MAXQ INSIGHTS

The Future of Radiology

Are you feeling pressure to do more with less? This is especially true for radiologists, who are under pressure to make quick and accurate decisions while treating a large number of patients, reach faster, more accurate decisions when diagnosing stroke, head trauma, and other life-threatening conditions. For rural and community hospitals, which may have limited radiology support – even less on nights and weekends –the problem is compounded. In larger facilities, CT head cases can stack up, and there is no way of knowing what is urgent such as an intracranial hemorrhage (ICH). Now, when minutes matter, there is vast potential for AI-powered technologies to relieve this pressure by augmenting radiologists with the right solutions in the right way.

MaxQ AI's Video Education Series

Today, the unfortunate reality is the sheer volume of head trauma and stroke cases annually admitted to an ED, whether at a small or large facility, is only growing in volume. The American Heart Association and American Stroke Association project that by 2030, there will be 3.4 million stroke victims per year and, with even with best efforts, experience serious misdiagnosis rates for ICH*. Johns Hopkins investigators have estimated that medical errors are the #3 cause of death in the U.S. with 250,000 such deaths per year*. To compound this issue further, the Association of American Medical Colleges recently predicted the nationwide shortage of providers will reach up to 121,000 physicians by 2035*. The economic impact?  With the cost of stroke care estimated as $150,000 per year per patient, projections of $240 billion in total direct and indirect costs are anticipated*. However, the economic cost of treating a misdiagnosed patient is nothing compared to the devastation to the families.

 

Radiologists are “the doctor’s doctor”, by making the call that leads to final outcomes-based decisions in the care-pathway, AI solutions will augment – not replace – the radiologist in both large and small healthcare facilities. For example, a large facility can receive the benefit of automatic prioritization and triage of suspected ICH patients. For a smaller facility, there is a benefit of near real-time projected expertise; helping care providers make the call to keep the patient locally or to discharge.

 

An early adopter of ACCIPIO ICH and Stroke Care Platform, Dr. Ajay Choudhri of Capital Health in New Jersey states in this week’s video education series that the rapid adoption of these augmented tools in the radiology space is inevitable and will help fill these gaps.

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To learn more about MaxQ AI and the industry-leading, trusted OEM CT, PACS software, Radiology Reporting, and AI Platform companies deploying our solution, or to request a demo, visit us at maxq.ai. Follow us via LinkedIn.

*References upon request, 4, 14, 47, 66

*MaxQ AI Device Regulatory Status