title: PatientsLikeMe: Consumer health vocabulary as a folksonomy.
abstract: PatientsLikeMe is an online social networking community. Subcommunities center on three diagnoses: Amyotrophic Lateral Sclerosis, Multiple Sclerosis and Parkinsons Disease. Community members can describe their symptoms online in natural language, resulting in folksonomic tags available for clinical analysis and for browsing by other users to find patients like me. Forty-three percent of PatientsLikeMe symptom terms are present as exact (24%) or synonymous (19%) terms in the Unified Medical Language System Metathesaurus (National Library of Medicine; 2007AC). Slightly more than half of the symptom terms either do not match the UMLS, or are unclassifiable. A clinical vocabulary, SNOMED CT, accounts for 93% of the matching terms. Analysis of the failed matches reveals challenges for online patient communication, not only with healthcare professionals, but with other patients. In a Web 2.0 environment with lowered barriers between consumers and professionals, a deficiency in knowledge representation affects not only professionals, but consumers as well.
authors.affiliation: University of Wisconsin-Madison, Cambridge, MA, USA.
authors.forename: Catherine Arnott
authors.initials: CA
authors.lastname: Smith
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Wicks
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D057218:Blogging / Q000458:organization & administration*; D054626:Consumer Health Information / Q000458:organization & administration*; D003255:Consumer Organizations / Q000458:organization & administration; D020407:Internet; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods; D012944:Social Support; D013358:Subject Headings; D014481:United States; D014584:User-Computer Interface; D018875:Vocabulary, Controlled