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Is Crowdsourcing Patient-Reported Outcomes the Future of Evidence-Based Medicine? A Case Study of Back Pain

  • Mor PelegEmail author
  • Tiffany I. Leung
  • Manisha Desai
  • Michel Dumontier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10259)

Abstract

Evidence is lacking for patient-reported effectiveness of treatments for most medical conditions and specifically for lower back pain. In this paper, we examined a consumer-based social network that collects patients’ treatment ratings as a potential source of evidence. Acknowledging the potential biases of this data set, we used propensity score matching and generalized linear regression to account for confounding variables. To evaluate validity, we compared results obtained by analyzing the patient reported data to results of evidence-based studies. Overall, there was agreement on the relationship between back pain and being obese. In addition, there was agreement about which treatments were effective or had no benefit. The patients’ ratings also point to new evidence that postural modification treatment is effective and that surgery is harmful to a large proportion of patients.

Keywords

Multiple Sclerosis Back Pain Amyotrophic Lateral Sclerosis Treatment Rating Propensity Score Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

We thank Ofer Ben-Shachar for supplying the HealthOutcome data and thank him and Tobias Konitzer for the valuable discussions.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mor Peleg
    • 1
    • 2
    Email author
  • Tiffany I. Leung
    • 3
  • Manisha Desai
    • 1
  • Michel Dumontier
    • 1
    • 4
  1. 1.Stanford Center for Biomedical Informatics ResearchStanford UniversityStanfordUSA
  2. 2.Department of Information SystemsUniversity of HaifaHaifaIsrael
  3. 3.Faculty of Health, Medicine and Life SciencesMaastricht UniversityMaastrichtThe Netherlands
  4. 4.Institute of Data ScienceMaastricht UniversityMaastrichtThe Netherlands

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