Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record

Simple item page
dc.citation.issue3
dc.citation.volume25
dc.contributor.authorWalonoski J
dc.contributor.authorKramer M
dc.contributor.authorNichols J
dc.contributor.authorQuina A
dc.contributor.authorMoesel
dc.contributor.authorHall D
dc.contributor.authorDuffett C
dc.contributor.authorDube K
dc.contributor.authorGallagher T
dc.contributor.authorMcLachlan S
dc.date.available2018-03
dc.date.available2017-07-05
dc.date.issued30/08/2017
dc.description.abstractObjective: Our objective is to create a source of synthetic electronic health records that is readily available; suited to industrial, innovation, research, and educational uses; and free of legal, privacy, security, and intellectual property restrictions. Materials and Methods: We developed Synthea, an open-source software package that simulates the lifespans of synthetic patients, modeling the 10 most frequent reasons for primary care encounters and the 10 chronic conditions with the highest morbidity in the United States. Results: Synthea adheres to a previously developed conceptual framework, scales via open-source deployment on the Internet, and may be extended with additional disease and treatment modules developed by its user community. One million synthetic patient records are now freely available online, encoded in standard formats (eg, Health Level-7 [HL7] Fast Healthcare Interoperability Resources [FHIR] and Consolidated-Clinical Document Architecture), and accessible through an HL7 FHIR application program interface. Discussion: Health care lags other industries in information technology, data exchange, and interoperability. The lack of freely distributable health records has long hindered innovation in health care. Approaches and tools are available to inexpensively generate synthetic health records at scale without accidental disclosure risk, lowering current barriers to entry for promising early-stage developments. By engaging a growing community of users, the synthetic data generated will become increasingly comprehensive, detailed, and realistic over time. Conclusion: Synthetic patients can be simulated with models of disease progression and corresponding standards of care to produce risk-free realistic synthetic health care records at scale.
dc.description.publication-statusPublished
dc.format.extent230 - 238
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000426850500003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=c5bb3b2499afac691c2e3c1a83ef6fef
dc.identifier.citationJOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2018, 25 (3), pp. 230 - 238
dc.identifier.doi10.1093/jamia/ocx079
dc.identifier.eissn1527-974X
dc.identifier.elements-id371531
dc.identifier.harvestedMassey_Dark
dc.identifier.issn1067-5027
dc.identifier.urihttps://hdl.handle.net/10179/11810
dc.publisherOxford University Press (OUP)
dc.relation.isPartOfJOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
dc.relation.urihttps://doi.org/10.1093/jamia/ocx079
dc.subjectelectronic health records
dc.subjectcomputer simulation
dc.subjectpatient-specific modeling
dc.subjectclinical pathways
dc.subjectRS-EHR
dc.subject.anzsrc08 Information and Computing Sciences
dc.subject.anzsrc09 Engineering
dc.subject.anzsrc11 Medical and Health Sciences
dc.titleSynthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record
dc.typeJournal article
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/College of Sciences/School of Mathematical and Computational Sciences
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