Estimating the Annual Number of Strokes and the Issue of Imperfect Data: An Example from Australia

Author:

Cadilhac Dominique A.123,Vos Theo4,Thrift Amanda G.12

Affiliation:

1. Stroke & Ageing Research Centre, Monash Medical Centre, Southern Clinical School, Monash University, Clayton, Victoria, Australia

2. Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia

3. University of Melbourne, Melbourne, Victoria, Australia

4. Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA

Abstract

Background Estimates of strokes in Australia are typically obtained using 1996–1997 age-specific attack rates from the pilot North East Melbourne Stroke Incidence (NEMESIS) Study (eight postcode regions). Declining hospitalizations for stroke indicate the potential to overestimate cases. Aims To illustrate how current methods may potentially overestimate the number of strokes in Australia. Methods Hospital separations data (primary discharge ICD10 codes I60 to I64) and three stroke projection models were compared. Each model had age- and gender-specific attack rates from the NEMESIS study applied to the 2003 population. One model used the 2003 Burden of Disease approach where the ratio of the 1996–1997 NEMESIS study incidence to hospital separation rate in the same year was adjusted by the 2002/2003 hospital separation rate within the same geographic region using relevant ICD-primary diagnosis codes. Hospital separations data were inflated by 12.1% to account for nonhospitalized stroke, while the Burden of Disease model was inflated by 27.6% to account for recurrent stroke events in that year. The third model used 1997–1999 attack rates from the larger 22-postcode NEMESIS study region. Results In 2003, Australian hospitalizations for stroke (I60 to I64) were 33 022, and extrapolation to all stroke (hospitalized and nonhospitalized) was 37 568. Applying NEMESIS study attack rates to the 2003 Australian population, 50 731 strokes were projected. Fewer cases for 2003 were estimated with the Burden of Disease model (28 364) and 22-postcode NEMESIS study rates (41 332). Conclusions Estimating the number of strokes in a country can be highly variable depending on the recency of data, the type of data available, and the methods used.

Publisher

SAGE Publications

Subject

Neurology

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2. The Role of Personalized Virtual Reality in Education for Patients Post Stroke—A Qualitative Case Series;Journal of Stroke and Cerebrovascular Diseases;2019-02

3. Analyzing and interpreting “imperfect” Big Data in the 1600s;Big Data & Society;2016-02-17

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