The unseen risk from the previous room occupant

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It is clear that sharing a room or multi-occupancy bay with a patient infected or colonised with an HCAI-related pathogen is a risk factor for acquisition. Indeed, the physical segregation of patients has been a key intervention to prevent the spread of infectious diseases since the advent of germ theory! The risk of acquiring pathogens from contamination left behind by a previous occupant of the same room or bed-space is less obvious, but one that is now widely recognised. However, which is greater? The risk from a current roommate, or the risk from a previous occupant of the same bed-space? Whilst you may think it would be the current roommate, a new study suggests that the risk from the previous room occupant may be greater!

The American research team performed a large case-control study, in a population of 760,000 patients across four hospitals in New York between 2006 and 2012. More that 10,000 patients developed an HCAI during this period, and these cases were matched with uninfected controls based on time, location, and length of stay. The key finding was that both exposure to a roommate or a previous room occupant with the same pathogen that caused the HCAI were risk factors for HCAI. Interestingly, exposure to a current room occupant increased the risk of HCAI 5-fold, whereas exposure to a previous room occupant increased the risk of acquisition 6-fold! Whilst the study was not designed to compare directly the increased risk from current roommates with previous room occupants, this finding suggests that exposure to a previous room occupant could be a greater risk for HCAI than exposure to a current roommate. One possible reason for this is that a current roommate with an HCAI is a more obvious, tangible risk for transmission, and so basic IPC practice and cleaning standards are higher. In contrast, a previous room occupant is an unseen risk, so cleaning standards are lower.

These findings reinforce the need to improve cleaning and disinfection of the clinical environment both during the stay of patients, and at the time of discharge to minimise the risk of HCAI.

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Multi-occupancy bays as a risk factor for norovirus spread

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Norovirus is a common cause of gastrointestinal diseases in hospitals and other ‘semi-closed’ environments (like cruise ships, prisons, and schools). A new study suggests that wards whether patients share multi-occupancy bays are more likely to experience norovirus outbreaks, and that the risk of norovirus transmission increases as more patients share a bay.

The factors driving norovirus transmission are poorly understood. This is because designing studies in norovirus transmission is difficult. Norovirus usually spreads in outbreak clusters, which are often contained using bundled interventions. So, it’s very difficult to understand which part of the bundle was effective in containing an outbreak – or, indeed, whether an outbreak would have stopped without any intervention at all! A new Swedish study reviewed outbreaks and a large number of sporadic norovirus cases in almost 200 wards across southern Sweden to understand risk factors for norovirus spread.

The study found that risk factors for norovirus transmission were: sharing a multi-occupancy with a norovirus case, vomiting, older age (>80 years), comorbidity, and hospital onset of symptoms. These factors remained significantly associated with norovirus transmission even when accounting for all variables together in a multivariable model. The more patients who shared a multi-occupancy bay, the greater the risk of norovirus spread: in fact, the risk doubled for each extra patient in the bay!

These findings suggest that improving the segregation of patients who become symptomatic with norovirus-like symptoms will help to prevent the spread of norovirus in hospitals.

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Sporicidal disinfection should be the basis of all bundles to prevent C. difficile infection

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Since the evidence base is limited, knowledge on what really works to prevent the transmission of pathogens that cause HCAI is limited. This is the case for C. difficile and other hospital pathogens. So, we commonly apply bundles of interventions, in the hope that one or more elements of the bundle will be effective. A recent modelling study helps us to break down the bundle to understand which elements are most effective for preventing C. difficile infection. Daily cleaning with a sporicidal disinfectant was the most effective intervention, reducing hospital-onset C. difficile infection by two thirds.

The study created a virtual 200 bed acute care hospital and modelled how 9 single interventions and 8 intervention bundles interrupted the spread of C. difficile between patients. The interventions and intervention bundles were either hospital-centred (e.g. daily or terminal cleaning, contact precautions for staff, and staff hand hygiene) or patient-centred (e.g. screening for asymptomatic colonisation or patient hand hygiene). Six of the interventions had some degree of effectiveness in reducing C. difficile infection: daily and terminal cleaning, staff hand hygiene, patient hand hygiene, screening at admission, and patient transfer reduction. Surprisingly, contact precautions for staff made little impact on transmission in this model. Daily cleaning with a sporicidal disinfectant was the most effective single intervention, reducing C. difficile infection by 69%. Implementing screening to detect asymptomatic carriers was also effective, reducing C. difficile infection by 36%. All of the bundles tested reduced C. diffiicle infection, but the most effective bundle was daily cleaning with a sporicidal disinfectant combined with screening for asymptomatic carriage, which would reduce C. difficile infection by 82%. Adding staff hand hygiene and patient hand hygiene would reduce C. difficile infection further.

The main problem with a modelling study like this is that it stands or falls by the quality of the data used to parameterise the model. If the parameters for the variables going into the model are inaccurate, the findings will be unreliable – and incorrect parameter values going into the model can be compounded by the calculations to give very odd findings! In this case, however, there’s a lot of experimental data on the impact of daily and terminal cleaning relating to C. difficile, so the outcomes of the model relating to cleaning are probably reliable. There is considerably less data on the impact of screening for C. difficile asymptomatic colonisation, so outcomes related to this intervention are probably less reliable.

Overall, the modelling study supports that an intervention bundle is the best approach to preventing C. difficile infection, and that daily and terminal disinfection with a sporicidal agent should be the fundamental component of all C. difficile prevention bundles, which is reflected in the latest European guidelines.

 

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UV-C room disinfection reduces viral infection

There is now strong evidence that UV-C room disinfection reduces the transmission of key bacterial pathogens in hospitals, including MRSA, VRE, and perhaps to a lesser degree, C. difficile infection. A new study demonstrates that UV-C room disinfection using GAMA’s Violet UV-C room sanitiser also reduced viral infection.

The study was performed is a fairly small 100 bed paediatric long-term care facility in the USA. The study had a before-after design, with UV-C implemented for 12 months in 2016 and viral infection rates compared with historic rates of virus infection in the unit over the 12 months prior to implementation. Unlike other studies, UV-C was not used at the time of patient discharge to enhance terminal disinfection. Instead, UV-C was deployed on a rolling disinfection programme so that the rooms considered at highest risk were disinfected using UV-C 2-3 times a week, and common areas were disinfected 3 times per week.

A 44% reduction in the incidence of viral infection was achieved during the 12 month intervention (50.3 vs. 82.0 viral HCAIs per 10,000 patient days) (see the Figure below). One interesting finding was that there seemed to be a cumulative effect of UV-C, suggesting that the regular programme of UV-C disinfection ‘chipped away’ at long standing environmental contamination, resulting in a gradual decrease in viral infection incidence.

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Figure: Cumulative viral rate in the months before UV-C use began (blue) vs. the first 12 months of UV-C use (purple)
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Crucially, no other interventions were made, and there were no changes to infection prevention and control practices on the unit. This suggests that the observed reduction in viral infection rates was due to the implementation of UV-C. These findings suggest that a rolling programme of UV-C patient room and common area disinfection should be considered to reduce viral infection.

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Getting real with disinfectant concentration and contact time

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The processes in place for establishing whether a hospital disinfectant is suitable for use in a clinical setting have been around for a long time – but do they remain fit for purpose? A recent study shows that disinfectant concentration and contact time can be reduced without negatively affecting efficacy – but not too much!

Tests with unrealistically long contact times, high concentrations of disinfectant, and performed in suspension rather than on a hard substrate are not helpful in establishing whether a disinfectant is suitable for use in the clinical setting. Equally, laboratory disinfectant testing needs to be performed with a worst-case scenario in mind. A recent study ‘stress tested’ the parameters for the laboratory testing of a selection of hospital disinfectants, reducing the disinfectant concentration and contact time. The disinfectants tested were accelerated hydrogen peroxide, quaternary ammonium compounds (QACs), and sodium hypochlorite. There was a degree of tolerance to reducing contact time and disinfectant concentration. The study found that bactericidal efficacy was not reduced when contact times or concentrations were reduced to just below label use values. However, all of the disinfectants were significantly less bactericidal when contact times and concentrations were reduced substantially. The sodium hypochlorite was most tolerant to changes in contact time and concentration.

This study is useful and suggests that contact times and disinfectant concentrations could be reduced in some settings. However, there are many drivers of the efficacy of a disinfectant, including soiling, the presence of biofilms, and stability of the disinfectant. Therefore, laboratory studies need to be complemented by real-world studies in the clinical setting to establish the suitability of disinfectants for surface disinfection in hospitals.

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