Supports facility expansions
Ten years ago, Midstate Radiology Associates, in Connecticut, was a single hospital with two outpatient imaging centers. Today, it has four hospitals, 18 outpatient sites, and three vein centers, staffed by more than 50 radiologists and 11 advanced practice providers.

In 2020, it adopted ProFound AI Detection and PowerLook Density Assessment to better manage the surge in patients it was seeing. In addition to helping staff handle this larger patient throughput, especially for delayed care during the pandemic, the solutions standardized breast density assessments and increased ancillary services.
“With PowerLook Density Assessment, our density assessments have become more standardized and uniform, which has more than doubled our utilization of screening breast ultrasound and ultimately helps us identify which women would benefit from supplemental screening," said Tom Cappas, chief operating officer at Midstate Radiology Associates.

According to the authors of the GAO report, demonstrating the value of AI like this requires policymakers to create incentives, guidance, or policies that encourage the formation of studies to identify biases, limitations, and ways for improving this technology and to inform providers to increase trust. They also say expanding access to high-quality data is also essential for training and testing machine learning applications across diverse conditions and patient populations.

These needs can be facilitated through greater collaborations among providers, regulators, and technology developers, and the passing of supportive legislative actions by policymakers, including Congress, federal agencies, state and local governments, academic and research institutions, and industry.

This is already being seen. Earlier this year, policymakers in the EU agreed to aggregate cancer imaging data into a cross-border, interoperable infrastructure, allowing clinicians and researchers to validate AI solutions for diagnosing and treating cancer and improving personalized care.

And numerous companies and academic researchers are forming partnerships to accelerate the adoption of AI technologies, including Nuance and Nvidia; and iCAD and Google Health.

Additionally, companies are now sharing more real-world results from their clinical trials, providing health systems and hospitals a more realistic view of whether a solution is the best for their practice, and how it can enhance their operations and care protocols to make it a valuable asset to patients and communities.

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