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Harnessing digital patient-generated health data to improve clinical decisions in people with long-term conditions

Project Description

One in four people in the UK live with one or more long-term conditions. To support the management of these conditions, there is an increasing focus on harnessing the potential of patient-generated health data (PGHD), such as home-based blood pressure readings, patient-reported symptom scores, or physical activity data from wearables. Studies have shown that collection of digital PGHD and its integration in electronic health record systems is feasible, but with varying and often limited impact on patient outcomes. This may be because health care professionals need support with interpreting and acting on this new type of data in order for it to inform their decision making.

This PhD project aims to investigate how PGHD can improve patient care and outcomes by better informing clinical decisions in people with long-term conditions. Specific objectives are to: (1) Investigate how PGHD are currently used to inform clinical decisions; (2) Explore health care professionals’ needs for better incorporating PGHD in clinical decisions; and (3) Design and test a digital intervention that addresses these needs. Chronic kidney disease will serve as the clinical context for this project, with a focus on using PGHD for symptom management in secondary care.

The project will enhance our understanding of how PGHD can inform clinical decisions and lead to improved patient outcomes, while also delivering the design of an intervention to optimise use PGHD in clinical decision-making. Together, these will inform a larger study that further develops the intervention and evaluates its impact on patient outcomes.

This project would suit a student with a strong health informatics, health services or clinical/nursing background who has a particular interest in digital health technology. Candidates are expected to hold (or be due to obtain) a minimum upper-second (or equivalent) class undergraduate degree in health informatics, psychology, a clinical discipline, or other relevant subject.

A Masters degree in a relevant subject and/or relevant research experience is desirable.

For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website ( Informal enquiries may be made directly to the primary supervisor. On the online application form select PhD Medical / Clinical Science.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit

Funding Notes

Applications are invited from self-funded students. This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

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.

Fees can be found here K:\FBMH Doctoral Academy\DA Reference Library - Policy and Procedures\Fees


Austin L, Sharp CA, Van der Veer SN, Machin M, Humphreys J, Mellor P, McCarthy J, Ainsworth J, Sanders C, Dixon WG. Providing ‘the bigger picture’: benefits and feasibility of integrating remote monitoring from smartphones into the electronic health record. Rheumatology 2019; Epub ahead of print

Fraccaro P, Vigo M, Balatsoukas P, Buchan IE, Peek N, Van der Veer SN. The influence of patient portals on users’ decision making is under-investigated: a systematic methodological review. International Journal of Medical Informatics 2018; 111:100-111

Aresi G, Hassan L, Rayner H, Mitra S, Burton JO, Sanders C, Van der Veer SN. Reasons for underreporting of uremic pruritus in people with chronic kidney disease: a qualitative study. Journal of Pain and Symptom Management 2019; Epub ahead of print

Dowding D, Merrill JA, Barrón Y, Onorato N, Jonas K, Russell D. Usability evaluation of a dashboard for home care nurses. CIN: Computers, Informatics, Nursing. 2019. 37(1), 11-19

Dowding D, Russell D, Onorato N, Merrill JA. Technology Solutions to Support Care Continuity in Home Care: A Focus Group Study. J Healthc Qual. 2018;40(4):236-246.

Dowding D, Merrill JA, Onorato N, Barrón Y, Rosati RJ, Russell D. The impact of home care nurses’ numeracy and graph literacy on comprehension of visual display information: implications for dashboard design. Journal of the American Medical Informatics Association. 25(2): 175-182.

Davies A, Harper S, Vigo M, Jay C Investigating the effect of clinical history before electrocardiogram interpretation on the visual behavior and interpretation accuracy of clinicians. Scientific Reports 2019; 9(11):1-10

Alahmadi A, Davies A, Vigo M, Jay C Can lay people identify a drug-induced QT-interval prolongation? A psychophysical and eye-tracking experiment examining the ability of non-experts to interpret an ECG. Journal of the American Medical Informatics Association 2019; 26(5):404-411

Number of post-docs/Ras/project managers available to support student/project: 4
Study Examining the Association between Weather and Pain: Cohort Study. JMIR Mhealth Uhealth. 2017 Nov 1;5(11):e168.

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