Development of an internationally agreed national minimum dataset for low back pain: a modified Delphi study
McKenzie, Bayden, Ferreira, Giovanni E., Haas, Romi, Gorelik, Alexandra, Maher, Chris G., Buchbinder, Rachelle, and International Low Back Pain Minimum Dataset Delphi Panel (2025) Development of an internationally agreed national minimum dataset for low back pain: a modified Delphi study. The Spine Journal. (In Press)
|
PDF (Accepted Publisher Version)
- Published Version
Available under License Creative Commons Attribution. Download (2MB) | Preview |
Abstract
BACKGROUND Low back pain is the leading cause of disability worldwide and the burden is expected to rise due to increases in ageing and population growth. The 2018 Lancet Low Back Pain Series proposed urgent actions to reverse the rising trend of disability due to low back pain including the need for a set of data indicators to routinely monitor progress in achieving these actions worldwide.
PURPOSE To reach international consensus on a national minimum dataset of low back pain indicators that could be used across all countries to monitor progress in improving care and reducing disability from low back pain.
STUDY DESIGN Modified Delphi study.
SAMPLE Nineteen participants attended a preliminary workshop at the 2023 International Back and Neck Pain Forum, The Netherlands. Subsequently, 305 and 339 participants (researchers, clinicians, policy makers, educators, and consumers) completed Delphi surveys Rounds 1 and 2, respectively.
OUTCOME MEASURES A 9-point Likert scale rated importance and feasibility of low back pain indicators (1 = not important or feasible; 9 = extremely important or feasible, 0 unsure). In Round 2, indicators that achieved consensus on importance and feasibility were ranked “most important” (top-ranked) to “least important.”
METHODS Workshop participants were divided into four groups and asked to independently consider the importance and feasibility of 105 indicators identified from previous reviews divided into six themes. Participants could remove indicators considered unimportant or not feasible. This required unanimous agreement from independent workshop groups. Participants could also suggest improvements to the wording of indicators, the best unit of measure and additional missing indicators.
RESULTS Thirty-eight indicators were recommended by workshop participants for inclusion in the Delphi study. Survey responses over two rounds reached consensus for 21 indicators (11 burden, 10 care) ranked from most to least important after reaching consensus on importance and feasibility in Round 1. Number of work days lost and number of opioid prescriptions for low back pain were the highest ranked indicators for burden and care, respectively. Importance rankings were similar across subgroups comparing high-income and low- and middle-income countries, and consumers and non-consumers.
CONCLUSION We reached international consensus that 21 indicators could be used to monitor progress in improving care and outcomes for people with low back pain globally. Future work is needed to confirm the acceptability and feasibility of these indicators across countries, and, if implemented, to determine their value over time.
| Item ID: | 89501 |
|---|---|
| Item Type: | Article (Research - C1) |
| ISSN: | 1878-1632 |
| Related URLs: | |
| Copyright Information: | Copyright: © 2025 The Authors. Published by Elsevier Inc. Creative Commons Attribution (CC BY 4.0) |
| Additional Information: | Carol Flavell is a member of the International Low Back Pain Minimum Dataset Delphi Panel. All collaborators are listed at the end of the article. |
| Funders: | National Health and Medical Research Council (NHMRC) |
| Projects and Grants: | NHMRC Early Leadership Fellowship (APP2009808), NHMRC Leadership Grants (APP1194283), NHMRC Leadership Grants (APP1194483) |
| Date Deposited: | 12 Nov 2025 23:55 |
| FoR Codes: | 42 HEALTH SCIENCES > 4201 Allied health and rehabilitation science > 420109 Rehabilitation @ 100% |
| SEO Codes: | 20 HEALTH > 2001 Clinical health > 200103 Human pain management @ 100% |
| More Statistics |
