Abstract 156: Establishing An Informatics Framework For Longitudinal Cerebrovascular And Neurological Disease Research

Background: Although developments in computational big data methods have enhanced the ability to meaningfully extract information from hospital EMRs, there are inherent gaps in understanding care utilization and long-term patient outcomes outside of in-patient milieu, particularly across hospital systems. Methods: Utilizing registry data from a 7-hospital stroke certified healthcare system serving a large metropolitan, cohorts were identified for Medicare-insured patients with primary discharge diagnoses of acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), or cerebral amyloid angiopathy (CAA). In collaboration with a CMS Qualified Entity which houses health care utilization data for over 80% of the state population (including 100% of Medicare Fee-for-Service), patient records were securely matched and linked. Socio-demographic and enrollment characteristics for matched cohorts are reported. Results: Medical records and claims data were matched for 98.4% of patients (n=6,531) admitted between 05/2016 and 12/2020 (n=5,789 AIS; 696 ICH; 46 CAA). Across all matched patients, the median (IQR) age at hospital admission was 76.0 (69.0-84.0) (54% female; 56% non-Hispanic White; 24% non-Hispanic Black; 13% Hispanic/Latino; median [IQR] Area Deprivation Index: 4 [2-6]). Age-based standard enrollment represented 86% of patients, with the remainder enrolled due to disability or health complications. Median (IQR) number of total years for patients with Part AB and D coverage was 6.9 (5.0-7.0) and 5.4 (2.9-7.0) years, respectively. At the time of reporting, all-cause death rates among Medicare enrollees who sought care are: 33% (AIS), 55% (ICH), and 41% (CAA). Conclusion: In the absence of systematically captured long-term outcomes data, health informatic pipelines that create linkages across multimodal sources provide a valuable framework for enabling longitudinal research on patients throughout and after stroke hospitalizations.