The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis.

Background: Patients with difficult medical cases often remain undiagnosed despite visiting multiple physicians. A new online platform, CrowdMed, uses crowdsourcing to quickly and efficiently reach an accurate diagnosis for these patients.Objective: This study sought to evaluate whether CrowdMed dec...

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Publicado en:Journal of Medical Internet Research Vol. 18; no. 6; pp. 91 - 92
Autores principales: Juusola, Jessie L, Quisel, Thomas R, Foschini, Luca, Ladapo, Joseph A
Formato: research Journal Article
Publicado: JMIR Publications Inc. Jul2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2016
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        atl: The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis.
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          Juusola, Jessie L
          Quisel, Thomas R
          Foschini, Luca
          Ladapo, Joseph A
        affil: Evidation Health, Inc, San Mateo, CA, United States
      sug:
        subj:
          Telemedicine
          Patient Attitudes
          Crowdsourcing Methods
          Internet
          Insurance
          Quality of Health Care Methods
          Female
          Male
          Retrospective Design
          Adult
          Human
          Adult: 19-44 years
          Female
          Male
      ab: Background: Patients with difficult medical cases often remain undiagnosed despite visiting multiple physicians. A new online platform, CrowdMed, uses crowdsourcing to quickly and efficiently reach an accurate diagnosis for these patients.Objective: This study sought to evaluate whether CrowdMed decreased health care utilization for patients who have used the service.Methods: Novel, electronic methods of patient recruitment and data collection were utilized. Patients who completed cases on CrowdMed's platform between July 2014 and April 2015 were recruited for the study via email and screened via an online survey. After providing eConsent, participants provided identifying information used to access their medical claims data, which was retrieved through a third-party web application program interface (API). Utilization metrics including frequency of provider visits and medical charges were compared pre- and post-case resolution to assess the impact of resolving a case on CrowdMed.Results: Of 45 CrowdMed users who completed the study survey, comprehensive claims data was available via API for 13 participants, who made up the final enrolled sample. There were a total of 221 health care provider visits collected for the study participants, with service dates ranging from September 2013 to July 2015. Frequency of provider visits was significantly lower after resolution of a case on CrowdMed (mean of 1.07 visits per month pre-resolution vs. 0.65 visits per month post-resolution, P=.01). Medical charges were also significantly lower after case resolution (mean of US $719.70 per month pre-resolution vs. US $516.79 per month post-resolution, P=.03). There was no significant relationship between study results and disease onset date, and there was no evidence of regression to the mean influencing results.Conclusions: This study employed technology-enabled methods to demonstrate that patients who used CrowdMed had lower health care utilization after case resolution. However, since the final sample size was limited, results should be interpreted as a case study. Despite this limitation, the statistically significant results suggest that online crowdsourcing shows promise as an efficient method of solving difficult medical cases.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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