The Aragonese public health system has performed over 143.000 studies using artificial intelligence to detect bone lesions.

The tool, implemented in all public hospitals in Aragon, contributes to improving diagnostic certainty and clinical decision-making.

The Aragonese public healthcare system continues to advance in the incorporation of artificial intelligence tools to support clinical practice. Between January 1 and May 5, 2026, 143.812 studies were performed using an artificial intelligence solution designed to facilitate the detection of fractures and bone injuries in conventional radiology.

The tool is currently implemented in all public hospitals in Aragon and acts as a support system for healthcare professionals, contributing to improved diagnostic safety and care efficiency, especially in high-demand areas such as Emergency services.

Its main benefits include support for the detection of fractures and bone injuries, increased diagnostic sensitivity, reduced errors, and automatic prioritization of studies with suspected pathology. It also allows for a faster clinical response in high-volume settings and facilitates decision-making by healthcare professionals.

Dr. Fernando López, attending emergency physician of Miguel Servet University Hospital He explains that this technology “provides greater certainty when making clinical decisions” and emphasizes that it is a support tool that complements professional judgment. He points out that it also helps identify injuries that may be difficult to detect in an initial assessment and helps reduce cases of undiagnosed pathology.

Pioneering experience in Teruel

The precedent for this regional deployment is found in the Obispo Polanco University Hospital of Teruel, where a pilot project of artificial intelligence applied to the interpretation of simple osteomuscular radiology was launched in September 2024.

The initiative was developed by the Directorate General for Digital Health and Infrastructure in conjunction with the relevant clinical services. It allowed for the analysis of X-rays, automatically identifying potential pathological areas and prioritizing studies with abnormalities in just a few minutes. The system was integrated into standard workflows and always maintained the physician's final responsibility for the diagnosis.

During its development, the project achieved significant results in terms of efficiency and diagnostic accuracy, with a reduction in test interpretation time of approximately 36% and an improvement of roughly 12% in diagnostic accuracy. Furthermore, it reached a negative predictive value of nearly 99,6% for pathology detection.

The progressive incorporation of these tools is part of the technological modernization strategy of the Aragonese public health system and seeks to further strengthen the quality of care, clinical safety and support for healthcare professionals.

Source: health DepartmentGovernment of Aragon