Data Extractor for Epidemiological Research (DExtER)
A three tier software system with a web based front-end to help design and conduct routine epidemiological and pharmaco-epidemiological studies and a high performing robust middle-ware to extract ‘ready to analyse’ data-sets based on study design that is supported by a highly secure back-end database system. DExtER powered by BEAR is available 24*7 and incorporates a standard data extraction ETL routine developed in-house that has made our research highly accurate and reproducible. With the help of DExtER the data extraction process has been made completely human independent and heavily reduced the costs of resources in terms of time, complexity, computing and expertise that is normally required. Created with an aim to expedite epidemiological research by reducing the gap between medical researchers and electronic patient records, DExtER is now part of the ACES framework.
Automated Clinical Epidemiology Studies (ACES)
One of the most ambitious Health Informatics projects at the Institute in collaboration with the Health Data Research UK. This project is led by Krishna Gokhale and Krish Nirantharakumar. Powered by DExtER, ACES involves building two separate frameworks for: 1) Automated Infant and Mothers Studies (AIMS) and 2) Automated Pharmaco-Epidemiology Studies (APES). This work stream will also build global collaborators by sharing the technology with international partners to enable simultaneous research across multiple countries/databases for a given clinical question (ACES: Global).
Research groups and centres
Founding member of Real World Evidence THIN-KING GROUP: with DExtER as its backbone this group currently led by Krish Nirantharakumar and Nicola Adderley utilises traditional cohort and routinely collected health care data to answer important clinical questions on risk factors, therapeutic options and complications of a number of clinical conditions, in particular diabetes and endocrinology disorders. In addition, the group evaluates policies and estimates healthcare costs utilising routinely collected data.