential inclusion by three independent reviewers. Data on each eligible study was charted in a Microsoft Excel® database. Stakeholder consultation occurred before and after the scoping review was completed. Results There were 9480 records identified from all sources and 35 studies were included in the scoping review. Included studies were divided into two categories that emerged from stakeholder feedback: sedatives prescribed in hospital or home medications. The most common study designs were pre-/post-test (24, 68.6%) and randomized controlled trials (6, 17.1%). The majority of studies tested a single intervention (28, 80%) and these were most commonly education, relaxation training and sleep protocols. Patients were frequently the target of relaxation training and behavior change interventions, while sleep protocols, multifaceted interventions and education were usually directed at healthcare providers, either alone or in combination with patients. Most studies reported positive outcomes in decreasing BZD/SHD use (23, 65.7%), including some that were statistically significant (13, 37.1%). Conclusions This scoping review found a variety of interventions aimed at decreasing the utilization of BZD/SHD in the acute care setting, where previously little was known. Current literature addressed the initiation of BZD/SHD in hospital, rather than chronic medications that had been prescribed in the community. Stakeholder consultation supported these findings and pointed out important factors to consider when designing an intervention for hospital patients. Registration: Open Science Framework, https://osf.io/u7s4h/?view_only=15a9b9134be743b6a4177ba2eec9e91a
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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 | 0.020 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".