Validity of early-onset dementia diagnoses in VA electronic medical record administrative data

Abstract Objective To determine the validity of diagnoses indicative of early-onset dementia (EOD) obtained from an algorithm using administrative data, we examined Veterans Health Administration (VHA) electronic medical records (EMRs). Method A previously used method of identifying cases of dementia using administrative data was applied to a random sample of 176 cases of Post-9/11 deployed veterans under 65 years of age. Retrospective, cross-sectional examination of EMRs was conducted, using a combination of administrative data, chart abstraction, and review/consensus by board-certified neuropsychologists. Results Approximately 73% of EOD diagnoses identified using existing algorithms were identified as false positives in the overall sample. This increased to approximately 76% among those with mental health conditions and approximately 85% among those with mild traumatic brain injury (TBI; i.e. concussion). Factors related to improved diagnostic accuracy included more severe TBI, diagnosing clinician type, presence of neuroimaging data, absence of a comorbid mental health condition diagnosis, and older age at time of diagnosis. Conclusions A previously used algorithm for detecting dementia using VHA administrative data was not supported for use in the younger adult samples and resulted in an unacceptably high number of false positives. Based on these findings, there is concern for possible misclassification in population studies using similar algorithms to identify rates of EOD among veterans. Further, we provide suggestions to develop an enhanced algorithm for more accurate dementia surveillance among younger populations.