Presentation (CTI)

OBJECTIVES: Seasonal variation in urologic procedure utilization can strain procedural capacity and contribute to delays in care, yet little is known about how these patterns differ across U.S. states. Understanding state-level variation in utilization timing may clarify differences in urologic care delivery across the U.S.
METHODS: Using the 2013-2023 Merative™ MarketScan® Commercial Database, monthly utilization rates per enrolled beneficiary were calculated for each U.S. state and Census region for elective (artificial urinary sphincter, inflatable penile prosthesis, slings, sacral neuromodulation), semi-elective (lithotripsy, transurethral resection of the prostate), and non-elective (ureteral stent, diagnostic ureteroscopy) procedures. Linear regression models estimated state- and regional monthly differences in utilization using January as the reference month. Similarity in seasonal patterns were assessed using Pearson’s correlation coefficients comparing state- and regional estimates.
RESULTS: State-regional similarity in seasonal utilization patterns differed across procedure category. For elective procedures, similarity was generally high nationwide, with 40 states demonstrating strong correlation (r ≥ 0.5); District of Columbia showed the weakest correlation with its regional pattern (r = -0.22). Greater divergence was observed for semi-elective procedures, including inverse correlations in Rhode Island (r = -0.44), Idaho (r = -0.20), and Arkansas (r = -0.14). The largest departures occurred for non-elective procedures, where Nebraska demonstrated the strongest negative correlation with its regional seasonal pattern (r = -0.35), followed by Rhode Island (r = -0.20), Oklahoma (r = -0.19), Montana (r = -0.18), and Wisconsin (r = -0.13).
CONCLUSIONS: State-level divergence from regional seasonal utilization patterns highlights meaningful differences in access to urologic care across the U.S. Identifying where procedure timing deviates from broader regional trends can help health systems anticipate capacity needs, allocate resources efficiently, and reduce delays in time-sensitive care. These insights support more informed procedural capacity and care delivery planning, improved continuity of services, and enhanced alignment of treatment pathways.