Context:

Our healthcare client was facing certain issues where recruitment was lagging in a large cardiovascular trial. Traditional outreach was slow and costly.

Resolution:

We provided a data science team to solve this; a smart system was developed that used the model Random Forest Classifier that Identified patients which most likely were to meet inclusion criteria and consent to participate.

Result:

A model shortened recruitment timelines by 30%, it reduced screening costs by focusing on high-probability candidates and improved diversity in the participant pool.