Introduction: Inferences from population-based cohort studies may be inaccurate as a result of biased coverage of the target population. We investigated the presence of absolute coverage error and selection bias in the Swiss Spinal Cord Injury (SwiSCI) cohort study, using a secondary, nationally representative data source. The proposed methodology is applicable to future Swiss cohort studies aiming to assess their cover-age error.
Methods: ICD-10 codes relating to traumatic spinal cord injuries (TSI) (S14.0, S14.1, S24.0, S24.1, S34.0, S34.1, S34.3, T.060, T.061, T.093, and T91.3) were used to identify incident TSCI cases in 2012 and 2013 from nationwide, administrative hospital discharge data collected by the Swiss Federal Statistical Office. The hospital discharge data were compared with SwiSCI data, and factors associated with receiving rehabilitation in a SwiSCI centre were statistically investigated. Age- and sex-specific incidence rates (IRs) were estimated using hospital discharge data. Different ICD-10 coding combinations were used in sensitivity analyses. Severity of spinal cord injury was characterised by lesion level (paraplegia or tetraplegia) and lesion completeness (complete or incomplete).
Results: In total, 621 administrative cases, compared with 213 SwiSCI cases, were identified. The hospital discharge data differed from SwiSCI data with respect to age (p <0.01). The annual overall IR ranged between 19.9 and 49.7 per one million population, depending on the selection criteria used. Overall, IRs were elevated for men (compared with women), older age groups (compared with 16-30 year olds) and paraplegia (com-pared with tetraplegia). Men, younger persons and people with high tetraplegia (cervical vertebrae C1-C4) were more likely to visit a specialised rehabilitation centre.
Conclusion: There is undercoverage of incident TSCI cases in specialised rehabilitation centres in Switzerland, particularly among the elderly and persons with less severe TSCIs. The extent of coverage error indicated in the ICD-10-based sensitivity analyses can inform future modelling scenarios of national epidemiological estimates of TSCI.