Study Shows Hospitals Can Save Millions by Optimizing Surgical Supply Lists

Study Shows Hospitals Can Save Millions by Optimizing Surgical Supply Lists

Researchers at the University of California San Diego School of Medicine, in collaboration with the Data Science Alliance, a nonprofit organization that promotes the importance of a responsible scientific environment, conducted a study that showed hospitals could save millions of dollars and significantly reduce surgical waste by rethinking operating room prep supply lists without compromising patient safety.

The study was published in the online edition of November 26, 2025JAMA Surgeryfound that preference cards—hospital checklists of tools and supplies for surgery—often contain far more items than are actually needed. When these lists are copied and reused over time, unnecessary items accumulate, creating inefficiency and waste, resulting in operating rooms being filled with materials that often go unused.

Optimized surgical preference cards not only reduce waste per surgery, but can also save significant hours in preparation and cleanup between cases. This means we have more time to help more patients through life-changing and life-saving surgeries and procedures.”

Sean Perez, MD, lead author and surgical resident at UC San Diego School of Medicine

Researchers analyzed thousands of practices at UC San Diego Health in urology, surgical oncology and colorectal specialties to find out what materials were actually used. In these areas, reducing unused items represented a significant source of potential savings over a five-month period – up to $3 million in items that were either thrown away or needed to be restocked.

Using advanced statistical models, the team optimized versions of these lists to maintain full operational readiness while significantly reducing waste. For patients, this could mean shorter waiting times and lower healthcare costs.

“We hope this study encourages health systems to take a more data-driven approach to maintaining preference maps,” said Karandeep Singh, MD, senior author of the study and chief health AI officer at UC San Diego Health. “Optimizing these lists means that operations are prepared more efficiently and resources are used more responsibly, without sacrificing safety or quality.”

Traditionally, preference maps are updated manually based on individual experiences. This study presents an evidence-based method that leverages real data and makes updates efficient and consistent.

UC San Diego Health is now implementing these optimized lists in real-time surgical environments and is looking for ways to automate updates so they remain accurate over time. The researchers believe this project demonstrates the practical impact data can have on healthcare by demonstrating how responsible data science can reduce hospital waste, increase operational efficiency and ultimately improve patient care.

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