Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic: A case report

Jyotishman Pathak, Richard C. Kiefer, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

The Linked Open Data (LOD) community project at the World Wide Web Consortium (W3C) is publishing various open data sets as Resource Description Framework (RDF) on the Web and extending it by setting RDF links between data items from different data sources containing information about genes, proteins, pathways, diseases, and drugs. While this presents a very powerful platform for federated querying and heterogeneous data integration, its true potential can only be realized when combining such information with "real" patient data from electronic health records. In this paper, we report our early experiences in applying Linked Data principles and technologies for representing patient data from electronic health records (EHRs) at Mayo Clinic in RDF. In particular, we demonstrate a proof-of-concept case study leveraging publicly available data from the Linked Open Drug Data cloud to federated querying for type 2 diabetes patients. Our study highlights several challenges and opportunities in using Semantic Web tools and technologies within a healthcare setting for enabling clinical and translational research.

Original languageEnglish (US)
Title of host publicationIHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Pages455-464
Number of pages10
DOIs
StatePublished - 2012
Event2nd ACM SIGHIT International Health Informatics Symposium, IHI'12 - Miami, FL, United States
Duration: Jan 28 2012Jan 30 2012

Other

Other2nd ACM SIGHIT International Health Informatics Symposium, IHI'12
CountryUnited States
CityMiami, FL
Period1/28/121/30/12

Fingerprint

Electronic Health Records
Technology
Translational Medical Research
Information Storage and Retrieval
Semantics
Pharmaceutical Preparations
Internet
Type 2 Diabetes Mellitus
Delivery of Health Care
Proteins

Keywords

  • Electronic Health Record (EHR)
  • Linked data
  • Semantic web
  • Translational research

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

Cite this

Pathak, J., Kiefer, R. C., & Chute, C. G. (2012). Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic: A case report. In IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (pp. 455-464) https://doi.org/10.1145/2110363.2110415

Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic : A case report. / Pathak, Jyotishman; Kiefer, Richard C.; Chute, Christopher G.

IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. 2012. p. 455-464.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pathak, J, Kiefer, RC & Chute, CG 2012, Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic: A case report. in IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. pp. 455-464, 2nd ACM SIGHIT International Health Informatics Symposium, IHI'12, Miami, FL, United States, 1/28/12. https://doi.org/10.1145/2110363.2110415
Pathak J, Kiefer RC, Chute CG. Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic: A case report. In IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. 2012. p. 455-464 https://doi.org/10.1145/2110363.2110415
Pathak, Jyotishman ; Kiefer, Richard C. ; Chute, Christopher G. / Applying Linked Data principles to represent patient's electronic health records at Mayo Clinic : A case report. IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium. 2012. pp. 455-464
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