A Bayesian Network Decision Support Tool for Low Back Pain Using a RAND Appropriateness Procedure: Proposal and Internal Pilot Study

Hill A., Joyner C. H., Keith-Jopp C., YET B., TUNCER ŞAKAR C., Marsh W., ...More

JMIR RESEARCH PROTOCOLS, vol.10, no.1, 2021 (ESCI) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 10 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.2196/21804
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, EMBASE, Directory of Open Access Journals
  • Keywords: back pain, decision making, Bayesian methods, consensus, RED FLAGS, MANAGEMENT
  • Middle East Technical University Affiliated: Yes


Background: Low back pain (LBP) is an increasingly burdensome condition for patients and health professionals alike, with consistent demonstration of increasing persistent pain and disability. Previous decision support tools for LBP management have focused on a subset of factors owing to time constraints and ease of use for the clinician. With the explosion of interest in machine learning tools and the commitment from Western governments to introduce this technology, there are opportunities to develop intelligent decision support tools. We will do this for LBP using a Bayesian network, which will entail constructing a clinical reasoning model elicited from experts.