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Challenges in Synthesizing Surrogate PHI in Narrative EMRs

  • Chapter
Medical Data Privacy Handbook

Abstract

Preparing narrative medical records for use outside of their originating institutions requires that protected health information (PHI) be removed from the records. If researchers intend to use these records for natural language processing, then preparing the medical documents requires two steps: (1) identifying the PHI and (2) replacing the PHI with realistic surrogates. In this chapter we discuss the challenges associated with generating these realistic surrogates and describe the algorithms we used to prepare the 2014 i2b2/UTHealth shared task corpus for distribution and use in a natural language processing task focused on de-identification.

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Notes

  1. 1.

    Somewhat confusingly, “re-identification” is also sometimes used to refer to determining a person’s true identity from de-identified data [7], so we avoid that term for the remainder of this chapter.

  2. 2.

    Informatics for Integrating Biology and the Bedside.

  3. 3.

    University of Texas Health Science Center at Houston.

  4. 4.

    45 CFR 164.514.

  5. 5.

    http://www.asbestos.com/occupations/.

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Acknowledgements

This project was funded by NIH NLM 2U54LM008748 PI: Isaac Kohane, and by NIH NLM 5R13LM011411 PI: Ozlem Uzuner.

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Authors and Affiliations

  1. School of Library and Information Science, Simmons College, Boston, MA, USA

    Amber Stubbs

  2. State University of New York, Albany, NY, USA

    Özlem Uzuner & Christopher Kotfila

  3. Department of Computer Science, Siena College, Loudonville, NY, USA

    Ira Goldstein

  4. Department of Computer Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Peter Szolovits

Authors
  1. Amber Stubbs
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  2. Özlem Uzuner
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  3. Christopher Kotfila
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  4. Ira Goldstein
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  5. Peter Szolovits
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Correspondence to Amber Stubbs .

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Editors and Affiliations

  1. IBM Research - Ireland, Mulhuddart, Dublin, Ireland

    Aris Gkoulalas-Divanis

  2. Cardiff University, Cardiff, United Kingdom

    Grigorios Loukides

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Stubbs, A., Uzuner, Ö., Kotfila, C., Goldstein, I., Szolovits, P. (2015). Challenges in Synthesizing Surrogate PHI in Narrative EMRs. In: Gkoulalas-Divanis, A., Loukides, G. (eds) Medical Data Privacy Handbook. Springer, Cham. https://doi.org/10.1007/978-3-319-23633-9_27

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  • DOI: https://doi.org/10.1007/978-3-319-23633-9_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23632-2

  • Online ISBN: 978-3-319-23633-9

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