Description

The causes of infectious hospitalisation, that is the infection of hospital patients, staff or visitors by germs, include a lack of hygiene and higher levels of residual contamination on surfaces with which patients come into direct or indirect contact in healthcare facilities (Knoll 2000). By taking appropriate measures it is possible to reduce the frequency of nosocomial infections – infections that occur during a hospital stay – by about one third (RKI 2000). To identify such appropriate measures, one must consider all the conceivable chains of transmission of pathogens (Boyce 2007). Contaminated or insufficiently clean surfaces can serve as a reservoir for microorganisms and therefore represent a potential path of transmission for nosocomial infections due to the long residence time of many pathogens. To counteract this, hygiene-safe solid surfaces should be used in hospitals. Solid surfaces are classed as being hygiene-safe when they can be easily and effectively cleaned over their entire lifetime. To assess this, one must consider the mechanical, chemical and physical effects acting on a material in the intended area of application. This article discusses the testing of different material surfaces over their product lifecycle to ascertain how their properties change as they age. Through an appropriate choice of materials, the risk of infection emanating from inanimate solid surfaces can be permanently reduced. This is a key hygiene measure alongside a suitable cleaning strategy, physical barriers and the implementation of an appropriate hand hygiene infrastructure.

Material ageing

The property of a material changes over its lifetime. In most cases, material ageing means a change in the material’s chemical composition and physical structure (Pongratz 2005). These chemical, physical and also mechanical ageing processes can be caused by various internal and external factors. The internal influencing factors are specific to the material and include its chemical composition or physical structure as well as possible additives. Each material thus reacts differently to the external influencing factors acting on it in the context of a healthcare environment to cause ageing. These external influencing factors are essentially:

chemical influencing factors (e.g. body fluids, disinfectants/cleaning agents, gases),

physical factors (UV radiation, temperature), and

mechanical factors (static and dynamic surface pressure, for example caused by rolling beds and trolleys).

Through the use of a specially developed artificial ageing programme, the key influencing factors can be simulated to determine the impact of material ageing on the cleanability of solid surfaces. To begin with, the initial conditions of the samples were first recorded before they were exposed to an artificial ageing programme that simulates the extreme boundary conditions found in hospitals in a time-lapse manner (Fig. 1). Firstly, the mechanical stresses caused by low or high mechanical abrasion were simulated. This was followed by artificial weathering, whereby UV radiation, temperature fluctuation and liquid acted on the material surfaces. Finally, the materials were chemically stressed by exposing them to low- or high-concentration disinfectant baths.

Methods

Cleanability refers to the ability of a solid surface to facilitate the removal of (particulate) contamination. Cleanability depends essentially on two surface properties: the shape deviation from an ideally smooth surface (roughness, R_a [µm]) and the wetting properties (surface free energy, γ_s [mN/m]). These parameters have the greatest influence on the interaction between contamination and a surface and thus the cleanability of a surface. The cleanability of surfaces can be described by the quantity of residual particle deposits P [-] after a defined soiling and cleaning process as follows

P = exp [ b_i R_ª+ b_j γ_s+ b_ij R_ª γ_s ] – k₀

where b [-] is a system-specific coefficient b [-] and k₀ = 0.1 is a constant. The higher the value of P, the more difficult it is to clean the surface.

Different coefficients (Fig. 2) result for different sizes of particulate contaminants and have a significant influence on cleanability (Dreßler 2018). This means that both an increase in roughness and an increase in surface free energy impair the cleanability of a surface. An increase in roughness in particular leads to a surface being less easy to clean effectively.

The solid surfaces tested were examined with a digital 3D laser scanning microscope to determine the surface profile or line roughness → Fig. 3 left. To determine the surface free energy, the progressive contact angle → Fig. 3 right of three liquids on the samples is determined from which the surface free energy is calculated.

Material

Elastic floor coverings made of rubber or polyvinyl chloride (PVC) as well as high-pressure laminates (HPL boards) were investigated (Fig. 4), all of which are commonly used for many surfaces in various areas in hospitals. Since they are used as flooring, laboratory worktops or the surfaces of patient headboards and furniture, patients, staff and visitors come into direct or indirect contact with them.

Alongside the material’s composition, the nature of its surface is also important, as this is directly exposed to external factors and consequently influences the durability of the polymer. An overview of the roughness and surface free energy properties of all the material samples prior to artificial ageing is given in (Fig. 5).

The various material groups exhibit different degrees of roughness with sample H5 exhibiting the highest and sample P1 the lowest roughness. This can be attributed to variations in the profile of the material surfaces. In general, all the tested material samples have a low surface energy compared to glass or metals and can therefore be described as low surface energy materials.

Results

The artificial ageing programme was employed to investigate the influence of material ageing on the cleanability of solid surfaces in the case of particulate contamination and the results were evaluated using the equation shown earlier. Physical factors (UV radiation, temperature fluctuations, liquid influence) caused the greatest changes in the surface properties, whereas hardly any changes resulted from mechanical abrasion. Chemical exposure to disinfectants – especially with long exposure times – intensified the ageing phenomena already present.

The artificial ageing programme was applied with exposure to different degrees of mechanical abrasion (high and low) and physical factors and immersion in a low-concentration and a high-concentration disinfectant bath. The resulting changes in line roughness and surface free energy of the sample surfaces before and after the artificial ageing programme are shown in (Figs. 6, 7). The changes of the respective property were normalised to be relative to the initial value. Since the material changes can be attributed to multifactorial influences, the changes in the parameters roughness and surface free energy caused by the artificial ageing programme are described using the example of the rubber sample K1.

The roughness of the rubber sample K1 decreases, which can be attributed to an oxidative ageing process, which manifests itself for example in chalking or microcracks. The removal of the chalking pigments through cleaning processes during the measurements led to a reduction in roughness. The oxidative ageing process also causes an increase in the surface free energy and thus the wettability of K1. The low-concentration disinfectant bath also appears to have a greater effect on the surface free energy of K1 compared to the high-concentration disinfectant bath.

Residual particle quantity and cleanability

The residual particle quantity P
^ˆ

of the individual samples before and after the artificial ageing programme is shown in (Fig. 8) for the particle size group 0.5 < d ≤ 1.0 µm. In this case the before and after results are shown without the individual effects of the mechanical abrasion and the different disinfectants. On average, the residual particle quantity of all material groups increases, which means the materials are more difficult to clean than before artificial ageing.

The samples H1 and H2, in particular, exhibit a significant increase in the quantity of residual particles and are therefore the most difficult to clean in comparison. Samples P1 and H4 have the best cleanability in comparison despite the increase in the quantity of residual particles.

Conclusion

The test showed that the mechanical, chemical and physical influences common in healthcare facilities do affect the (surface) properties of materials, resulting in a change in their cleanability properties and in turn in the risk of possible infection caused by surface contamination. Depending on the combination of influences, this need not necessarily mean a deterioration of the properties. Each hospital operator must decide what they deem to be an acceptable measure of change. Where possible, hospitals should select materials that change as little as possible in the expected conditions they are exposed to. In this study, those materials were PVC or HPL boards with a corresponding supplementary surface coating.

References

J. M. Boyce, “Environmental contamination makes an important contribution to hospital infection”, Journal of Hospital Infection, 65, 2007, pp. 50–54

Inka Dreßler, Hygienesichere Oberflächen im nicht-­immergierten System, PhD thesis, Technische Universität Braunschweig, 2018

Karl Heinz Knoll, Hygiene in Gesundheitseinrichtungen. Planung – Anlage – Bau – Ausstattung – Betrieb, Stuttgart: Wissenschaftliche Verlagsgesellschaft, 2000

Robert Koch Institut (RKI) and Statistisches Bundesamt, 2000, Nosokomiale Infektionen – Gesundheitsbericht­erstattung des Bundes. Vol. 8, 2000

Sonja Pongratz, Die Alterung von Thermoplasten, post-doctoral thesis, Friedrich-Alexander Universität Erlangen-Nürnberg, 2005

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Originally published in: Wolfgang Sunder, Julia Moellmann, Oliver Zeise, Lukas Adrian Jurk, The Patient Room, Birkhäuser, 2020.