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We’re living in the era of big data. Whether it’s location settings on our cellphones, cookies informing the types of digital ads that we see or activity trackers on our wrists, vast amounts of data are being generated and collected.

As the already massive amount of information collected increases, a dedicated group of researchers at the Methods Hub, within the Cumming School of Medicine’s (CSM) O’Brien Institute for Public Health, are developing new ways to analyze and use this information to support initiatives and improve patient outcomes in Canadian hospitals.

While nearly all hospitals use data in some form to make decisions, the health system has a long way to go to fully realize the potential of data-driven improvement, according to Methods Hub director Maria Santana, PhD.

“It’s easy to generate data, but many hospitals aren’t utilizing their data effectively,” says Santana, an assistant professor with the CSM’s departments of Community Health Sciences and Paediatrics, and a member of the O’Brien and Libin Cardiovascular Institutes. “Developing the tools to understand and interpret this information quickly will help providers enhance the patient experience while improving care and reducing costs.”

Methods Hub researchers recently worked with the Canadian Institute for Health Information (CIHI) to develop a data-driven way to identify patient safety incidents — events or occurrences that could have resulted, or did result, in unnecessary harm to the patient. By measuring this information, it’s possible to improve the resources available to heath  are practitioners to support patient safety improvements.

Shaping how the world shares information for better health

With more information becoming available as a result of digitization, the development of automated analytic methods is crucial, says Methods Hub researcher and founding member Hude Quan (PhD’98).

In order to track and monitor diseases and mortality rates, the World Health Organization (WHO) has developed an International Classification of Diseases (ICD) standard, which shapes how health professionals, scientists and policy makers communicate and share information relating to health care.

Research led by Quan on improving the ability to define medical conditions in ICD administrative data has garnered international recognition. In 2015, the O’Brien Institute was officially designated a WHO Collaborating Centre for Classification, Terminology and Standards. The centre is working closely with partners at Stanford University and the Mayo Clinic, a non-profit medical practice and medical research group based in Rochester, Minn., to standardize international practices regarding the collection and use of information.

Data, however, is not always gathered with the same language. This makes it challenging to use this research as a tool to improve outcomes.

“The main question is, ‘How can we know how many people die and why?’” says Quan, who’s also a member of the O’Brien and Libin Institutes, and a professor with the Department of Community Health Sciences. “We can count in Alberta or Canada, but how do we determine what that number is when the scope becomes global?” 

In the end, the intent is to provide better information to policy makers on the spread, risk and prevention of disease, as well as measuring health system safety and quality. Quan says this will have a major impact both abroad and at home.

“When health researchers are able to leverage data, they’re better able to improve health, prevent and detect disease at an earlier stage, and personalize interventions," says Quan.

Other big data initiatives by the O'Brien Institute

The ��ݮ����Ƶ���� Biostatistics Centre (UCBC): Made up of members from Alberta Health Services, the University of British Columbia, and the faculties of Veterinary Medicine, Science, Nursing, Kinesiology and the Cumming School of Medicine at the ��ݮ����Ƶ����, the UCBC is looking at how to better mine and classify big data to improve the health of populations. Its work has garnered the attention of the Canadian Statistical Sciences Institute and has led to the creation of the UCBC’s own Rocky Mountain Data Sciences Training Centre, which provides graduate level training on big data.

International Population Data Linkages Network (IPDLN): Sharing the directorship with Ontario’s Institute for Clinical Evaluative Sciences (ICES), the O’Brien Institute is serving as half of the IPDLN’s secretariat and directorship from 2016 to 2018. The network is made up of members from North America, Europe and Australasia. It brings together data scientists and research from all over the world in an attempt to put data to work, improving the health of populations at a global scale.