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Physics of the Medical Record: Handling Time in Health Record Studies

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Artificial Intelligence in Medicine (AIME 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9105))

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Abstract

The rapid increase in adoption of electronic health records (EHRs) creates the possibility of tracking billions of patient visits per year and exploiting them for clinical research. The international observational research collaboration, Observational Health Data Sciences and Informatics (OHDSI), has counted 682 million patient records that have been converted to a common format known at the OMOP Common Data Model [1]. While this number includes duplicates and records that have not been made broadly available to researchers, its scale demonstrates that converting the world population to a common format is feasible.

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Author information

Authors and Affiliations

  1. Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA

    George Hripcsak

Authors
  1. George Hripcsak
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Correspondence to George Hripcsak .

Editor information

Editors and Affiliations

  1. University of Pennsylvania, Philadelphia, Pennsylvania, USA

    John H. Holmes

  2. University of Pavia, Pavia, Italy

    Riccardo Bellazzi

  3. University of Pavia, Pavia, Italy

    Lucia Sacchi

  4. University of Manchester, Manchester, United Kingdom

    Niels Peek

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Hripcsak, G. (2015). Physics of the Medical Record: Handling Time in Health Record Studies. In: Holmes, J., Bellazzi, R., Sacchi, L., Peek, N. (eds) Artificial Intelligence in Medicine. AIME 2015. Lecture Notes in Computer Science(), vol 9105. Springer, Cham. https://doi.org/10.1007/978-3-319-19551-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-19551-3_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19550-6

  • Online ISBN: 978-3-319-19551-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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