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Best Pract Res Clin Rheumatol. 2016 Dec;30(6):1084-1097. doi: 10.1016/j.berh.2017.07.002. Epub 2017 Aug 5.

Decision support tools in low back pain.

Author information

1
Department of Epidemiology and Biostatistics, VU University Medical Centre, Amsterdam, The Netherlands. Electronic address: v.coupe@vumc.nl.
2
Department of Research, Sint Maartenskliniek, Nijmegen, The Netherlands; Department of Orthopaedics, Radboud University Medical Center, Nijmegen, The Netherlands.
3
Department of Orthopaedics, Radboud University Medical Center, Nijmegen, The Netherlands.
4
Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.
5
Department of Epidemiology and Biostatistics, VU University Medical Centre, Amsterdam, The Netherlands; Department of Health Sciences, Faculty of Earth and Life Sciences, VU University, Amsterdam, The Netherlands.

Abstract

Information from individual classification systems or clinical prediction rules that aim to facilitate stratified care in low back pain is important but often not comprehensive enough to be used to support clinical decision-making. The development and implementation of a clinically useful decision support tool (DST) that considering all key features is a challenging enterprise, requiring a multidisciplinary approach. Key features are inclusion of all relevant treatment options, patient characteristics, and benefits and harms and presentation as an accessible and easy to use toolkit. To be of clinical value, a DST should (1) be based on large numbers of high-quality data, allowing robust estimation of benefits and harms; (2) be presented using visually attractive and easy-to-use software; (3) be externally validated with a clinical beneficial impact established; and (4) include a procedure for regular updating and monitoring. As an illustration, we describe the development; presentation; and plans for further validation, implementation, and updating of the Nijmegen Decision Tool for Chronic Low Back Pain (NDT-CLBP).

KEYWORDS:

Clinical prediction rules; Decision support tool; Low back pain

PMID:
29103551
DOI:
10.1016/j.berh.2017.07.002
[Indexed for MEDLINE]

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