Validation of a Back Pain Severity Prediction Algorithm: A Cross-Sectional Study with Updated Healthcare Costs for Back Pain Patients Based on the Graded Chronic Pain Scale

Abstract Background: Treatment of chronic lower back pain (CLBP) should be stratified for best medical and economic outcome. To improve targeting of potential participants for exclusive therapy offers by payers, Freytag et al. developed an algorithm to identify back pain chronicity classes (CC) based on claims data. The aim of this study was the external validation of the algorithm, as this was previously lacking.Methods: Administrative claims data and self-reported patient information of 3,506 participants of a health management programme of a private health insurance in Germany were used to validate the algorithm. Sensitivity, specificity and Matthews correlation coefficient (MCC) were computed comparing the prediction with actual grades based on von Korff’s Graded Chronic Pain Scale (GCPS). Secondary outcome was an updated view on direct health care costs (€) of back pain (BP) patients grouped by GCPS.Results: Results showed a fair correlation between predicted CC and actual GCPS grades. A total of 69.7 % of all cases were classified correctly. Sensitivity and specificity rates of 54.6 % and 76.4 % underlined the accuracy. Correlation between CC and GCPS with an MCC of 0.304 also indicated a fair relationship between prediction and observation. Cost data could be clearly grouped by GCPS: the higher the grade, the higher the costs and health care usage.Conclusions: This was the first study to compare the predicted BP severity using claims data with actual BP severity by GCPS. Based on the results, the usage of the CC as a single tool to determine who receives treatment of CLBP cannot be recommended. The CC is a good tool to segment candidates for BP specific types of intervention. However, it cannot replace a medical screening at the beginning of an intervention as the rate of false negatives is too high. Trial registration: The study was conducted using routinely collected data from an intervention, which was evaluated and registered previously at the German Clinical Trials Register under DRKS00015463 retrospectively (4 Sept 2018). The informed consent and the self-reported questionnaire have remained unchanged since the study and are therefore still valid in accordance with the ethics proposal.