Is crowdsourcing patient-reported outcomes the future of evidence-based medicine? A case study of back pain

Mor Peleg, Tiffany I. Leung, Manisha Desai, Michel Dumontier

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Proceedings
EditorsAnnette [surname]ten Teije, Christian Popow, Lucia Sacchi, John H. Holmes
PublisherSpringer Verlag
Pages245-255
Number of pages11
ISBN (Print)9783319597577
DOIs
StatePublished - 2017
Event16th Conference on Artificial Intelligence in Medicine, AIME 2017 - Vienna, Austria
Duration: 21 Jun 201724 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10259 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Conference on Artificial Intelligence in Medicine, AIME 2017
Country/TerritoryAustria
CityVienna
Period21/06/1724/06/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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