Designing user interfaces to support front-end clinical decision-making in neurodegenerative disease: Bridging from research to practice
EuroPOND CDT studentship
Prof Daniel Alexander, MailScanner has detected a possible fraud attempt from "www.ucl.ac.uk" claiming to be Centre for Medical Image Computing, Dept. Computer Science.
Dr Anna Cox, UCL Interaction Centre, Division of Psychology and Language Sciences.
Dr Annemie Ribbens, Icometrix (external).
This is an opportunity for a student to design a tool that will help clinicians use novel models of neurodegenerative disease emerging from recent research at UCL. Realising broader clinical impact in this area is important and timely because management of neurodegenerative disease is reaching crisis point with the ageing population. This PhD offers candidates an exciting opportunity to have real impact on the way clinicians diagnose, and ultimately treat, neurodegenerative diseases like Alzheimer’s disease and other dementias.
There are a number of exciting challenges for the PhD candidate to engage with before achieving this potential, which include, but are not limited to:
• understanding the capability and value of the research models for clinical practice;
• understanding the workflows, constraints and everyday practices of clinicians;
• following a user-centred design design process in a clinical context;
• creating appropriate low and hi-fidelity prototypes so clinical colleagues can provide feedback;
• negotiating technical and ethical issues for developing a medical tool for a clinical context.
This industry-sponsored studentship is a collaboration between UCL’s Centre for Medical Image Computing, the UCL Interaction Centre, and Icometrix – a healthcare engineering company based in Leuven, Belgium. The studentship aligns with the Horizon 2020 – EuroPOND. The student will join a growing cohort of PhD students who are part of the UCL Institute for Digital Health
Recent work in the POND group within CMIC has developed longitudinal models of biomarker changes from large cross-sectional data sets; see for example (Young, et al. 2014) The models uniquely integrate information from a wide range of biomarkers – imaging, CSF markers, blood tests, neuropsychological assessments, etc. – which clinicians and biomedical researchers find increasingly difficult to assimilate. The student will build a front-end tool following user-centred design processes so clinicians can utilise these modelling techniques in their normal work. The models offer great potential for neurodegenerative diseases, such as Alzheimer’s disease and other dementias. They have potential to i) enhance the success of drug trials, by stratifying patients by disease subtype and stage, and ii) enhance clinical management, by providing early diagnosis, accurate prognosis, and informing potential treatment decisions.
However, failures in the adoption of health IT systems have been well documented. It has been argued that these failures are often due to the “design-reality gap” (Heeks 2005). There is a need to realign work as imagined and work as done for the design of health IT (Blandford et al., 2014). The translation of this technology into clinical practice therefore presents significant challenges: – How should the data be visualised so as to best aid clinical decision-making? – How should the system be delivered to end-users, e.g. clinicians, so as to ensure uptake? (On which platform? Who needs access? How does it integrate with existing systems and workflow?) Candidates will conduct fieldwork in healthcare to find answers to these questions (Furniss et al. 2014). They will engage with techniques to analyse how interactive systems work with other tools and artefacts whilst being embedded in workflows, social practices, and physical working environments (Furniss et al., 2015). Indeed, Distributed Cognition may provide a suitable framework for understanding how clinicians currently integrate the wide range of biomarkers for decision-making and how the proposed tool could augment and support their thinking.
This project builds on the substantial expertise in conducting digital health research within CMIC and UCLIC and delivery of emerging technology to front-line application at Icometrix The doctoral student will work directly with several end-user groups, taking a user-centred approach to the design and development of a system that supports transformation of clinical practice. They will be based at UCL, but spend time on-site with Icometrix, as well as working directly with end-user groups of clinicians and treatment developers.
The successful applicant will have solid skills in design orientated subjects with the ability to create low and high-fidelity prototypes of the proposed tool (e.g. the candidate might have a background in design (product/industrial), ergonomics, HCI, human factors, computer science). The ability to develop a working product would be an advantage (here the candidate would have programming and software engineering skills). Experience of healthcare systems and research would also be advantage, but not essential. Funding is limited to UK/EU applicants.
There is an option with this studentship to join the MRes year of the CDT in Medical Imaging. This can be discussed during the interview phase of the recruitment process.
The fees are covered for EU/UK students and the stipend is approx. £16,296 per year.
Enquiries: Contact any of the supervision team for scientific enquiries
TO APPLY – Please complete a ‘Prism’ application. Click Here
Deadline for applications: 15 July 2016
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