The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive, Synthetic Health Record

The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of...

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Veröffentlicht in:Electronics (Basel) 2022-04, Vol.11 (8), p.1199
Hauptverfasser: Walonoski, Jason, Hall, Dylan, Bates, Karen M., Farris, M. Heath, Dagher, Joseph, Downs, Matthew E., Sivek, Ryan T., Wellner, Ben, Gregorowicz, Andrew, Hadley, Marc, Campion, Francis X., Levine, Lauren, Wacome, Kevin, Emmer, Geoff, Kemmer, Aaron, Malik, Maha, Hughes, Jonah, Granger, Eldesia, Russell, Sybil
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Sprache:eng
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Zusammenfassung:The “Coherent Data Set” is a novel synthetic data set that leverages structured data from Synthea™ to create a longitudinal, “coherent” patient-level electronic health record (EHR). Comprised of synthetic patients, the Coherent Data Set is publicly available, reproducible using Synthea™, and free of the privacy risks that arise from using real patient data. The Coherent Data Set provides complex and representative health records that can be leveraged by health IT professionals without the risks associated with de-identified patient data. It includes familial genomes that were created through a simulation of the genetic reproduction process; magnetic resonance imaging (MRI) DICOM files created with a voxel-based computational model; clinical notes in the style of traditional subjective, objective, assessment, and plan notes; and physiological data that leverage existing System Biology Markup Language (SBML) models to capture non-linear changes in patient health metrics. HL7 Fast Healthcare Interoperability Resources (FHIR®) links the data together. The models can generate clinically logical health data, but ensuring clinical validity remains a challenge without comparable data to substantiate results. We believe this data set is the first of its kind and a novel contribution to practical health interoperability efforts.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics11081199