Data-driven surgical supply lists can reduce hospital cost and waste

Researchers show that using advanced statistical models, streamlined versions of surgical supply lists can reduce hospital waste and improve operational efficiency

2025-11-26

(Press-News.org) Researchers at University of California San Diego School of Medicine, in collaboration with Data Science Alliance, a nonprofit promoting the importance of a responsible science environment, led a study showing that hospitals could save millions of dollars and significantly reduce surgical waste by rethinking supply lists used to prepare operating rooms, without compromising patient safety.

The study, published in the November 26, 2025, online edition of JAMA Surgery, found that preference cards — hospital checklists of tools and supplies for surgeries — often include far more items than are actually needed. Over time, as these lists are copied and reused, unnecessary items accumulate, creating inefficiencies and waste, resulting in operating rooms being stocked with supplies that often go unused.

“In addition to decreasing waste per surgery, optimized surgical preference cards can save significant hours in preparation and cleanup between cases,” said Sean Perez, MD, lead author and surgical resident at UC San Diego School of Medicine. “This means that we have more time to help more patients through life-changing and life-saving operations and procedures.”

Researchers analyzed thousands of surgeries across UC San Diego Health in urology, surgical oncology and colorectal specialties to identify which supplies were truly used. Across these areas, reducing unused items represented a major source of potential savings over five months — up to $3 million in items either being discarded or needing to be restocked.

Using advanced statistical models, the team streamlined versions of these lists that maintained full surgical readiness while sharply reducing waste. For patients, that could mean shorter wait times and lower health care costs.

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

Traditionally, preference cards are updated manually based on individual experience. This study introduces an evidence-based method using real-world data, making updates efficient and consistent.

UC San Diego Health is now implementing these streamlined lists in real-time surgical settings and exploring ways to automate updates so they stay accurate over time. The researchers believe this project demonstrates the practical impact data can have in health care by showing how responsible data science can cut hospital waste, boost operational efficiency and ultimately improve patient care.

Full study: https://doi.org/10.1001/jamasurg.2025.5179

Co-authors include: Adir Mancebo Jr., Patricia Lopez, Leslie Joe, Zhihan Li, Mehri Sadri, Eduardo Spiegel-Pinzon, and Ryan Lopez, Data Science Alliance; Kristin Mekeel, University of Colorado Health; Bryan Clary, Christopher A. Longhurst, and Paul Benavidez, UC San Diego.

Funding support for the study came, in part, from the Joan & Irwin Jacobs Center for Health Innovation at UC San Diego Health.

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