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

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 des...

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Detalles Bibliográficos
Autores principales: Meyer, Ashley N.D, Longhurst, Christopher A, Singh, Hardeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731679/
https://www.ncbi.nlm.nih.gov/pubmed/26769236
http://dx.doi.org/10.2196/jmir.4887
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author Meyer, Ashley N.D
Longhurst, Christopher A
Singh, Hardeep
author_facet Meyer, Ashley N.D
Longhurst, Christopher A
Singh, Hardeep
author_sort Meyer, Ashley N.D
collection PubMed
description 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.
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spelling pubmed-47316792016-02-16 Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed Meyer, Ashley N.D Longhurst, Christopher A Singh, Hardeep J Med Internet Res Original Paper 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. JMIR Publications Inc. 2016-01-14 /pmc/articles/PMC4731679/ /pubmed/26769236 http://dx.doi.org/10.2196/jmir.4887 Text en ©Ashley N.D. Meyer, Christopher A. Longhurst, Hardeep Singh. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.01.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Meyer, Ashley N.D
Longhurst, Christopher A
Singh, Hardeep
Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title_full Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title_fullStr Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title_full_unstemmed Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title_short Crowdsourcing Diagnosis for Patients With Undiagnosed Illnesses: An Evaluation of CrowdMed
title_sort crowdsourcing diagnosis for patients with undiagnosed illnesses: an evaluation of crowdmed
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731679/
https://www.ncbi.nlm.nih.gov/pubmed/26769236
http://dx.doi.org/10.2196/jmir.4887
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