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PhD Studentship: Development of statistical methods to improve treatment monitoring in patients with chronic conditions

  • Full or part time
  • Application Deadline
    Friday, February 01, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Number of awards:

1

Start date and duration:

Starting April (preferred) or September 2019 for 3.5 years.

Overview:

This project is a really exciting opportunity to work in an interdisciplinary team bringing together statisticians, methodologists, clinicians and industrial partners to find solutions to a key problem that is becoming increasingly more costly for the NHS. Management of long term illness is an important challenge in our ageing society; it requires both effective treatment and ongoing monitoring, i.e. periodic measurement that guides the management of a chronic or recurrent condition and which can be done by clinicians, patients, or both. For example, patients with rheumatological conditions are usually treated with drugs that can have serious adverse effects, so they are routinely monitored with a panel of tests.

Research is lacking in statistical methods for evaluating monitoring protocols (e.g. the optimal frequency of testing in the different phases of monitoring), even though the impact on health and health care expenditure and patient health is substantial. One reason for the lack of research on monitoring is that it is rare to have access to good quality longitudinal data on adverse events attributable to treatment.

In Newcastle, the monitoring service for patients being treated for rheumatological conditions recently implemented a system (DAWN-RH, http://www.4s-dawn.com/products/patient-safety-monitoring/) which records appointments scheduled and attended, drugs prescribed for the rheumatological condition, test results for the monitoring strategy, alerts on results that are out of range, and the occurrence, duration, and severity of adverse drug events. Through this system, around 3000 patients are monitored for a total of 20k appointments annually. This unique dataset will allow the development and internal validation of the statistical methods and tools developed during the project.

The PhD student will work on cutting edge research in an interdisciplinary team linking the School of Mathematics, Statistics and Physics, the School of Biology and two key infrastructures of the National Institute for Health Research (NIHR): the Newcastle In Vitro Diagnostics Co-operative and the Newcastle Biomedical Research Centre (BRC). This project has the potential to have a high impact on patient health and on NHS delivery of care. The methodologies developed will have wider applications in a range of clinical areas.

Sponsor:

NIHR Newcastle In Vitro Diagnostics Co-operative (https://bit.ly/2DWXczr) and NIHR Newcastle Biomedical Research Centre (https://bit.ly/2PhORrP).

Name of supervisor(s):

Mark Shirley (https://bit.ly/2zDVNdR), Sara Graziadio, Dennis Prangle (https://bit.ly/2BOr2o6) and Stephen Rushton (https://bit.ly/2PiGkoy).

Eligibility Criteria:

This studentship is available to UK and EU candidates who have or are predicted to obtain at least a 2(i) Bachelor Degree or Master in Mathematics, Statistics, Physics, or Computer Science (or international equivalent).

How to apply:

You must apply through the University’s online postgraduate application form (https://bit.ly/2FZnZ0G):

Please include the following information:

•Insert the programme code 8080F in the programme of study section
•Select ‘PhD Mathematics (full time) – Applied Mathematics’
•Insert the studentship code MSP016 in the studentship/partnership reference field.
•Attach degree transcripts and certificates, a personal statement and CV.

Contact:

For further information please email either or .

Funding Notes

A tax-free stipend of £14,777 per year (subject to minor change) and 100% UK/EU tuition fees.

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