When is Clean, Clean?
Research type
Research Study
Full title
When is clean, clean? The impact of evidence-based clinical decontamination strategies on infection prevention and control practice in an NHS hospital and its implications for the National Cleaning Standards of NHS Wales and England
IRAS ID
332262
Contact name
Sarah Fieldhouse
Contact email
Sponsor organisation
Staffordshire University
Duration of Study in the UK
3 years, 0 months, 1 days
Research summary
Effective cleaning of clinical environments is essential to reduce and remove contagious and infectious microorganisms, including multidrug-resistant microbes, which contribute to nosocomial infection.
Visual inspections infer cleanliness, but financial and resourced practicalities with exhaustive environmental monitoring often limit further investigation. Bioburden often exists in a latent state; therefore, cleaning practice relies on surface area saturation and assumptions of cleanliness. The ability to visualise bioburden and understand factors that prevalently contribute to the presence and distribution of infectious microorganisms could transform the way that clinical environments are cleaned and contribute to the ‘prevention’ and ‘control’ of Healthcare Acquired infections (HAI’s).
Prior research has demonstrated the efficacy of a forensic light source for bioburden detection in an NHS hospital. The method enabled more ATP containing substances to be detected than current practice speculative ATP testing, attributable to its ability to screen larger areas in real time, and the fact that many substances fluoresce, including most body fluids that may contain and enable infection transmission.
This research shall statistically examine observational fluorescence data using the light source, ATP, microbiological and Fourier Transform Infrared Spectroscopy data from a strategic sample of National Cleaning Standard objects across a hospital footprint.
A random cross-sectional sample of the selected objects shall be screened with the light source prior to patient use, and statistically analysed for differences with control (non-screened objects). Artificial Intelligence (AI) data modelling shall visually explore the data alongside hospital generated infection statistics, including ward infection rates, patient pathway information and operational factors, such as cleaning mode, time since cleaning, likely human contact at the point of analysis, and object movement (through the hospital).An expert stakeholder group shall map the data against the current National Cleaning Standards and consider the contribution of the research data in the development of best practice cleaning guidance.
REC name
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REC reference
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