title: Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed.
abstract: BACKGROUND
  Despite visits to multiple physicians, many patients remain undiagnosed. A new online program, CrowdMed, aims to leverage the "wisdom of the crowd" by giving patients an opportunity to submit their cases and interact with case solvers to obtain diagnostic possibilities.
  
  
  OBJECTIVE
  To describe CrowdMed and provide an independent assessment of its impact.
  
  
  METHODS
  Patients submit their cases online to CrowdMed and case solvers sign up to help diagnose patients. Case solvers attempt to solve patients' diagnostic dilemmas and often have an interactive online discussion with patients, including an exchange of additional diagnostic details. At the end, patients receive detailed reports containing diagnostic suggestions to discuss with their physicians and fill out surveys about their outcomes. We independently analyzed data collected from cases between May 2013 and April 2015 to determine patient and case solver characteristics and case outcomes.
  
  
  RESULTS
  During the study period, 397 cases were completed. These patients previously visited a median of 5 physicians, incurred a median of US $10,000 in medical expenses, spent a median of 50 hours researching their illnesses online, and had symptoms for a median of 2.6 years. During this period, 357 active case solvers participated, of which 37.9% (132/348) were male and 58.3% (208/357) worked or studied in the medical industry. About half (50.9%, 202/397) of patients were likely to recommend CrowdMed to a friend, 59.6% (233/391) reported that the process gave insights that led them closer to the correct diagnoses, 57% (52/92) reported estimated decreases in medical expenses, and 38% (29/77) reported estimated improvement in school or work productivity.
  
  
  CONCLUSIONS
  Some patients with undiagnosed illnesses reported receiving helpful guidance from crowdsourcing their diagnoses during their difficult diagnostic journeys. However, further development and use of crowdsourcing methods to facilitate diagnosis requires long-term evaluation as well as validation to account for patients' ultimate correct diagnoses.
authors.affiliation: Houston Veterans Affairs Center for Innovations in Quality, Effectiveness and Safety, Health Services Research and Development, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States.
authors.forename: Ashley N D
authors.identifier: http://orcid.org/0000-0001-7993-8584
authors.initials: AN
authors.lastname: Meyer
authors.forename: Christopher A
authors.identifier: http://orcid.org/0000-0003-4908-6856
authors.initials: CA
authors.lastname: Longhurst
authors.forename: Hardeep
authors.identifier: http://orcid.org/0000-0002-4419-8974
authors.initials: H
authors.lastname: Singh
mesh_terms: D063045:Crowdsourcing / Q000379:methods; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D010820:Physicians; D011795:Surveys and Questionnaires
keywords: World Wide Web; crowdsourcing; diagnosis; diagnostic errors; patient safety