Source
Download (4.65 Mo) The advance of electronic record-keeping and secure methods for sharing and linking health data have led to the creation of massive datasets. These datasets combine sociodemographic, practice, and administrative data about millions of people in thousands of communities. Using traditional methods to sift through it all in search of meaningful patterns and useable new knowledge can be overwhelming. Artificial intelligence (AI) - programming that enables computers to learn - helps us find the meaning in this universe of data. AI, then, is a tool that can help us tailor interventions and direct them to the people and communities who would benefit most. Far from dehumanizing health care, learning machines have the potential to make it more individualized, more responsive, and more equitable.
A first step in understanding where AI may be useful is understanding the population the tool is intended to benefit, and how that population is represented in the data to be analyzed. In this interactive session, Dr. Jaky Kueper describes what the existing datasets tell us about people who received ongoing primary care from a Community Health Centre in 2009-2019, in terms of their sociodemographic and clinical characteristics and their interactions with the health system.
Watch the webinar below, or check out the slide deck here.
#
#Still curious?
#Let's take the next step... together.
Help us build on the learnings from Dr. Kueper's research! On October 21, we'll take a deeper dive into her work with a special brainstorming meeting. The goal of that meeting is to start designing a research project that will lead to the creation of new decision-support tools from electronic health record data. Dr. Kueper will help lead this project as part of her postdoctoral research, alongside Dr. Jennifer Rayner and Dr. Danel Lizotte. Staff from Alliance member organizations, including members of our practice-based learning network (PBLN) are invited to participate. You do not need previous research experience or to be a PBLN member to attend, but we ask that you attend this webinar (or watch the recording).
#Additional Resources
Check out Dr. Kueper's article, Primer for artificial intelligence in primary care, published in Canadian Family Physician in December 2021. It's an introduction to introduces AI and machine learning; the types of tasks that AI methods are currently capable of performing, with examples from primary care; and describes specialized techniques that might be needed to perform tasks with language and image data.
Another paper, co-authored by Dr. Kueper alongside Dr. Jennifer Rayner, the Alliance's Director of Research & Evaluation; Dr. Merrick Zwarenstein, an expert in learning health systems; and Lorri Zagar, an expert in Quality Improvement in primary health care, will soon be published in the International Journal of Distribued and Parallel Systems. You can view a preprint here. This article demostrates how AI was used health to create an epidemiological description of a client population based on health system data from CHCs in Ontario.
#Keynote Speaker
 |
Dr. Jaky Kueper, a postdoctoral associate at Western University, is a researcher in epidemiology and computer science. She works on developing and using machine learning to improve primary health care for people with complex health needs. During this presentation, Jaky shared findings from her PhD research and invited the audience to reflect on them and share their reactions. Jaky has earned numerous awards, scholarships and accolades for her work. In October 2022, she received the prestigious Governor General’s Gold Medal recognizing her extraordinary academic performance throughout her combined PhD in Epidemiology and Biostatistics and Computer Science – the first at Western.
|