Indication for spinal surgery: associated factors and regional differences in Germany

Abstract

Abstract Background Rising surgery rates have raised questions about the indications for spinal surgery. The study investigated patient-level and regional factors associated with spinal surgery for patients with spinal diseases. Methods We undertook a cohort study based on routine healthcare data from Germany of 18.4 million patients within 60.9 million episodes of two patient-years before a possible spinal surgery in the time period 2008 to 2016. Using a Poisson model, the effects of a broad range of patient-related (sociodemographic, morbidity, social status), disease- and healthcare-related (physicians’ specialty, conservative treatments) and regional variables were analyzed. Results There was substantial regional heterogeneity in the occurrence of spinal surgery which decreased by only one quarter when controlling for the various determinants assessed. Previous musculoskeletal and mental health disorders as well as physical therapy were associated with a lower probability of surgery in the fully-adjusted model. Prescriptions for pain medication and consultations of specialists were associated with a higher probability of surgery. However, the specific severity of the vertebral diseases could not be taken into account in the analysis. Furthermore, a substantial proportion of patients with surgery did not receive a consultation with an outpatient specialist (29.5%), preoperative diagnostics (37.0%) or physical therapy (48.3%) before hospital admission. Conclusion This large study on spinal diseases in Germany highlights important patterns in medical care of spinal diseases and their association with the probability of spinal surgery. However, only a relatively small proportion of the regional heterogeneity in spinal surgery could be explained by the extensive consideration of confounders, which suggests the relevance of other unmeasured factors like physicians’ preferences.

Keywords

• Spinal surgery
• Back pain
• Health service research
• Secondary data analysis