AI-Driven Data Abstraction for Efficient Gastrointestinal Surgical Research
The Challenge
This project leverages advanced AI to tackle one of the most time-consuming and costly bottlenecks in clinical research: the manual extraction and transcription of patient data collected for research in general and gastrointestinal (GI) surgery. Currently, Clinical Research Assistants (CRAs) spend countless hours reviewing the complex medical documentation from these surgeries, such as operative notes and discharge summaries, and re-entering the information into electronic case report forms. This process is repetitive, error-prone, and can contribute to staff burnout. This pilot will explore whether the new AI-powered system can support CRAs to abstract research-ready data directly from general and GI surgery health records, aiming to make the process faster and more accurate. In the long run, accelerating research could enable the earlier integration of new medical technology and practice innovations into surgical care delivery, benefiting patients and the healthcare system alike.
“By using AI to automate one of the most time-consuming parts of clinical research, we’re improving data quality, saving money, and supporting staff to focus on more meaningful work. Over time, this will help bring new treatments to patients faster.”
– Ted Scott, Chief Innovation Officer, Hamilton Health Sciences
Investment
$
0.9
M
Scale AI investment
$
1
M
Total investment
Partners
