Cormac Rea

DSI welcomes the Centre for Addiction and Mental Health (CAMH) as a partner

By: Cormac Rea

The Data Sciences Institute (DSI) aspires to build meaningful collaborations with organizations that share mutual goals of engaging and supporting world-class data science research and training, across all sectors. We are excited to announce a new partnership with the Centre for Addiction and Mental Health (CAMH).

CAMH is Canada’s largest mental health teaching hospital and one of the world’s leading research centres in its field. CAMH is fully affiliated with the University of Toronto and is a Pan American Health Organization/World Health Organization Collaborating Centre.

With a dedicated staff of more than 5,000 physicians, clinicians, researchers, educators and support staff, CAMH offers outstanding clinical care to more than 38,000 patients each year. The organization conducts groundbreaking research, provides expert training to health care professionals and scientists, develops innovative health promotion and prevention strategies, and advocates on public policy issues at all levels of government. And through its Foundation, CAMH is working to raise tens of millions of additional dollars to fund new programs and research and augment services.

“CAMH is already a leader in data science and best practices, particularly through our Krembil Centre for Neuroinformatics,” said Dr. Aristotle Voineskos, Vice President Research & Director Campbell Family Mental Health Research Institute at CAMH. “A partnership with the DSI will better connect our organizations and the larger Toronto Academic Health Sciences Network, fostering new approaches and collaborations among hospitals and the University of Toronto. Additionally, it provides CAMH scientists and trainees with access to vital seed funding and scholarships, further advancing our mission to transform mental health research and care.”

The DSI fuels innovation and fosters the exchange of ideas, connecting a diverse community of researchers and trainees that represent a wide array of disciplines. By connecting data science researchers, data and computational platforms, and external partners, the DSI advances research and nurtures the next generation of data science researchers. As one of our external funding partners, researchers at CAMH can apply for research grants and support, training, as well as participate in networking opportunities at the DSI.

“The DSI is very proud to announce this partnership, expanding our research community to include such a widely recognized and reputable leader in social responsibility and mental health issues as CAMH. Our commitment to building a hub of data science researchers that can accelerate the impact of data across disciplines and affect positive social change will be significantly enriched by having researchers from CAMH join our community,” said Lisa Strug, DSI Director. 

Data Sciences Institute and Dalla Lana School of Public Health host government and healthcare professionals at Policy Lab workshop

By: Andrea Smitko

The Data Sciences Institute’s (DSI) Policy Lab, a collaboration with the Dalla Lana School of Public Health (DLSPH), recently hosted the workshop “Data Science Tools and Adoption for Health and Beyond,” which brought together researchers, healthcare professionals and government representatives to discuss how the data sciences can be used to inform public healthcare policy.

The Policy Lab aims to support work on data sciences and public policy across sectors and ensure that its capacity-building approach meets the needs of complex policy environments. The Policy Lab works with ministries, agencies and other policy-oriented groups to build capacity and demand across the public sector for data science to foster a community of data scientists and data science users and increase the use of data sciences in the development of policy to create healthier and more just societies.

 

L-R: Tina Badiani, Researcher-In-Residence, Data Sciences Institute; Laura Rosella, Co-Chair Policy Lab, and Associate Director, Education & Training, Data Sciences Institute; Lisa Strug, Director, Data Sciences Institute; Steven Habbous, Researcher-In-Residence, Data Sciences Institute and Lead Methodologist, Strategic Analytics, Ontario Health; Jeremy Herring, Researcher-In-Residence, Data Sciences Institute; Michael Hillmer, Co-Chair Policy Lab, and Assistant Deputy Minister, Digital and Analytics Strategy, Ontario Ministry of Health/ Ministry of Long-Term Care; Adalstein Brown, Professor and Dean, Dalla Lana School of Public Health; Helen Lasthiotakis, Director, Operations & Strategy, Data Sciences Institute. (photo: Harry Choi Photography)

This workshop was an opportunity for the DSI and DLSPH to share insights and engage in conversation based on initial collaborative work in public health and health systems. The partnership also undertook specific projects to define the context better and understand barriers to overcome to enable data science capacity in public sector organizations; in particular, it focused on the findings from the Policy Lab’s Researchers-in-Residence.

The event began with a presentation by Policy Lab co-chairs Laura Rosella, associate director, education & training, DSI, faculty member and associate professor, DLSPH, and associate professor, Laboratory Medicine & Pathobiology, Faculty of Medicine, and Michael Hillmer, assistant deputy minister, digital & analytics strategy, Ontario Ministry of Health/Ministry of Long-Term Care, and associate professor, IHPME, who spoke about the Policy Lab and the work it’s doing to understand barriers preventing data science capacity in public sector organizations.

“We’re seeing all of this work with data sciences and AI in the private sector and in key areas in research. We want to have an impact on society, so we’re trying to increase the use of data science in the policy space and we’re going to focus on health policy as a start, but a lot of the learnings are going to extend beyond health,” says Rosella. “The idea was to bring in researchers-in-residence — people that work in public sector health organizations — to spend time at the university and help us define what it means to meaningfully collaborate in advanced data science and use it for policy decision making.” 

 

Data Sciences Institute and Dalla Lana School of Public Health, University of Toronto, Policy Lab – “Data Science Tools and Adoption for Health and Beyond” (photo: Harry Choi Photography)

During the workshop, three researchers-in-residence presented key findings from several recent case studies; some of which included analyzing the use of AI to maintain and update a large public health registry, determining machine learning’s accuracy in identifying non-melanoma skin cancers, and measuring the effectiveness of AI to categorize exposures when investigating cases of food born illnesses. 

“These were examples of successful applications of AI or machine learning in the public health sector space. We saw that in all three there were commonalities,” says researcher-in-residence Steven Habbous, lead methodologist, strategic analytics, Ontario Health. “AI enabled the completion of work that was inefficient for us to do. It does improve the speed and ability to implement effective interventions, and ultimately makes better use of the data we have. It wasn’t about acquiring new data, the data was already there, but leveraging it for our needs — that’s where it shines.”

There were several collaborative activities throughout the day, where attendees engaged in rigorous discussions on topics such as how to build data science functionality in public sector organizations, and education and capacity building. The event also featured a presentation that detailed important items for organizations to consider as part of a data science toolkit, including the importance of securing dedicated funding and resources, recruitment and upskilling staff, and change management. A common theme throughout was the need for a strong buy-in from leadership and an organizational structure that supports the integration and use of AI and machine learning.   

“How do you create a culture of evidence and data? It starts with leadership, that’s incredibly important, and then you focus on people, process and tools,” said Hillmer. “That’s what this fellowship is all about. You can now go off and be the proselytizers of data science in organizations. It doesn’t have to be a grand initiative, it just needs to be you being creative. Whatever form it takes, just get started with that first step and build that culture.”