Ann Gastroenterol Surg. 2026 Apr 6. doi: 10.1002/ags3.70220. Online ahead of print.
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.
PMID:42495685 | PMC:PMC13394805 | DOI:10.1002/ags3.70220
