Explaining accesses to electronic health records

  • Authors:

  • Daniel Fabbri;Kristen LeFevre;David A. Hanauer

  • Affiliations:

  • University of Michigan, Ann Arbor, MI, USA;University of Michigan, Ann Arbor, MI, USA;University of Michigan Medical School, Ann Arbor, MI, USA

  • Venue:
  • Proceedings of the 2011 workshop on Data mining for medicine and healthcare
  • Year:
  • 2011

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Abstract

Electronic health record systems (EHRs) are increasingly used to store patient medical information. To ensure the responsible use of this data, EHRs collect access logs, which record each access to sensitive data (e.g., a patient's record). Using the access log, it is easy to determine who has accessed a specific medical record. However, in addition to this information, we observe that for various applications such as user-centric auditing, it is also important to understand why each access occurred. In this paper, we study why accesses occur in EHRs. Our goal is to provide an explanation describing why each access occurred (e.g., Dr. Dave accessed Alice's medical record because Dr. Dave has an appointment with Alice). Using data from the University of Michigan Health System, we demonstrate that most accesses to EHRs occur for a valid clinical or operational reason, and often the reason is documented in the EHR database. Specifically, we observe three general types of explanations (direct, group, and consultation), and we show that these explanations can explain over 90% of the accesses in the log. Moreover, we identify collaborative groups that help to explain additional accesses.