Visualising infection transmission routes in order to identify, monitor and prevent antimicrobial resistant infection
Lead Research Organisation:
Imperial College London
Department Name: Dept of Medicine
Abstract
Healthcare-associated infection (HCAI), and specifically antimicrobial resistance (AMR) is one of the most pressing threats to global public health. The rapid worldwide emergence of AMR may render antibiotics, one of the greatest advances in medicine, obsolete. Approximately 700,000 people die annually as a result of multi-drug resistant bacterial infections; a figure which is estimated to rise to 10 million by 2050. Concurrently HCAIs are the most frequently encountered adverse event to threaten patient safety, affecting 4 million patients in the EU annually and causing an estimated 16 million additional bed-days. A reduction in HCAIs would aid in conserving the use of antibiotics, and therefore curb the spread of AMR in healthcare settings.
Estera's proposed research aims to to develop a tool for tracking and visualising infections throughout a healthcare system. Acquiring and analysing timely data which allows the mapping of infection sources and visualisation of transmission routes is a key component of effective responses against AMR. This information can be used to dissect disease spread at an individual-to-individual level, and develop a quantitative evidence base for decision making. A specific area where this can be readily applied is the patient journey through a hospital network. During hospitalisation, patients visit many procedural and diagnostic common areas, presenting opportunities for transmission of infection. However, these potential exposures are not typically captured in analyses evaluating disease transmission. The proposed study will aim to use electronic health record data and in-silico simulations in order to study infectious disease outbreaks and hospital performance on key healthcare quality metrics.
Visualisation of these pathways will inform quantitative modelling of HCAI transmission, which will facilitate intervention development and targeting of infection control measures. Ultimately this will enable monitoring, feedback and decision making within hospitals.
Estera's proposed research aims to to develop a tool for tracking and visualising infections throughout a healthcare system. Acquiring and analysing timely data which allows the mapping of infection sources and visualisation of transmission routes is a key component of effective responses against AMR. This information can be used to dissect disease spread at an individual-to-individual level, and develop a quantitative evidence base for decision making. A specific area where this can be readily applied is the patient journey through a hospital network. During hospitalisation, patients visit many procedural and diagnostic common areas, presenting opportunities for transmission of infection. However, these potential exposures are not typically captured in analyses evaluating disease transmission. The proposed study will aim to use electronic health record data and in-silico simulations in order to study infectious disease outbreaks and hospital performance on key healthcare quality metrics.
Visualisation of these pathways will inform quantitative modelling of HCAI transmission, which will facilitate intervention development and targeting of infection control measures. Ultimately this will enable monitoring, feedback and decision making within hospitals.
People |
ORCID iD |
| Ceire Costelloe (Primary Supervisor) | |
| Emanuela Estera Boncea (Student) |
Publications
Boncea EE
(2021)
Association between intrahospital transfer and hospital-acquired infection in the elderly: a retrospective case-control study in a UK hospital network.
in BMJ quality & safety
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| ES/P000703/1 | 30/09/2017 | 29/09/2027 | |||
| 2110267 | Studentship | ES/P000703/1 | 30/09/2018 | 31/12/2022 | Emanuela Estera Boncea |
| Description | In the first year of my doctoral funding, I focused on building the evidence base that the patient journey through a hospital network influences the odds of an individual developing a hospital acquired infection. This led to a publication in the BMJ Quality and Safety and a conference presentation at the World Congress on Public Health 2020, which demonstrated that an association between patient movement and infection does exist in elderly patients, with each additional ward transfer increasing the odds of infection by 9%. The article was well received, being cited in a new editorial in the same journal on the topic of healthcare-associate infections and achieving a high altmetrics score (a social media engagement and online attention measure), which placed it in the top 10% of articles ever published, as well as above average for articles published solely in the BMJ Quality and Safety within a similar time frame. Feedback on the publication has highlighted the importance of accounting for different types of patient movement within the hospital, helping to refine a new research question focussing on characterising the complexity of patient movement trajectories and understanding how different patterns of transfers may be linked to adverse events including and beyond the risk of infection. In the second year of my funding, I used network analysis, a novel tool within the public health discipline, to explore 'communities' of patients who move in similar patterns. I developed a data-driven approach to exploring the impact of patient movement by considering hospitals as complex systems, and characterising some patterns of movement as 'routine' while others as 'atypical'. I observed a relationship between ward-transfers and longer length of stay, which is greater for patients which move through atypical pathways. Such transfers happen across different clinical specialities and geographical locations in hospitals. It is possible that atypical transfers are due to bed shortages, and a lack of coordination and communication between the unrelated clinical speciality wards leads to delays in care. Further research is needed to confirm the possible causes behind such patient movements, in order to better inform recommendations for hospital managers overseeing patient flow. |
| Exploitation Route | Identifying and characterising the mechanisms behind differing pathways of patient movement, and their impact on patient outcomes will be relevant to hospital managers and healthcare staff responsible for optimising the organisation of hospital services. The work is also relevant for informing model parameters for future modelling of patient movement. The knowledge generated will help to create new interventions for patient flow management and in the longer term can be applied to informing hospital design. |
| Sectors | Communities and Social Services/Policy,Healthcare,Government, Democracy and Justice |
| URL | https://qualitysafety.bmj.com/content/early/2021/01/31/bmjqs-2020-012582 |
| Description | MRF training |
| Geographic Reach | National |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | The course was attended by around 50 PhD students. Feedback from the students reflected that the course had been useful in giving insights on how to generate research questions in AMR from a multidisciplinary perspective. |
| Description | Global Fellows Programme 2021 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | I took part in a weeklong programme attended by approximately 40 doctoral researchers from Nanyang Technological University, Technical University of Munich and Imperial College. Its purpose was to develop professional, research and collaborative competencies as well as the intercultural awareness required to establish international collaborations. The objective of the programme was for teams to bring their subject specialist knowledge together in order to develop collaborative research ideas around the topic of 'Health data and technology for society'. This initiated a lot of discussion about our own research and how we may foster collaborations in the future. |
| Year(s) Of Engagement Activity | 2021 |
| Description | Imperial College School of Public Health Research Symposium |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Postgraduate students |
| Results and Impact | The School of Public Health at Imperial College London hosts an annual Research Symposium which allows students the opportunity to present and review work amongst peers and academics from across the School. I gave a presentation about my recent PhD research and was awarded a third place prize for my work. |
| Year(s) Of Engagement Activity | 2021 |
| Description | NIHR Research Day |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Undergraduate students |
| Results and Impact | Research open day showcasing the Global Digital health unit's work, including my research surrounding the impact of intrahospital transfers on odds of developing an infection |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://imperialbrc.nihr.ac.uk/2019/09/22/nihr-imperial-research-open-day-friday-15th-november-2019/ |
| Description | Public event - Imperial 'Lates' Beautiful Data |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | I took a lead in creating and hosting an interactive stand showcasing visualisation of infection data and patient movement with other members of my research unit (Global Digital Health Unit) |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.imperial.ac.uk/events/116446/imperial-lates-beautiful-data/ |