Opioids are commonly used in the management of acute and chronic pain, escalating prescriptions for which have contributed to an opioid epidemic in several high-income countries. They are known to be associated with a spectrum of adverse events including effects on cognition that can range from concentration difficulties, memory deficits, hallucinations to sudden onset confusion (delirium) and possible long-term effects on cognition. Patient narratives from our previous work have shown that cognitive side effects following opioid use can considerably impact several aspects of quality of life. However at present there is little understanding of how prescription factors, sociodemographic factors, comorbidities or a combination of these increase the risk of such events, which means that interventions to mitigate such adverse events are lacking.
Electronic health records (EHRs) in hospitals and primary care contain a wealth of rich, routinely collected information that have the potential to drive improvements in patient care and research. EHR data from hospitals often collect more accurate measures to capture exposure to the drug, variables that allow better control for confounding by indication and outcome measurement through objective instruments to ascertain delirium. Primary care records benefit from cradle to grave EHRs that allow measurement of more insidious outcomes such as cognitive decline. Non-serious adverse effects on cognition such as on concentration, memory and sensorial capacity however need to be captured directly from patients. Mobile applications are used increasingly for self-reporting patient experience in chronic conditions and associated treatment, and provide a valuable opportunity to evaluate the nature and impact of reported adverse events.
Aims/Objectives:
The aim of this PhD will be to evaluate the risk of serious and non-serious cognitive adverse events in association with prescription opioids using routinely collected and mhealth generated digital data. Specific objectives will include:
1) Review the use of existing instruments available to measure cognitive effects in routinely collected data and mhealth applications
2) Evaluate the risk of delirium and cognitive decline associated with opioids using emerging secondary care and existing primary care EHRs
3) Assess individual risk factors and identify patient subgroups at risk of serious cognitive effects using routinely collected data
4) Evaluate user acceptability of mhealth tools to detect longitudinal changes in cognitive effects
https://www.research.manchester.ac.uk/portal/meghna.jani.html
https://www.research.manchester.ac.uk/portal/will.dixon.html
http://www.cfe.manchester.ac.uk/
Entry Requirements
Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology.
How to Apply
To be considered for this project you MUST submit a formal online application form - full details on how to apply can be found on the MRC Doctoral Training Partnership (DTP) website www.manchester.ac.uk/mrcdtpstudentships
Applicants interested in this project should make direct contact with the Primary Supervisor to arrange to discuss the project further as soon as possible.
Equality, Diversity and Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/
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