Elsevier, part of RELX Group, has entered into an agreement to offer its STATdx online radiology diagnostic decision support tool through M*Modal Fluency for Imaging, an advanced speech recognition and workflow management system, to deliver the next generation of diagnostic decision support.

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Image: Elsevier to offer ts STATdx online radiology diagnostic decision support tool through M*Modal Fluency for Imaging. Photo: courtesy of Marcelo Terraza / FreeImages.

This combined solution will be demonstrated during the Association of Medical Imaging Management (AHRA) 2018 annual meeting in Orlando from July 22-25.

STATdx, written by renowned radiologists in each specialty and widely regarded as the “gold standard” of radiology reference solutions, increases accuracy and confidence in diagnosing complex imaging cases and includes more than 4,000 common and complex diagnoses, 200,000 expert-selected and annotated image examples, 20,000 easily sortable patient cases with cine clips for select topics and much more.

Elsevier’s STATdx received two prestigious awards in 2017. STATdx received Frost & Sullivan’s 2017 North America Technology Innovation Award. STATdx also received top honors in the Digital and Online Resources category at the British Medical Association’s awards.

“The STATdx integration with M*Modal will expedite the diagnostic process by putting together two critical tools in one place, streamlining the workflow,” said Hajo Oltmanns, Senior Vice President and Chief Commercial Officer, Clinical Solutions, Elsevier.

“Radiologists’ reports will not only be more accurate, but this integrated solution will provide completeness, conformity, usability and consistency to drive actions and deliver value to the healthcare provider and, ultimately, the patient.”

Currently, medical knowledge is growing at such a rapid pace that clinicians cannot keep up. Reliable information sources are not easily accessible, and healthcare providers must rely on limited sets of information to determine diagnoses.

Also, the content from clinician notes is not always in the correct context, which can cause confusion and errors in decision-making. This situation can be resolved by deep workflow integration with intelligent search that connects radiologists with content in the appropriate context to make quicker, more confident diagnosis.

Chris Spring, Vice President Imaging Solutions at M*Modal, added, “The goal of this combined solution is to drive significantly better detection, interpretation and classification of disease so that clinicians can make the most appropriate diagnoses.”

Source: Company Press Release