Project Overview

Learning Health System for Breast Cancer

Hamilton Health Sciences (HHS)’ Centre for Data Science and Digital Health (CREATE) is partnering with cancer genetics expert Dr. Andrea Eisen to expand the hospital’s artificial intelligence (AI) Learning Health System for Breast Cancer to include genetics information from patients. Eisen is the Buffett Taylor Chair in Breast Cancer Research, a position previously held by retired HHS medical oncologist and renowned breast cancer researcher Dr. Mark Levine.

Learning Health System

Expanding the LHS for Breast Cancer to include genetics information

Eisen is providing the clinical leadership as a medical oncologist and leader in cancer genetics and high-risk breast cancer while CREATE brings expertise in software engineering, AI and data sciences, with health care as the niche specialty.

MyHeadHealth App
datalines

Challenges

Expanding the Learning Health System for Breast Cancer to include genetics information from patients will help close gaps in care.

“We’re looking at using the Learning Health System to, for example, identify people diagnosed with breast cancer who might have benefitted from genetic testing but weren’t offered it. For instance, the criteria for qualifying for genetic testing may have been more restrictive when they were diagnosed. Or they may have felt that the timing wasn’t right because they were in the middle of treatment.”

– Dr. Andrea Eisen

Imaging
Petch, Eisen, Levin

Solution

BRCA1 and BRCA2 are the most common genes associated with hereditary breast and ovarian cancer. By identifying people with BRCA genes early, preventative measures such as surgery can be taken in order to avoid them getting these cancers.

“By including genetics, we’re opening up an incredibly powerful resource to ask critical questions about how our system is doing at delivering care, and the quality of the outcomes we’re getting. This means we can take a much closer look at this patient population, to help ensure they receive the care they need.”

-Dr. Jeremy Petch

Summary

AI-based Learning Health System

The Learning Health System for Breast Cancer uses AI to rapidly collect, sort and interpret breast cancer patients’ medical information, providing HHS doctors, leaders and researchers with data they request in real time.

The AI database currently includes diagnoses, scans, tumor pathology, demographics, social determinants of health, medications, treatments, surgeries and survivorship. Prior to this platform, it took months or even years, to search for and collect data to determine, for example, if certain patient groups faced barriers to care. Using AI, this information can be gathered and made available almost instantly.

A grant was secured from the Canadian Cancer Society to expand the system to include genetics information from HHS patients. It’s also expected to include data from St. Joseph’s Healthcare Hamilton, since some breast cancer patients receive care from both hospital systems.