Aberdeen Centre for Women's Health Research Seminar with Krishnarajah Nirantharakumar: DExtER: An automated clinical epidemiology study platform for women's health research

Aberdeen Centre for Women's Health Research Seminar with Krishnarajah Nirantharakumar: DExtER: An automated clinical epidemiology study platform for women's health research
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Aberdeen Centre for Women's Health Research Seminar with Krishnarajah Nirantharakumar: DExtER: An automated clinical epidemiology study platform for women’s health research

The NHS provides healthcare to 66 million people, with over a million people utilising NHS services every day. Each of these encounters is an opportunity to learn, but this data is often poorly accessible and not in research-ready formats. By bringing together experts in epidemiology, data science, and software engineering, we created DExtER (PMID: 32856160), an automated system for efficient, transparent and reproducible research. Studies which used to take months can now be undertaken within days. For example, DExtER enabled analysis of >70,000 serum testosterone measurements in young women, identifying increased risk of non-alcoholic fatty liver disease and diabetes in women with androgen excess. This led to a major new experimental medicine study (DAISy-PCOS) stratifying risk and developing novel treatments to prevent metabolic complications in women with polycystic ovary syndrome, a lifelong condition affecting 1 in 10 women worldwide.  DExtER will also support the recently awarded MuMPreDiCT consortium that will study the effect of multiple long term conditions on pregnancy outcomes.

The tool also enables representative recruitment for mechanistic studies by rapidly generating eligible participants based on inclusion and exclusion criteria by searching through millions of electronic patient records within minutes. It is also underpinning data-driven clinical trials, such as RADIANT, a trial to improve testing for diabetes in women with a history of gestational diabetes. Such trials use already-collected NHS health information to reduce the time taken for research, both for patients and NHS staff, with both recruitment and outcomes driven electronically.

 

Importantly, DExtER also supports better clinical decision-making. Publications arising from DExtER have supported clinical decision-making across varied health conditions including idiopathic intracranial hypertension, a health condition that is common among young women. Furthermore, we have demonstrated that DExtER can answer clinical questions that arise during patient consultations within hours: termed an ‘informatics consult’, a tailored approach particularly important where there is lack of clinical trial evidence. We are hoping to trial this concept in the Shrewsbury and Telford maternity hospital.

 

Venue
Virtually via Microsoft Teams
Contact

Please contact kelly.gray@abdn.ac.uk for the MS Teams link.