AZmed, one of the leading artificial intelligence (AI) companies in medical imaging, and RADIO-LOG, a premier multi-specialty medical service provider in Bavaria, today detailed the integration of AI into the provider’s daily clinical workflow. To navigate the complexities of modern diagnostic imaging, RADIO-LOG began using AZmed’s AI solutions in 2023 and later expanded their clinical deployment with additional AI capabilities.
Reflecting the acute shortage of skilled specialists currently affecting the German healthcare system, radiology departments are dealing with the complex challenge of managing a surging workload while continuing to provide diagnostic precision. Specifically, there was a need for the imaging team at RADIO-LOG to find an AI solution to help alleviate this clinical challenge during the most critical periods of the week (nights and weekends) when staffing across the region is reduced and the pressure is greatest on the radiologists on-call.
RADIO-LOG first incorporated the CE-marked AZtrauma and later AZchest into its digital ecosystem. The AI capabilities provide an automated second-read of radiographs for detecting bone fractures, dislocations, and joint effusions, and thoracic abnormalities, thereby directly addressing the increased risk of missed diagnoses in complex cases.
"Our organization has made a commitment to providing clinical excellence and patient safety, and we're using AI to accomplish this," said Dr.
Jens-Peter Staub, Senior radiologist at RADIO-LOG. "Before we began using AZmed's solutions within our workflow, we faced the challenge of handling increasing
numbers of examinations with the same high level of diagnostic accuracy. Using AI has transformed the way we care for our patients by allowing for immediate and
objective evaluations of our studies, thereby providing a critical safety net for junior physicians and allowing preliminary diagnoses to occur quickly and accurately, regardless of the time of day and the presence of radiologists."
Immediately, improvements in patient management were observed; with the integration of AI into their PACS, RADIO-LOG streamlined their diagnostic workflow and created an expedited method for accessing diagnostic findings without any additional clicks required during the reporting process. The technology enables clinicians to quickly rule out normal cases and rapidly localize pathology, enabling fast triage for intervention or discharge.
"Over the past several years, our AI algorithms have been clinically tested and validated across diverse datasets and routine care settings. This foundation enables us to provide a high-quality second opinion that helps radiologists achieve consistent diagnostic performance, while reducing the administrative burden placed on them," stated Julien Vidal, AZmed's CEO.
The adoption of these capabilities places AZmed as the preferred partner for healthcare networks in Germany looking to enhance their quality of care through the deployment of clinically validated, reliable AI solutions.
