Sometimes it takes an algorithm to improve the health of a population.
The project has been commissioned by the Teachers Health Foundation, a private charitable trust that is part of Teachers Federation Health.
Using the anonymised data from members’ health claims, Dr Wickramasuriya and his team hope to uncover patterns that will prompt further, targeted, research.
“One area that we are looking at is the co-morbidity of diseases,” he said.
“For example, it is already well-known that diabetes is associated with heart and kidney problems.
“When we apply machine-learning, we are hoping to uncover other unknown, but profound patterns among other diseases.”
Although still in its early stages – the one-year project started in September last year – the approach is already yielding results.
The project – which is called ‘Uncovering prevalent and emerging health issues in the education sector through claims data analysis’ – intends to contribute to the wider community by researching and supporting a safe and healthy education system.
This will be achieved by identifying medical and health issues prevalent in the education sector and attempting to create the most effective ways of providing high quality care for teachers, lecturers and support staff.
SMART’s job is to develop systems to analyse claims information, enabling the Foundation to formulate appropriate and relevant research questions for future medical research grants.
Part of that work will include a comparison of findings with available population and public health data to identify any differences between teachers and the general population.