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Challenges with the growing healthcare burden of Alzheimer’s disease

Challenges with the growing healthcare burden of Alzheimer’s disease

How can AI help with the diagnosis, treatment, and monitoring of patients at scale?

Two smartphone screens showing MRI scans of the human brain
Picture collage of two doctors discussing patient scans, and a doctor discussing diagnosis with a patient.

Alzheimer’s disease is a growing burden for US healthcare

Alzheimer’s disease is a growing epidemic. In the United States, there are over 6 million people suffering from the disease today. This is projected to increase to nearly 13 million people by 2050.1 As new disease-modifying therapies for Alzheimer’s disease emerge, what was once a terminal diagnosis may soon become a manageable chronic condition. This paradigm shift in the management of Alzheimer’s disease will add new challenges to an already overburdened healthcare system.

Emerging Alzheimer’s therapies are changing clinicians’ approach to diagnosis

Today, many clinicians caring for patients with dementia are non-specialists who do not obtain a definitive diagnosis of Alzheimer’s dementia.2 This is due, in part, to the limited availability and reimbursement for advanced imaging such as an amyloid PET scan.3 In addition, confirmation of Alzheimer’s dementia has been deemphasized by physicians due to the limited treatment options.4 However, new Alzheimer’s therapies will require advanced diagnostic imaging and other laboratory tests to confirm the diagnosis. Analysts believe that the US healthcare system is not well-prepared to meet this increased demand.5

Detecting and monitoring ARIA at scale with new Alzheimer's therapies

New Alzheimer’s therapies are on the way with rigorous monitoring requirements. What will be needed in today’s virtual and hybrid work environment to optimize patient care and adherence? New therapies have the potential to improve cognitive function in patients with Alzheimer’s.6,7 These therapies will require periodic monitoring for amyloid related imaging abnormalities (ARIA) on brain MRI scans. Detecting actionable findings requires time-consuming analysis, and many radiologists have limited experience in assessing ARIA. The anticipated increase in MRI volume will put pressure on an already overburdened system.8,9 Neurologists are closely involved with radiologists in discerning risk, which could also increase overall screening time. Streamlined communication channels between clinicians evaluating imaging and those providing care are critical for safe and effective use of Alzheimer’s therapies.

Viz' AI-powered disease detection and care coordination is already being used by radiologists and neurologists in nearly 1,500 hospitals to deliver health system efficiencies. Viz.ai is the leader in helping to scale detection and monitoring of patients with neurological conditions from large vessel occlusion and cerebral aneurysm to subdural hemorrhage.

Case Study with Viz Aneurysm For example, FDA-cleared Viz Aneurysm software automatically detects suspected aneurysms and triages patients so that they receive proper monitoring and treatment.
 • FDA-cleared, smallest aneurysm detection at 4mm+
 • 85% of aneurysms detected by Viz not followed-up previously
 • 88.2% positive predictive value in recent independent study

Auto-detect suspected cerebral aneurysm and view in real-time

Direct patients to the right specialist for monitoring and treatment

Watch this webinar on how Viz.ai is delivering better outcomes at leading health systems

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