Prof W Dixon, Dr G Nenadic, Dr C Jay
No more applications being accepted
Competition Funded PhD Project (European/UK Students Only)
About the Project
Background
Healthcare mobile applications are used increasingly for self-reporting patient experience on living with (chronic) diseases and associated treatment. Such data is mainly used to support care of the individual who enters the data, but the use of such data for supporting clinical care, and for large-scale epidemiological research and regulatory purposes is still untapped. This research will address the critical aspect of accurate and valid data collection.
Aim and rationale
This project will explore developing a mobile app to collect and code patient-reported medication side effects without the need for clinician involvement. The project will investigate the best ways to collect data and optimise/personalise selection of codes from a clinical terminology that facilitate efficient and valid coding of adverse events. The three key objectives for this project are:
1. Develop a computer system to map short user-entered descriptions of side effects to the most relevant MedDRA code
2. Design and refine the user interface for data entry and selection of code, including incorporation of selection optimisation (eg code suggestions informed by prior knowledge such as patient information leaflets or common selections or patient previous history)
3. Assess the usability of the application and validity of the resultant data in patients with chronic diseases.
Methods
The project will develop a multi-disciplinary mixed methods approach that combines user experience, interface design and development, automated healthcare text mining, clinical validation and digital epidemiology. Text mining of user input will use and tailor existing machine-learning approaches to map short descriptions in user input to MedDRA and facilitate finding the most appropriate code(s) by relying on existing knowledge from external resources and context.
The impact of the work will be through the development of a trusted open-source method to collect coded side effect information from patients within smartphone applications. This has future uses in supporting mobile health research studies, supporting clinical practice via remote monitoring, and advancing data quality and volume for national pharmacovigilance.
Will Dixon
https://www.research.manchester.ac.uk/portal/en/researchers/william-dixon(12ae2656-071c-4dbb-b013-eb2caad1b6b4).html
Goran Nenadic
https://www.research.manchester.ac.uk/portal/gnenadic.html
Caroline Jay
https://www.research.manchester.ac.uk/portal/caroline.jay.html
Entry Requirements:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
Funding Notes
This project is to be funded under the MRC Doctoral Training Partnership. If you are interested in this project, please make direct contact with the Principal Supervisor to arrange to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found on the MRC DTP website www.manchester.ac.uk/mrcdtpstudentships
As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
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