A Systematic Review on the Effectiveness of Interventions to Improve Hand Hygiene Compliance of Nurses in the Hospital Setting
Bibliographic record
Abstract
PURPOSE: The purpose of the present systematic review is to identify the interventions that improve hand hygiene compliance (HHC) specifically among nurses. METHODS: A systematic review was performed guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to evaluate the short and long-term effects of interventions to promote hand hygiene practices among nurses in the hospital setting. A search of the Cumulative Index to Nursing and Allied Health Literature, Medline Global Health, and Embase was conducted in addition to studies identified by the most recent systematic review. Six studies met inclusion criteria: three randomized controlled trials (RCTs), one controlled before and after studies (CBAs), and two interrupted times series (ITS). FINDINGS: One RCT reported effectiveness and 6-month sustainability of the effect related to multimodal-directed and multimodal with team leadership-directed strategies. The other two RCTs found positive effect of education and feedback on compliance; however, compliance rates declined after 1 month. Education was also found to improve HHC up to 3 months postintervention. An electronic reminder and feedback system evaluated by an ITS improved HHC and detected variation in HHC through the day. CONCLUSIONS: This review showed that single and combined interventions do improve hand hygiene practices among nurses; however, there is a need for more methodologically robust studies to define the most effective and sustainable interventions. CLINICAL RELEVANCE: Although hand hygiene is the most effective measure to prevent healthcare-associated infections, compliance with hand hygiene remains low. Nurses are among the healthcare providers who spend the most time in direct patient contact. Therefore, there is a need for research to identify the interventions that improve HHC in this group.
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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 | 0.019 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".