Background: High quality mortality data is foundational for effective public health policy and intervention. Cause of death data are derived from death certificates and coded using the World Health Organization ICD-10 framework. For people with neurodevelopmental disabilities, the disability itself (e.g., cerebral palsy) is often reported as the underlying cause of death. This practice is problematic as it obscures modifiable causes and limits prevention.

Methods: Two descriptive analyses were conducted. First, death certificate data were examined to identify cases where neurodevelopmental disability ICD-10 codes were assigned as the underlying cause. We assessed whether the disability was documented by the certifier as a direct or contributing cause, and whether, following coding, it was classified as the underlying or an associated cause. Second, National Disability Insurance Scheme (NDIS) data were used to identify a population with neurodevelopmental disability, and deaths with disability reported as the underlying cause were identified. A structured recoding approach reassigned underlying causes, enabling identification of masked causes.

Results: Neurodevelopmental disability appeared on 9,878 death certificates, with 40% recorded as the underlying cause of death. Among these, 72% were documented as a direct cause, indicating certifier-driven misclassification, with the remainder arising through coding processes. Within the NDIS cohort (n=4,182 deaths), 23% had disability recorded as the underlying cause. Recoding revealed that leading underlying causes were frequently preventable or manageable conditions, including aspiration pneumonia, dementia, and respiratory infections.

Conclusion: Current certification and coding practices reduce the quality of mortality data for people with neurodevelopmental disabilities. Misclassification masks actionable causes of death and undermines efforts to improve health outcomes. As death certification and coding processes are internationally standardised, this represents a broader data quality issue across health systems. Targeted education for certifiers, alongside systematic recoding protocols, are required to ensure mortality data reflects preventable causes and supports effective policy and intervention.