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The explosion and abundance of digital data could facilitate large scale research for psychiatry and mental health. Research using so-called “real world data” – such as electronic medical/health records – can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real world data sources is complex because the clinically important ‘signal’ is often contained in both structured and unstructured (narrative or “free-text”) data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real world) data for psychiatric research.


Journal article


Translational psychiatry


Springer Nature

Publication Date