Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed

Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed

http://www.jmir.org/2016/1/e12/

 

1Houston 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

2Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, United States

3Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, United States

Corresponding Author:

Hardeep Singh, MD, MPH

 

Houston Veterans Affairs Center for Innovations in Quality, Effectiveness and Safety

Michael E. DeBakey Veterans Affairs Medical Center

VA HSR&D Center of Innovation (152)

2002 Holcombe Boulevard

Houston, TX, 77030

United States

Phone: 1 713 794 8601

Fax:1 713 748 7359

Email: hardeeps [at] bcm.edu

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.

J Med Internet Res 2016;18(1):e12

doi:10.2196/jmir.4887

KEYWORDS

Maurice Preter, MD

About Maurice Preter MD

Maurice Preter, MD is a European and U.S. educated psychiatrist, psychotherapist, psychopharmacologist, neurologist, and medical-legal expert in private practice in Manhattan. He is also the principal of Fifth Avenue Concierge Medicine, PLLC, a medical concierge service and health advisory for select individuals and families.
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