TY - JOUR
T1 - Evaluating health interest profiles extracted from patient-generated data
AU - Hartzler, Andrea L.
AU - McDonald, David W.
AU - Park, Albert
AU - Huh, Jina
AU - Weaver, Charles
AU - Pratt, Wanda
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
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M3 - Article
C2 - 25954368
AN - SCOPUS:84964314068
VL - 2014
SP - 626
EP - 635
JO - AMIA ... Annual Symposium proceedings. AMIA Symposium
JF - AMIA ... Annual Symposium proceedings. AMIA Symposium
ER -