Clinical algorithms to aid osteoarthritis guideline dissemination.


Journal Article (Review)

BACKGROUND: Numerous scientific organisations have developed evidence-based recommendations aiming to optimise the management of osteoarthritis (OA). Uptake, however, has been suboptimal. The purpose of this exercise was to harmonize the recent recommendations and develop a user-friendly treatment algorithm to facilitate translation of evidence into practice. METHODS: We updated a previous systematic review on clinical practice guidelines (CPGs) for OA management. The guidelines were assessed using the Appraisal of Guidelines for Research and Evaluation for quality and the standards for developing trustworthy CPGs as established by the National Academy of Medicine (NAM). Four case scenarios and algorithms were developed by consensus of a multidisciplinary panel. RESULTS: Sixteen guidelines were included in the systematic review. Most recommendations were directed toward physicians and allied health professionals, and most had multi-disciplinary input. Analysis for trustworthiness suggests that many guidelines still present a lack of transparency. A treatment algorithm was developed for each case scenario advised by recommendations from guidelines and based on panel consensus. CONCLUSION: Strategies to facilitate the implementation of guidelines in clinical practice are necessary. The algorithms proposed are examples of how to apply recommendations in the clinical context, helping the clinician to visualise the patient flow and timing of different treatment modalities.

Full Text

Duke Authors

Cited Authors

  • Meneses, SRF; Goode, AP; Nelson, AE; Lin, J; Jordan, JM; Allen, KD; Bennell, KL; Lohmander, LS; Fernandes, L; Hochberg, MC; Underwood, M; Conaghan, PG; Liu, S; McAlindon, TE; Golightly, YM; Hunter, DJ

Published Date

  • September 2016

Published In

Volume / Issue

  • 24 / 9

Start / End Page

  • 1487 - 1499

PubMed ID

  • 27095418

Pubmed Central ID

  • 27095418

Electronic International Standard Serial Number (EISSN)

  • 1522-9653

Digital Object Identifier (DOI)

  • 10.1016/j.joca.2016.04.004


  • eng

Conference Location

  • England