Providers turn to AI for help with chronic care

Every patient is now a “big data” challenge, with vast amounts of information on past trajectories and current states, but new AI can help providers manage that challenge.
Jeff Rowe

It’s no secret that physicians face a number of challenges when it comes to delivering care in today’s rapidly changing healthcare environment. 

In a recent commentary, Lonny Reisman, MD, founder and CEO of HealthReveal, an AI technology firm focused on the chronically ill, ticked off several of those pressures, including the need to transition from fee-for-service to value-based care, coping with health information technology, patient data overload and an explosion of new medical knowledge. 

“A clinician’s ability to access and synthesize enormous volumes of data and then translate that data to actionable, patient-specific interventions consistent with complex, evolving guidelines, tests the limits of even the best and brightest of human minds,” he noted.

But the irony, Reisman continued, quoting a recent article at NEJM, is that “the same computers that today torment us with never-ending checkboxes and forms will tomorrow be able to process and synthesize medical data in ways we could never do ourselves.”

In other words, an increasing number of stakeholders believe, AI and machine learning can help solve the very “information overload” problems that the rise of digital health tools have helped to create.

For Reisman, one example of how AI can work to help physicians manage the therapy programs many chronic illness patients require is via new software that  creates a “digital replica” of each patient, “incorporating data from electronic health records, payers and even patient-generated health data (PGHD) from remote monitoring technology (devices that are wearable or implantable, or can be used in the home), such as blood pressure readings and blood sugar tests. From there, using cloud-based technology, the data collected about specific patients can be compared against the latest evidence-based guidelines. As discrepancies emerge, customized, real-time recommendations can be delivered instantaneously to the clinician, caregiver, or to the patient directly, alerting them to the likelihood of adverse events, and most importantly, offering actionable interventions for care to prevent those events from occurring.”

On a broader level, Reisman notes the potential of AI by pointing to a June 2017 report from McKinsey Global Institute that confirms the impact AI can have on patient care and outcomes, as well as on healthcare costs.

“AI has the potential to help doctors improve their diagnoses, forecast the spread of diseases, and customize treatments,” the report states. “Artificial intelligence combined with health care digitization can … transform the way we treat the chronic diseases that account for a large share of health-care budgets. Indeed … AI tools will enable healthcare to dramatically accelerate its shift toward preventive medicine.”

Or, as Reisman sums it up, “AI in healthcare is no longer a promise for the future – it’s a promise for today.”