Contemporary Regional Disparities in Robotic‐Assisted Rectal Resection in Japan: A Nationwide Population‐Based Study Using the National Database Open Data

ABSTRACT Background Robotic‐assisted rectal resection has expanded in Japan since national health insurance reimbursement began in 2018; however, its population‐level regional distribution remains unclear. We evaluated temporal trends and contemporary regional disparities using the National Database (NDB) Open Data. Methods We analyzed NDB Open Data for fiscal years 2014–2023. All patients undergoing rectal resection, irrespective of disease etiology, were included. Procedures were classified as open, laparoscopic, or robotic‐assisted. We assessed temporal trends and age‐ and sex‐stratified surgical volumes. For 2023, prefecture‐level surgical rates per 100 000 population and robotic proportions were calculated. Standardized claim ratios (SCRs) were computed to adjust for age and sex. Population density was used as a proxy for urbanization. Prefectures were categorized into urban and rural groups using the highest and lowest population‐density quartiles (middle two quartiles excluded), and robotic proportions were compared using the Mann–Whitney U test as an exploratory analysis. Results Robotic‐assisted rectal resections increased markedly after 2018, whereas open surgery declined. Substantial inter‐prefectural variation was observed in surgical volume and robotic utilization, and heterogeneity persisted after age‐ and sex‐standardization using SCRs. Urban prefectures exhibited a higher median robotic proportion than rural prefectures (29.3% vs. 19.0%), although this difference did not reach statistical significance ( p = 0.09). Treating population density as a continuous measure, robotic proportion was positively associated with population density (Spearman ρ = 0.338, p = 0.020). Conclusions Robotic‐assisted rectal resection expanded in Japan after reimbursement, yet marked inter‐prefectural heterogeneity remained, underscoring the need for continued nationwide monitoring of geographic variation in adoption.