Study: Hospitals can safely cut low-value preop tests before routine surgeries

Editor's Note

A new study shows hospitals can meaningfully reduce unnecessary preoperative testing for healthy patients undergoing low-risk surgeries without compromising safety or workflow, JAMA Network October 6 reports. The “Right-Sizing Testing Before Elective Surgery” (RITE-Size) strategy successfully lowered testing rates from 68.0% to 40.3% across three Michigan hospitals, while earning high marks for feasibility and acceptance among clinicians.

Guidelines have long advised against routine lab work or imaging before low-risk procedures such as laparoscopic cholecystectomy, inguinal hernia repair, or breast lumpectomy in healthy adults. Yet such testing remains common, adding costs, delays, and potential harm through unnecessary follow-up. The study’s authors noted the US spends an estimated $18 billion annually on low-value preoperative testing and related care cascades.

The RITE-Size initiative aimed to curb this overuse by implementing a structured, six-step “deimplementation” process that combined education, decision support tools, feedback systems, and policy revisions. Conducted from March through August 2024, the quality improvement effort involved 203 patients across a community hospital, a regional hospital, and an academic affiliate. Each site completed all implementation milestones on time. Stakeholders—including surgeons, anesthesiologists, nurses, and quality leads—rated the program highly appropriate and acceptable, with median scores of 20 out of 20 on both standardized measures.

Key factors for success included cohesive perioperative teams, leadership engagement, and embedding new protocols into anesthesia policy. Hospitals also used benchmarking data to compare their testing rates against other facilities, motivating teams to improve performance. Larger institutions faced more coordination barriers, while smaller hospitals adapted more quickly due to streamlined communication and decision-making.

The results reinforce a structured, data-driven deimplementation model can be applied across diverse health systems. The authors plan to expand RITE-Size through a statewide stepped-wedge cluster randomized trial, with adaptations for different institutional contexts.