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Cegedim Health Data’s Epi Res Platform is set to significantly reduce time in research study design and rapidly return verified and valid insights to expedite clinical research, slashing both the time and associated costs for research studies.

Cegedim Health Data (CHD) and it’s own real world data database, The Health Improvement Network (THIN), the data source for anonymised primary care records, today launch their revolutionary platform to transform the time and cost traditionally associated with expediting epidemiological research. Developed in conjunction with, and powered by, the University of Birmingham Institute of Applied Health Research’s Data Extractor for Epidemiological Research (Dexter), CHD’s Epidemiological Research Platform uses rapid, automated processes to extract Real World Data (RWD) to generate publication-ready, analysed datasets from THIN data, significantly reducing the time and cost involved in research study design. CHD’s ER platform is proven to rapidly return insights that are from verified, valid and reproducible datasets to expedite research and reduce human induced errors.

Samir Dhalla, Head of The Health Improvement Network, comments: “One of the challenges of medicines development is not about our ability to ask the right questions, but our ability to answer the questions in a robust and timely manner. In fact, it is the inability to rapidly return insights that can delay progress with clinical research. What this means is that real world data access can become protracted and analysis requires specialist skills. Even when the skill sets do exist, and data access has been brokered, the ability to turn a clinical question into actionable insights takes time and builds costs.”

Cegedim’s Epidemiological Research Platform offers a rapid, automated access point to epidemiological studies that is built on its robust and highly studied THIN database to provide publication-ready analysis without the need for dedicated statistics or IT resources. The solution offers multiple study design options and customisable online cohort builder for capturing inclusion criteria (study period, exposure, outcomes of interest). It allows for more rapid turnover of relevant studies, and because of the hard-coded analysis, reduces the risk of analyst error and helps minimise bias; making the data more reproducible. The platform is fully compliant with data governance best practice and protects patient data.

The ER Platform is a three-tier, web-based software system, comprising a web-based front end where users can submit their study design and data extraction requests; the Dexter data extraction middleware; and a secure relational database management system that accesses and reads data from the THIN database.

Dan Somers, CEO of DExtER Software, adds: “In spite of best efforts, data extraction from primary care databases poses a number of issues when it comes to research purposes, as they are not designed with that in mind. Thus, it is crucial to create automated methods to extract verifiable and valid datasets to expedite research and to avoid human induced errors. The collaboration between Cegedim Health Data and the University of Birmingham aims to address these issues. We anticipate our new architecture will expedite and reduce the time and costs epidemiological and health services research requires by reducing the gap between medical researchers and electronic patient records.”

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