ReviewCurrent treatment options in infectious diseases2017
Role of Human Factors Engineering in Infection Prevention: Gaps and Opportunities.
Review in Current treatment options in infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 18 citations in OpenAlex.
- Impact of infection prevention and control quality improvements in haemodialysis facilities: a scoping review.BMC nephrology · 2025Article
- Streamlining Preparedness: A Practical Pathway to Special Pathogens Management.Tropical medicine and infectious disease · 2025Article
- Connecting pathogen transmission and healthcare worker cognition: a cognitive task analysis of infection prevention and control practices during simulated patient care.BMJ quality & safety · 2024Article
- The use of procedural kits may reduce unscheduled central line dressing changes: A matched pre-post intervention study.Journal of infection prevention · 2024Article
- Implementing strategies to prevent infections in acute-care settings.Infection control and hospital epidemiology · 2023Article
- Applying eHealth for Pandemic Management in Saudi Arabia in the Context of COVID-19: Survey Study and Framework Proposal.JMIR medical informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Human factors engineering (HFE), with its focus on studying how humans interact with systems, including their physical and organizational environment, the tools and technologies they use, and the tasks they perform, provides principles, tools, and techniques for systematically identifying important factors, for analyzing and evaluating how these factors interact to increase or decrease the risk of Healthcare-associated infections (HAI), and for identifying and implementing effective preventive measures. We reviewed the literature on HFE and infection prevention and control and identified major themes to document how researchers and infection prevention staff have used HFE methods to prevent HAIs and to identify gaps in our knowledge about the role of HFE in HAI prevention and control. Our literature review found that most studies in the healthcare domain explicitly applying (HFE) principles and methods addressed patient safety issues not infection prevention and control issues. In addition, most investigators who applied human factors principles and methods to infection prevention issues assessed only one human factors element such as training, technology evaluations, or physical environment design. The most significant gap pertains to the limited use and application of formal HFE tools and methods. Every infection prevention study need not assess all components in a system, but investigators must assess the interaction of critical system components if they want to address latent and deep-rooted human factors problems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.