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Evaluating health interest profiles extracted from patient-generated data

  • Andrea L. Hartzler
  • , David W. McDonald
  • , Albert Park
  • , Jina Huh
  • , Charles Weaver
  • , Wanda Pratt
  • University of Washington

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Patient-generated health data (PGHD) offers a promising resource for shaping patient care, self-management, population health, and health policy. Although emerging technologies bolster opportunities to extract PGHD and profile the needs and experiences of patients, few efforts examine the validity and use of such profiles from the patient's perspective. To address this gap, we explore health interest profiles built automatically from online community posts. Through a user evaluation with community members, we found that extracted profiles not only align with members' stated health interests, but also expand upon those manually entered interests with little user effort. Community members express positive attitudes toward the use and expansion of profiles to connect with peers for support. Despite this promising approach, findings also point to improvements required of biomedical text processing tools to effectively process PGHD. Findings demonstrate opportunities to leverage the wealth of unstructured PGHD available in emerging technologies that patients regularly use.

Original languageEnglish
Pages (from-to)626-635
Number of pages10
JournalAMIA Annual Symposium proceedings
Volume2014
StatePublished - 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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