Increasing Physician Utilization

A large healthcare client was facing low appointment booking rates despite having available physician capacity. Outreach efforts were broad and untargeted, and their one-size-fits-all email campaigns showed limited impact on actual bookings.

To address this, I led a data-driven initiative to design and optimize targeted email campaigns that could drive higher appointment bookings by matching patients with the right physicians. I began by analyzing a dataset of over 500,000 patients, integrating medical history, demographics, and geographic data to segment the population and identify high-potential audience groups. This segmentation allowed us to prioritize outreach based on both care needs and proximity to available physicians.

With the right audience in focus, I designed a series of A/B testing experiments to evaluate which email formats would best drive engagement and conversions. Initial formats ranged from generic reminders to physician-specific messaging. Through iterative testing, we identified a winning format: an email that highlighted three nearby physicians, each accompanied by a “Book Appointment” button allowing patients to schedule directly with a single click. This combination of choice, personalization, and convenience proved to be the breakthrough.

The results were significant. Appointment bookings increased by 25%, and physician utilization rose in parallel—particularly in previously underbooked regions. The one-click booking functionality streamlined the scheduling process, reducing drop-off and making it easier for patients to act immediately.

Beyond the metrics, the project had a lasting operational impact. It demonstrated how healthcare systems can use data science not just to analyze outcomes, but to actively shape them—by delivering the right message, to the right patient, at the right time. What started as a marketing challenge evolved into a scalable patient engagement framework that aligned clinical resources with patient needs more effectively than ever before.