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(MRC DTP) 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) [1], 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 [2], but with varying and often limited impact on patient outcomes [3]. 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 [4,5].

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.

To address the project’s objectives, a multidisciplinary supervisory team will introduce you to a wide range of methods, including systematic literature reviewing, qualitative research (observations of clinic consultations; interviews with health care professionals and patients; medical record review) and health informatics methods (data analytics; user-centred design; health information system evaluation). You will have access to relevant modules within the MSc programmes in Health Data Science and Health Informatics that are run by the Centre for Health Informatics. There is also an opportunity to gain software engineering experience, should that be of interest to you.

We are looking for a high-calibre individual with a clinical or health informatics background who wants to develop a broad skill set relevant to designing and evaluating digital interventions for health care professionals. Evidence of a clear interest in using digital patient-generated health data for improving patient care and outcomes is desirable.

https://www.research.manchester.ac.uk/portal/sabine.vanderveer.html
https://www.research.manchester.ac.uk/portal/alan.davies-2.html
https://www.research.manchester.ac.uk/portal/john.ainsworth.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 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.

References

1. Cresswell KM, McKinstry B, Wolters M, Shah A, Sheikh A. Five key strategic priorities of integrating patient generated health data into United Kingdom electronic health records. J Innov Heal Informatics. 2018;25: 254–259. doi:10.14236/jhi.v25i4.1068
2. Harle CA, Listhaus A, Covarrubias CM, Schmidt SOF, Mackey S, Carek PJ, et al. Overcoming barriers to implementing patient-reported outcomes in an electronic health record: A case report. J Am Med Informatics Assoc. 2016;23: 74–79. doi:10.1093/jamia/ocv085
3. Chen J, Ou L, Hollis SJ. A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Heal Serv Res. BMC Health Services Research; 2013;13: 211. doi:10.1186/1472-6963-13-211
4. Reading MJ, Merrill JA. Converging and diverging needs between patients and providers who are collecting and using patient-generated health data: an integrative review. J Am Med Informatics Assoc. 2018;25: 759–771. doi:10.1093/jamia/ocy006
5. Greenhalgh J, Gooding K, Gibbons E, Dalkin S, Wright J, Valderas J, et al. How do patient reported outcome measures (PROMs) support clinician-patient communication and patient care? A realist synthesis. J Patient-Reported Outcomes. Journal of Patient-Reported Outcomes; 2018;2. doi:10.1186/s41687-018-0061-6

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