Researchers use big-data analytics to battle childhood chronic disease
Why the recent focus on IBD, asthma, and diabetes in health research?
There has been an increase in the incidence of these pediatric immune-mediated conditions. Many of them are also more prevalent in developed countries. A pair of recent studies by Dr. Eric Benchimol examined why Ontario immigrants from countries with low prevalence of these diseases might be at increased risk with early life exposure to the Canadian environment. However, the reasons behind the increased incidence of these immune-mediated diseases have not yet been clearly identified, and finding the predisposing factors is a high priority for healthcare providers.
Why big-data analytics as a research method?
With advances in computing and the availability of large and diversified datasets, big-data analytics is an increasingly useful method in health services research. It allows researchers to identify hidden patterns and relationships in a set of variables that would otherwise be overlooked. Researchers have opportunities to gain insights into early-life risk factors by virtue of linkable datasets held at the Institute for Clinical Evaluative Sciences (ICES). These diverse datasets cover health services records; medical and clinical information; data from newborn metabolic screening; immigration data; and socio-demographic data.
Professor Bijan Raahemi of the Telfer School and Professor Eric Benchimol of the Faculty of Medicine and the CHEO Research Institute have teamed up to identify factors that put children at greater risk of developing diseases such as asthma, type 1 diabetes, and inflammatory bowel disease. Together with doctoral student Mohammad Hossein Tekieh, they will be using novel big-data analytics to mine Ontario health data, and their findings are expected to contribute to improved health outcomes and lower costs related to chronic care.
“Investigating unknown patterns in health administrative records and population-based data offers exciting potential to improve health services for children,” said Raahemi, a Full Professor of Data Analytics and the Director of the Knowledge Discovery and Data Mining Research Laboratory. “Applying the latest data mining and artificial intelligence tools can generate important insights for better pediatric care, including more targeted and efficient health system interventions.”
The outcomes of the research could also identify how different risk factors might affect one another. Interactions between genetic predisposition, immune characteristics, and the environment are thought to play a role in the increased incidence of IBD, asthma, diabetes and other immune-mediated diseases.
Dr. Benchimol, an Associate Professor of Pediatrics and Epidemiology at the uOttawa Faculty of Medicine and a Core Scientist at the Institute for Clinical Evaluative Sciences (ICES), explained: “Using various analytical models and data mining techniques to explore the interaction among these factors holds great promise in terms of identifying the at-risk population and early intervention to prevent chronic disease or provide timely treatment.”
Mohammad Hossein Tekieh, a Ph.D. student in the Electronic Business Technologies Program at the University of Ottawa, will lead the data analysis. Funding for this project was provided by Mitacs and the CHEO Research Institute.
Published: January 19, 2017 | Category: Research Leadership