The tip of the iceberg: challenges of accessing hospital electronic health record data for biological data mining.
Modern cohort studies include self-reported measures on disease, behavior and lifestyle, sensor-based observations from mobile phones and wearables, and rich -omics data. Follow-up is often achieved through electronic health record (EHR) linkages across primary and secondary healthcare providers. Historically however, researchers typically only get to see the tip of the iceberg: coded administrative data relating to healthcare claims which mainly record billable diagnoses and procedures. The rich data generated during the clinical pathway remain submerged and inaccessible. While some institutions and initiatives have made good progress in unlocking such deep phenotypic data within their institutional realms, access at scale still remains challenging. Here we outline and discuss the main technical and social challenges associated with accessing these data for data mining and hauling the entire iceberg.
Institute of Health Informatics, University College London, London, UK ; Farr Institute of Health Informatics Research, University College London, London, UK.
Spiros C
SC
Denaxas
Institute of Health Informatics, University College London, London, UK ; Farr Institute of Health Informatics Research, University College London, London, UK ; Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, Utrecht, Netherlands.
Folkert W
FW
Asselbergs
Institute for Biomedical Informatics, Department of Biostatistics and Epidemiology, Perelman School or Medicine, University of Pennsylvania, Philadelphia, PA 19104-6116 USA.
Jason H
JH
Moore
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