Literature DB >> 35211336

Ensuring a safe(r) harbor: Excising personally identifiable information from structured electronic health record data.

Emily R Pfaff1, Melissa A Haendel2, Kristin Kostka3, Adam Lee4, Emily Niehaus5, Matvey B Palchuk6, Kellie Walters4, Christopher G Chute7.   

Abstract

Recent findings have shown that the continued expansion of the scope and scale of data collected in electronic health records are making the protection of personally identifiable information (PII) more challenging and may inadvertently put our institutions and patients at risk if not addressed. As clinical terminologies expand to include new terms that may capture PII (e.g., Patient First Name, Patient Phone Number), institutions may start using them in clinical data capture (and in some cases, they already have). Once in use, PII-containing values associated with these terms may find their way into laboratory or observation data tables via extract-transform-load jobs intended to process structured data, putting institutions at risk of unintended disclosure. Here we aim to inform the informatics community of these findings, as well as put out a call to action for remediation by the community.
© The Author(s) 2021.

Entities:  

Keywords:  Electronic health records; data privacy; medical terminologies

Year:  2021        PMID: 35211336      PMCID: PMC8826001          DOI: 10.1017/cts.2021.880

Source DB:  PubMed          Journal:  J Clin Transl Sci        ISSN: 2059-8661


  4 in total

1.  Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives.

Authors:  Youngjun Kim; Paul Heider; Stéphane Meystre
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  Modifications to the HIPAA Privacy, Security, Enforcement, and Breach Notification rules under the Health Information Technology for Economic and Clinical Health Act and the Genetic Information Nondiscrimination Act; other modifications to the HIPAA rules.

Authors: 
Journal:  Fed Regist       Date:  2013-01-25

3.  A Comparative Analysis of Speed and Accuracy for Three Off-the-Shelf De-Identification Tools.

Authors:  Paul M Heider; Jihad S Obeid; Stéphane M Meystre
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2020-05-30

Review 4.  Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1.

Authors:  Amber Stubbs; Christopher Kotfila; Özlem Uzuner
Journal:  J Biomed Inform       Date:  2015-07-28       Impact factor: 6.317

  4 in total
  1 in total

1.  Perceived Risk of Re-Identification in OMOP-CDM Database: A Cross-Sectional Survey.

Authors:  Yae Won Tak; Seng Chan You; Jeong Hyun Han; Soon-Seok Kim; Gi-Tae Kim; Yura Lee
Journal:  J Korean Med Sci       Date:  2022-07-04       Impact factor: 5.354

  1 in total

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