Determining the Optimal Methodology for Identifying Incident Stroke Deaths Using Administrative Datasets Within Australia

Abstract

Quantifying stroke incidence and mortality is crucial for disease surveillance and health system planning. Administrative data offer a cost-effective alternative to "gold standard" population-based studies. However, the optimal methodology for establishing stroke deaths from administrative data remains unclear. We aimed to determine the optimal method for identifying stroke-related deaths in administrative datasets as the fatal component of stroke incidence, comparing counts derived using underlying and all causes of death (CoD). Using whole-population multijurisdictional person-level linked data from hospital and death datasets from South Australia, the Northern Territory, and Western Australia, we identified first-ever stroke events between 2012 and 2015, using underlying CoD and all CoD to identify fatal stroke counts. We determined the 28-day case fatality for both counts and compared results with gold standard Australian population-based stroke incidence studies. The total number of incident stroke events was 16,150 using underlying CoD and 18,074 using all CoD. Case fatality was 24.7% and 32.7% using underlying and all CoD, respectively. Case fatality using underlying CoD was similar to that observed in four Australian "gold standard" population-based studies (20%-24%). Underlying CoD generates fatal incident stroke estimates more consistent with population-based studies than estimates based on stroke deaths identified from all-cause fields in death registers.