Team for Research in
Ubiquitous Secure Technology

Citation
Ellick Chan. "Understanding the Challenges with Medical Data Segmentation for Privacy". Talk or presentation, 10, October, 2013.

Abstract
Electronic Health Records (EHRs) are perceived as a path to significant improvement in healthcare, and patient privacy is an important consideration in the adoption of EHRs. Medical record segmentation is a technique to provide privacy and protect against discrimination for certain medical conditions such as STDs, substance abuse and mental health, by sequestering or redacting certain medical codes from a patient’s record. We present an initial study that describes an approach for segmenting sensitive medical codes to protect patient privacy and to comply with privacy laws. Firstly, we describe segmentation strategies for sensitive codes, and explore the link between medical concepts using sources of medical knowledge. Secondly, we mine medical knowledge sources for correlations between medical concepts. Thirdly, we describe an approach that a privacy attacker may use to infer redacted codes based off second order knowledge. More specifically, the attacker could use the presence of multiple related concepts to strengthen the attack. Finally, we evaluate defensive approaches against techniques that an adversary may use to infer the segmented condition.

Electronic downloads

• Chan_2013_10_TRUST.pptx · application/vnd.openxmlformats-officedocument.presentationml.pre · 2765 kbytes

• HTML

  Ellick Chan. <a
  href="http://www.truststc.org/pubs/926.html"
  ><i>Understanding the Challenges with Medical Data
  Segmentation for Privacy</i></a>, Talk or
  presentation,  10, October, 2013.

• Plain text

  Ellick Chan. "Understanding the Challenges with Medical
  Data Segmentation for Privacy". Talk or presentation, 
  10, October, 2013.

• BibTeX

  @presentation{Chan13_UnderstandingChallengesWithMedicalDataSegmentationFor,
      author = {Ellick Chan},
      title = {Understanding the Challenges with Medical Data
                Segmentation for Privacy},
      day = {10},
      month = {October},
      year = {2013},
      abstract = {Electronic Health Records (EHRs) are perceived as
                a path to significant improvement in healthcare,
                and patient privacy is an important consideration
                in the adoption of EHRs. Medical record
                segmentation is a technique to provide privacy and
                protect against discrimination for certain medical
                conditions such as STDs, substance abuse and
                mental health, by sequestering or redacting
                certain medical codes from a patient’s record.
                We present an initial study that describes an
                approach for segmenting sensitive medical codes to
                protect patient privacy and to comply with privacy
                laws. Firstly, we describe segmentation strategies
                for sensitive codes, and explore the link between
                medical concepts using sources of medical
                knowledge. Secondly, we mine medical knowledge
                sources for correlations between medical concepts.
                Thirdly, we describe an approach that a privacy
                attacker may use to infer redacted codes based off
                second order knowledge. More specifically, the
                attacker could use the presence of multiple
                related concepts to strengthen the attack.
                Finally, we evaluate defensive approaches against
                techniques that an adversary may use to infer the
                segmented condition.},
      URL = {http://www.truststc.org/pubs/926.html}
  }
  

Posted by Carolyn Winter on 18 Nov 2013.
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