Allure of Big Data for Monitoring the Quality of Care and Outcomes after Stroke

Stroke is a leading cause of death and disability in Australia and globally. In Australia, ~40,000 people suffer a stroke each year. Survivors often report poor quality of life and increased levels of disability, and are at an elevated risk of cardiovascular disease or death. Any disability or other consequences may considerably impact long-term productivity, and incur healthcare and socioeconomic costs. These consequences are more profound in young survivors, given their longer life expectancy. There is a growing interest in the use of large, routinely collected data from various sources, often called “big data,” to generate real-world evidence for understanding and improving the care for stroke and outcomes after stroke. The project sits within the Big Data, Epidemiology and Prevention Division of the Stroke and Ageing Research (STAR) group. We are leaders in big data evolution for stroke research in Australia. Major current projects available include:  Understanding the epidemiology of stroke in Australia, particularly the trends and risk factors among young Australians (aged <50 years).  Understanding gaps in the continuum of care (pre-hospital, hospital, general practice, rehabilitation) for preventing and managing stroke  Describing the short and long-term outcomes of stroke.  Describing the influence of infections (e.g., influenza), and maternal vaccinations (e.g., influenza vaccination) during pregnancy, on the incidence of stroke. Data for these projects are being obtained from the following sources:  The Australian Stroke Clinical Registry  Administrative health data sources, e.g., hospital, Medicare, Pharmaceutical, and general practice datasets  Stroke clinical trials linked to administrative datasets. These projects provide a good opportunity for students to gain knowledge in epidemiological, public health, and health services research. Students will also develop practical skills in biostatistics, data linkage, and data analysis, using contemporary and sophisticated methods. Supervision and support will be provided by a multidisciplinary team of epidemiologists, health services researchers, biostatisticians, and data linkage experts.