A pioneering systematic methodology to identify observational data sources for specific needs has been presented by Oxford PharmaGenesis today at ISPOR’s 19th Annual International Meeting in Montreal, Canada.

Using a novel five-step process, potential data sources were identified and characterized for use in a range of observational research programmes in the fields of cardiology, diabetes, oncology and respiratory medicine. Data were captured and project-specific evaluation criteria applied, including study population, target geographies, type of data required, length of follow-up, and ability to identify patients across data sources.

Over 14,000 references or potential data sources were screened across six separate studies to assess whether they reported information from a unique data source. From this mass of data, the Oxford PharmaGenesis team was able to recommend between 3 and 17 data sources per study that could be used for clients’ research programmes, as well as to identify data elements and geographical areas where additional data collection was needed.

Dr Karen Smoyer Tomic, US Practice Lead in Value Demonstration at Oxford PharmaGenesis said, “Our clients have come to us with a need to sort through a dizzying array of global data sources, to track down hard-to-find data elements, or to incorporate new data sources into their usual list. We developed a systematic and structured process and have had real success using it to identify the best data available or confirming that additional data collection is needed.”

The approach was effective in identifying accessible, relevant and high-quality data for both rare and more prevalent conditions. “This systematic understanding of real-world evidence has helped to guide observational research programmes in diverse therapeutic areas with specialized data requirements,” said Karen Tomic.

A copy of Karen Smoyer Tomic’s poster presentation, ‘Identifying Real-World Data for Observational Studies: A Systematic Approach’ is available here.