The world is in the midst of a technological revolution in artificial intelligence — and the United States is leading the way. However, AI adoption is lagging in some areas, in part due to perceived risks. This lag has the potential to hinder the benefits of the technology.
As other industries confront what some see as a ‘wild west’ in terms of AI adoption, the healthcare industry is already using it, with guardrails in place to protect the patients and healthcare workers who are its customers. To maintain this momentum and not stymie it, policies must be in place that spur continued adoption of this technology. For healthcare, this means we need a consistent reimbursement policy and a collaborative regulatory approach by policymakers to maximize the technology’s benefits.
AI in healthcare has tremendous potential to improve equitable access to care, diagnose disease faster and more precisely, and enable physicians to make treatment decisions based on comprehensive access to patient data in real time. To understand this potential, consider the rapid progress made with tangible benefits of AI-enabled health care tools for patients in terms of quality of care, time to diagnosis, and outcomes.
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The healthcare industry offers a blueprint for how to handle AI responsibly, with innovative applications that ensure the best outcome for users. For example, an AI algorithm built into the computed tomography scanner helps healthcare workers position patients for a CT scan during lung cancer screening, optimizing the resulting images while minimizing the patient’s time in the scanner. Radiologists reviewing these CT images can utilize AI-guided computer software as a clinical companion to identify small nodules and other abnormalities, measuring the density and characterizing the size of suspicious nodules that were previously not visible without AI’s assistance.
To fully harness the benefits of health AI, we must ensure widespread adoption of these technologies. They need to be accessible to more healthcare providers for use when treating patients, especially those in underserved and rural areas that often lack the resources to invest in new technologies.
A consistent, predictable reimbursement policy could change the paradigm for these patients, rather than adding additional, duplicative, and burdensome regulations for AI’s use in health care.
And while the Centers for Medicare & Medicaid Services (CMS) recognizes the value of AI-enabled tools, the agency’s Medicare payment decisions do not uniformly and consistently ensure appropriate levels of payment for these highly regulated, Food and Drug Administration-cleared services.
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Patient expectations continue to evolve, and healthcare practices that fail to adapt risk more than just revenue—they risk losing trust.
We need a reimbursement solution that recognizes the costs of developing and integrating AI into the clinical setting. That solution should include reimbursement for the distinct service these clinical AI solutions provide with a temporary and separate payment based on manufacturer-supplied cost data. This payment, which would exist for a five-year period, would encourage AI adoption while helping CMS collect more data to evaluate the overall value of algorithm-based health services.
Additional data will demonstrate the ability of these tools to increase access to care and improve outcomes for all patients. Further, consistent reimbursement ensures continued investment in AI health care advancements.
While many AI applications exist in healthcare, algorithm-based health services that provide quantitative and qualitative clinical information that the clinician would not otherwise have for diagnosis or treatment will revolutionize patient care. Payment should not be a barrier to the adoption of these services. By increasing access to healthcare AI through pathways like reimbursement, the U.S. can maintain its leadership position in AI and avoid stifling future innovation while substantially improving care, making that care more equitable and promoting the overall health of our entire population.
Source: champpixs, Getty Images
Peter Shen is the Head of Digital & Automation – North America for Siemens Healthineers. In his successful 25-year career in healthcare digitalization, he has held several executive management positions in sales, marketing and innovation, specifically focused on the introduction of new and emerging technologies to the healthcare market, including solutions in Imaging IT, 3D Advanced Visualization, Data Analytics, Digital Ecosystems and Artificial Intelligence. Peter is an industry leader in Healthcare Imaging IT, engaging with major health providers and leading technology partners and routinely speaking at healthcare conferences and events. Recently Peter testified before the US House Energy & Commerce Subcommittee on Health’s hearing on “Understanding How AI is Changing Healthcare” and before the US Senate Finance Committee’s hearing on “Artificial Intelligence and Health Care: Promise and Pitfalls”. A graduate of Johns Hopkins University with degrees in Biomedical Engineering and Mathematical Sciences, Peter currently resides in Silicon Valley.
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