ArticleInternational journal of computer assisted radiology and surgery2026
Technology-assisted visceral surgery: a model-based approach for quantifying translation and accessibility across populations and geographies.
Article in International journal of computer assisted radiology and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionTechnological innovation is rapidly transforming surgical care, yet disparities in access and adoption persist. This study introduces a flexible, population-based model designed to assess and potentially guide the equitable implementation of advanced technologies in visceral (gastrointestinal) surgery, ranging from laparoscopy and basic imaging up to robotic-assisted surgery and artificial intelligence. MATERIAL AND
methodsWe conducted a survey among technologically experienced visceral surgeons to classify current and emerging technologies by perceived complexity and requirement. This classification was used to query a self-developed translation model, which was integrated with demographic, hospital, and geographic data from official German sources. The model quantifies technological maturity and accessibility by calculating travel-to-treat times from the population's residence to hospitals offering specific technologies. We applied the model to the entire German population and all 16 counties, enabling regional and national comparisons.
resultsBased on the survey results, we constructed a layered classification for grouping surgical technologies with two dimensions, S and D, for surgical procedures and available devices and increasing levels of complexity (1-3). The model identified substantial regional disparities in access to advanced technology-assisted visceral surgery across Germany. While basic technologies (S1-S2, D1-D2) were broadly accessible nationwide, higher-level technologies such as robotic surgery (S3) were concentrated in urban areas. However, some advanced diagnostics (D3) were also available in remote regions. The model effectively quantified these differences from the population's perspective and demonstrated its potential for objective, population-based assessment of technological translation and accessibility.
conclusionOur model highlights persistent regional disparities in advanced technology adoption and demonstrates potential for guiding equitable implementation strategies. Its population-based, data-driven approach can be extended to other countries, healthcare settings, and technologies, supporting political decision-making and improved patient access.
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