During the recent AHIP Institute and Expo in Austin, Texas, a topic that was repeatedly discussed with both excitement and unease was the way in which precision medicine, technology advancement and artificial intelligence (AI) are poised to cause significant disruptions to the way healthcare services are delivered.
During the opening session, Eric Topol, M.D., a professor of genomics at the Scripps Research Institute and the Founder and director of the Scripps Translational Science Institute (STSI), offered powerful insights into these trends. His remarks focused on two distinct technological advancements, which he believes will improve the delivery of care while dramatically reducing costs. The first is the ability to combine data from smartphone-enabled and wearable devices with a patient’s genomic profile, which will lead to far more personalized, precise care delivery models and improved outcomes. Topol went on to highlight key examples of the shortcomings of current “non-personalized” care, including the fact that a majority of patients taking the top 10 grossing drugs in the U.S. don’t respond effectively to their medications.
To demonstrate the ability of this new generation of devices that enable patients to share more meaningful information with their physicians in real time, Topol shared a full-body “selfie” taken with a smartphone-enabled ultrasound, stating that the smartphone will become “the modern stethoscope.” This “selfie” may be a preview of things to come – Topol envisions a future in which many basic health tests and imaging will be self-administered by patients in their home.
Topol also addressed the role that AI and machine learning will play in performing many of the key diagnostic interpretations currently performed by physicians – at greatly reduced cost and with improved accuracy. He gave examples from the fields of dermatology and radiology, where AI is already exceeding the diagnostic accuracy of human physicians by a substantial margin. Of the cost-containing ability of these new technologies, Topol said, “The economics are stunning. AI-enabled radiology can interpret several million images at the cost of about $1,000 per day.” Leveraging AI in this capacity would also enable physicians to focus on making more complex medical decisions. He predicts the application of AI will drive not only significant cost reduction, but also save lives by reducing the volume of medical errors – the third leading cause of death in the U.S., according to the Centers for Disease Control and Prevention.
Topol emphasized that as these trends converge, employers and health plans will play an important role in creating compelling incentives for both patients and providers to encourage more rapid and widespread adoption. He acknowledged there will be some resistance to change among the physician community, where workflows will be altered or disrupted by these new technologies. Topol ended his presentation on a positive note, saying, “Although challenges to effectively leveraging these technologies may slow down implementation in some areas, the macro-level trend is pointed toward a future that focuses on digitization, democratization and patient-centered deep learning.”
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