- Start date: 1 September 2017
- End date: 31 May 2022
- Funder: Engineering and Physical Sciences Research Council (EPSRC)
- Value: £1,025,622
- Partners and collaborators: NHS Lanarkshire, Monaghans, Apex 4D Ltd, Leeds Teaching Hospitals NHS Trust
- Primary investigator: Professor Catherine Noakes
- Co-investigators: Dr Marco-Felipe King, Dr Andrew Kemp, Dr Louise Fletcher, Dr Andrew Sleigh, Dr Amirul Khan
Hospital buildings are critical for supporting effective patient treatment. There is strong evidence that the design of patient environments influences well-being and comfort, recovery rates and can both cause and control transmission of infections, particularly those with an airborne component.
Recent surveillance in England estimates 6% of patients a year contract an infection while in hospital, which with hospital admissions of 15.9 million, totals almost 1 million people. Around 20% of infections are thought to be directly related to the environment. Hospital buildings have not progressed at the same rate as medical advances and many clinicians are treating patients in sub-optimal conditions. In addition, recent scrutiny of healthcare buildings has been dominated by a focus on their energy usage, and there is increasing concern that decisions are made on energy and cost efficiency grounds without proper understanding of the risk to patients. This is counter-productive; efficiency savings in buildings leads to increased risks and hence costs in clinical delivery.
With the NHS commitment to reduce recurrent revenue costs in supporting the reduction of the national £22bn funding shortfall, it is essential that buildings are considered holistically and that the influence on patient outcomes is properly factored in. A major barrier to delivering good patient environments is having usable tools to assess risks and adapt the environment and operations in a responsive manner. Current tools for designing and operating healthcare buildings and selecting technology are good at modelling energy but are very limited from a health and infection control perspective. Our previous research developed new methods for modelling hospital environments and their influence on infection risk.
In this project, we aim to build on these approaches to develop and test novel computational based tools to assess, monitor and control real patient environments in hospitals for infection control, comfort and well-being. We will develop and couple models of physical, environmental, microbial and human parameters together with environmental sensor data to build new tools to dynamically model hospital environments. These will focus on addressing challenges with existing wards which are often constrained by the current building design and in many cases are naturally ventilated via opening windows.
We will build a system that links sensors with a real-time fluid dynamics simulation model to enable live monitoring of environmental conditions and allow predictions to be made for rapid adaption. This will inform and control aspects like window opening, heaters and additional cooling to optimise the patient environment for comfort and air quality parameters. Alongside this, we will develop a quantitative pathogen exposure model that can enable a comparison of the relative risk of air and surface transmission and the likely effectiveness of different design and infection control strategies. This tool will support decision making and scenario testing, as well as provide a valuable interactive training tool to demonstrate the interactions between pathogens, people and the physical environment.
The project has significant interaction with clinicians who manage complex ward environments and a wide range of patients, and expertise in industry, in the design, specification and operation of hospitals. We will develop and test our approaches on real wards to understand their challenges, measure variability in conditions and evaluate how and where our models can best be used to inform practice. By working closely with industry partners we will understand how our pilot tools can be deployed in design and estates management and where they may inform guidance and governance. The project will deliver new risk-based ways of assessing healthcare environments that support decisions, training, design and future guidance.
The hospital environment is a very significant element in providing safe and effective care and treatment to patients. The NHS estate comprises over 28 million square meters of buildings, over 300 acute hospital sites, and around 75% of it is over 20 years old. Hospitals spend millions of pounds every year on operating and maintaining these environments. Providing a good indoor environment for patients is a daily challenge for many hospitals and with a finite budget understanding how and where to invest in the environment is a key concern.
Infection control is a key factor in the decision making, yet the tools to support the link between the environment and health are limited. By exploring these relationships and developing new tools to monitor the environment and quantify risk, the project will bring significant benefits to a number of stakeholders. Hospitals and their patients are the major beneficiaries, bringing both economic and societal benefits.
Our partner hospitals will be the first to benefit from detailed data on the operation of their wards and models and tools applied to explore their particular challenges. It is anticipated that this will enable the clinical and estates teams to take action during the project timescale to adapt their environments or change their management processes.
Beyond the project, it is anticipated that these benefits will extend to other areas of the partner hospitals and bring similar knowledge to other hospitals. The outcomes from the research will assist in monitoring their environments in real time and to carry out decision making and scenario planning to support investment. This brings ultimate benefits to patients by reducing their risks of infection while in hospital and creating environments that better support their health and well-being.
Impact on industry and hence the economy lies firstly with the partners in the application of the models to future healthcare design, planning and maintenance projects as well as in the future development of tools for commercial application by others. Those who could benefit include the manufacturers of ventilation and infection control technologies, those who design buildings, the construction sector who retrofit healthcare buildings and Internet of Things (IoT) device manufacturers and installers.
The latter is potentially a significant new opportunity; the experience gained from the project could generate a new market and provide a platform for the predicted IoT revolution to gain traction especially in the healthcare sector. Economic beneficiaries also include government, professional bodies and policy makers, through the potential to provide new guidance for considering infection control and health aspects in hospital buildings. These include the Department of Health, NHS England, Care Quality Commission, PHE and bodies such as IHEEM and HIS who prepare standards and guidance and make recommendations. Beneficiaries also include the people who are directly impacted by the research programme: investigators, postdoctoral researchers, partners and associated students. There are wider public benefits through increasing understanding of the influence that buildings have on health and well-being.
Publications and outputs
Al-Kashoash H (2018) Congestion control in wireless sensor and 6LoWPAN networks: toward the Internet of Things in Wireless Networks
King MF (2020) Bacterial transfer to fingertips during sequential surface contacts with and without gloves in Indoor air
King MF (2020) Why is mock care not a good proxy for predicting hand contamination during patient care? In The Journal of hospital infection
López-García M (2019) A Multicompartment SIS Stochastic Model with Zonal Ventilation for the Spread of Nosocomial Infections: Detection, Outbreak Management, and Infection Control. In Risk analysis: an official publication of the Society for Risk Analysis
Wilson AM (2020) COVID-19 and use of non-traditional masks: how do various materials compare in reducing the risk of infection for mask wearers? In The Journal of hospital infection
2020 N. Salman, A. H. Kemp, A. Khan, C. Noakes, “Indoor Air Quality Forecast based on the Lattice Boltzmann method and 3D-Var Data Assimilation,” IndoorAir 2020, S. Korea
2020 N. Salman, A. H. Kemp, A. Khan, C. Noakes, “Wireless Sensor Network (WSN) Based Data Assimilation in Indoor Environments for Accurate Lattice Boltzmann Real-Time Indoor Air-Quality Prediction,” IndoorAir 2020, S. Korea.
2020 N. Salman, A. H. Kemp, A. Khan, C. Noakes, “Indoor Thermal Comfort Forecast based on the Lattice Boltzmann method and 3D-Var Data Assimilation,” Roomvent 2020, Italy.
2019 N. Salman, A. H. Kemp, A. Khan, C. Noakes, “Real Time Wireless Sensor Network (WSN) Based Indoor Air Quality Monitoring System,” 5th IFAC Symposium on Telematics, Chengdu, China.
W. Hiwar, M-F King, Farag Shuweihdi, L. A. Fletcher, S.J. Dancer, C.J. Noakes (2021). What is the relationship between indoor air quality parameters and airborne microorganisms in hospital environments? A systematic review and meta-analysis. Journal of Indoor Air. https://doi.org/10.1111/ina.12846