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Automated Population of an i2b2 Clinical Data Warehouse using FHIR.
Solbrig, Harold R; Hong, Na; Murphy, Shawn N; Jiang, Guoqian.
Affiliation
  • Solbrig HR; Department of Health Sciences Research, Mayo Clinic, Rochester MN, USA.
  • Hong N; Department of Health Sciences Research, Mayo Clinic, Rochester MN, USA.
  • Murphy SN; Laboratory of Computer Science, Massachusetts General Hospital, Boston, MA, USA.
  • Jiang G; Department of Health Sciences Research, Mayo Clinic, Rochester MN, USA.
AMIA Annu Symp Proc ; 2018: 979-988, 2018.
Article de En | MEDLINE | ID: mdl-30815141
ABSTRACT
HL7 Fast Healthcare Information Resources (FHIR) is rapidly becoming the de-facto standard for the exchange of clinical and healthcare related information. Major EHR vendors and healthcare providers are actively developing transformations between existing EHR databases and their corresponding FHIR representation. Many of these organizations are concurrently creating a second set of transformations from the same sources into integrated data repositories (IDRs). Considerable cost savings could be realized and overall quality could be improved were it possible to transformation primary FHIR EHR data directly into an IDR. We developed a FHIR to i2b2 transformation toolkit and evaluated the viability of such an approach.
Sujet(s)

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Dossiers médicaux électroniques / Health Level Seven (organisme) / Jeux de données comme sujet / Entreposage de données / Interopérabilité des informations de santé Limites: Humans Langue: En Journal: AMIA Annu Symp Proc Sujet du journal: INFORMATICA MEDICA Année: 2018 Type de document: Article Pays d'affiliation: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Dossiers médicaux électroniques / Health Level Seven (organisme) / Jeux de données comme sujet / Entreposage de données / Interopérabilité des informations de santé Limites: Humans Langue: En Journal: AMIA Annu Symp Proc Sujet du journal: INFORMATICA MEDICA Année: 2018 Type de document: Article Pays d'affiliation: États-Unis d'Amérique