By Raghid El-Yafouri

The race to valuable and responsible AI in healthcare is on. Interest and curiosity from providers, physicians, and patients are supportive. The perception is not that it will replace or diminish the role of doctors. On the contrary, it will alleviate it. In his book “Deep Medicine”, Dr. Eric Topol, a renowned cardiologist, describes AI as a necessary apprentice to physicians. With AI, duplicative testing and imaging decreases and the accuracy of diagnosis increases.

No two patients are alike. True patient care requires individualized assessment of all patient’s unique symptoms, medical history, environment, habits, cardio functions, blood work, diet, microbiome, and even genome. No human can crunch this interconnected data to arrive at a valuable actionable health insight. The siloed specializations of today’s practices make it near impossible. AI removes these boundaries and makes true integrative medicine a possibility. According to Topol, AI will give physicians time back. It will pull them away from screens and put them back in front of the patient, especially in task and protocol heavy specialties like radiology and pathology. It can also augment physicians where care is scarce like dermatology and mental health.

Although this future is in reach, some consideration regarding approach, alignment, and anticipation are necessary. It is moving fast, but in many directions. Data, regulation, and narrow learning are the backbone. Sharpening how we address them can be the difference between healthy and unhealthy AI.

From data consolidation to federation
AI needs data, and it has to be diverse. As organizations explore integrating data from other parties, they are faced with walls of obstacles. Most data integration efforts between organizations halt because of contract negotiations. This is common across industries, but in healthcare it is magnified. Securing ownership and guaranteeing monetization are at play. Without clear understanding what that can be, most take a step back and now they are without the missing piece for what completes their work. The result is an unscalable solution or a less than intelligent result.

Even when negotiation is bypassed, heterogeneous governance, protocols, and format limitations spring up. There are some standards floating around. All accounts to maintain security and privacy are necessary, but it is more than that. It is rare that two sources have coordinated data structures and methods—within an organization or across organizations.

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