Agreement Between Self-Reported Information and Administrative Data on Comorbidities, Imaging and Treatment in Denmark – A Validation Study of 38,745 Patients with Knee or Hip Osteoarthritis

Abstract

Purpose

To validate self-reported information obtained from patients with knee or hip osteoarthritis (OA) in primary care against administrative data from the three national Danish registries.

Patients and Methods

We compared the baseline and 12-month follow-up data from 38,745 patients with knee or hip OA participating in the Good Life with osteoArthritis in Denmark (GLA:D^®) program with registry-based data on joint surgeries, pain medication dispensing, radiographs, and hospital diagnoses. Agreement was calculated using Cohen’s Kappa (k) and percentage agreement, both with 95% CI.

Results

There was a moderate agreement between self-report and registry-based data for previous knee surgery (k=0.58, 84.99%) and a substantial agreement for previous hip surgery (k=0.73, 97.05%). Agreement varied from 0.05 to 0.95 and 84.99% to 99.94% for different types of surgeries with lowest agreement for collateral ligament surgery (k=0.05, 99.82%) and highest agreement for joint replacement (k=0.95, 99.54% for knee; k=0.95, 99.48% for hip). There was a moderate agreement (k=0.41, 81.59%) for knee and a slight agreement (k=0.20, 64.79%) for hip radiographs. Agreement varied from 0.01 to 0.53 and 65.39% to 99.90% for pain medication with lowest agreement for topical NSAID (k=0.01, 95.00%) and highest agreement for opioids (k=0.53, 92.56%). For comorbidities, agreement varied from 0.14 to 0.90 and 78.07% to 98.91%, with lowest agreement for anemia or other blood disease (k=0.14, 97.63%) and highest agreement for diabetes (k=0.90, 98.73%).

Conclusion

As the most common types of pain medication used by patients with OA can be bought over-the-counter and as most OA patients are treated in primary care, which is often not covered by national registries, self-report of pain medication use and comorbidities is preferred but cannot be sufficiently validated against registry-based data. Future studies collecting self-reported information on joint surgery and pain medication from patients with OA should use a less detailed categorization to improve accuracy.

Keywords:

• self-report
• data validity
• osteoarthritis
• Denmark

Acknowledgments

The authors would like to acknowledge all the participants and physiotherapists who have engaged in the GLA:D program and provided data for this study. Furthermore, Jacob Harbo Andersen is acknowledged for assisting in data management and analysis.

Disclosure

Dr. Roos and Dr. Skou are the developers of the Good Life with osteoArthritis in Denmark (GLA:D) program, a not-for-profit initiative to implement clinical guidelines in primary care. Professor Ewa M. Roos reports I am deputy editor of Osteoarthritis and Cartilage, the developer of Knee injury and Osteoarthritis Outcome Score (KOOS) and several other freely available patient-reported outcome measures and co-founder of the Good Life with Osteoarthritis in Denmark (GLA:D), a not-for profit initiative to implement clinical guidelines in primary care. Professor Soren T. Skou report grants from the Danish Physiotherapy Association’s fund for research, education and practice development, the Danish Rheumatism Association, and the Physiotherapy Practice Foundation, during the conduct of the study; and I am the co-developer of the Good Life with osteoArthritis in Denmark (GLA:D) program (where some of the data for the study is from), a not-for profit initiative to implement clinical guidelines in primary care. The authors report no other conflicts of interest related to this study.

The abstract of this paper was presented at the 2021 OARSI Virtual World Congress as a poster presentation with interim findings. The poster’s abstract was published in Volume 29, Supplement 1 in Osteoarthritis and Cartilage: https://doi.org/10.1016/j.joca.2021.02.345.

Additional information

Funding

Dr. Skou is currently funded by a grant from Region Zealand (Exercise First) and a grant from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 801790).