Artificial Intelligence... Applied Intelligently. Finally. An Answer to Rising Risk for Payers

Artificial Intelligence... Applied Intelligently. Finally. An Answer to Rising Risk for Payers

Chronic diseases and conditions like a heart condition, stroke, cancer, type 2 diabetes, obesity, and arthritis are among the foremost common, costly, and preventable of all health problems, consistent with the CDC. In fact, about half all adults within the US—117 million people—had one or more chronic health conditions, while one in four adults had two or more such conditions. Further, the CDC notes, seven of the highest 10 causes of death in 2014 were associated with chronic disease. Two of these—heart disease and cancer—together assumed for nearly 46 percent of all US deaths that year.

Health plans, perhaps quite the other stakeholders within the US healthcare system, are acutely conscious of the financial burden of chronic disease. The CDC reports that 86 percent of the nation’s $2.7 trillion annual healthcare expenditures are attributed to people with chronic and psychological state conditions. Consistent with a report from the Partnership for Solutions, a national program whose goal is to enhance care and quality of life for Americans with chronic health conditions, “People with chronic conditions, particularly those with multiple chronic conditions, are the heaviest users of healthcare services. 

In addition to the rising incidence of chronic disease, the amount of health plan members over the age of 65 is growing, statistically placing them at a better risk for chronic illness. because it is usually these aging communities who develop chronic diseases only adds to the financial concern that health plans are shouldering. It is, therefore, more important than ever for health plans to develop a technique for maintaining the health of their members, improving patient outcomes while reducing costs.

Managing Member Health

Traditionally, payers have focused on a couple of key efforts to take care of member health including Utilization Management, Wellness, and care management, and sophisticated case management.

The challenge inherent in these approaches of care management isn't that they're feeble, but that they're not optimized to deal with the complicated clinical needs unique to the individual patient. On one end of the thread, such care management actions specialize in population health, accentuating efforts that are good for a whole population generally, like the previously mentioned annual eye exams for members with diabetes. These population health efforts are in fact necessary and prudent, but they’re not personal.

We can create a “digital replica” of every patient, using the real-time

It’s just one occasion the preventive measures have failed for a few of the members—and healthcare costs for those members are already rising substantially—that health plans typically shift their efforts from the overall population to the precise member, that specializes in the way to control costs for the chronically ill patient who, for instance, has been hospitalized 3 times within the last six months.

Care management naturally moves from the management of the member population as an entire to the management of people who require the foremost care. But what if there was how for health plans to focus their efforts on individual patients from the beginning in order that fewer members ended up needing costly medical and care management services?

AI and Machine Learning for Individual Health

There are two ways during which health plans can begin to concentrate more on the needs of individual members from the beginning to stop the necessity for costlier downstream care: the appliance of guideline-directed medical therapy (GDMT) and therefore the addition of real-world, real-time patient data.

GDMT may be a series of medical protocols that pursue commonly accepted standards of care supported the newest research within the industry—for example, placing certain patients with diabetes and atherosclerotic disorder on intensified antihyperglycemic therapy as an accepted standard of care to scale back the danger of cardiovascular death. Surprisingly, however, many patients don't receive these evidence-based therapies. In fact, one study within the New England Journal of Drugs (NEJM) found that nearly half—46.3 percent—of chronically ill participants “did not receive recommended care.”

Another study published within the March 2017 issue of the Journal of the American Medical Association (JAMA) found that, of nearly 95,000 patients with a known history of fibrillation (AF) who had an acute ischaemic stroke, an astonishing 83 percent “were not receiving therapeutic anticoagulation.” This wasn't a case of patient non-adherence, but rather of physicians either never having prescribed the medication within the first place or not having adjusted the dosage for patients receiving anticoagulants in accordance with lab results. 

The second piece of the puzzle in personalized care management is leveraging the huge amounts of patient data available today. The industry now has the power to tug a huge array of real-time patient data from numerous sources—not just from claims data and electronic health records, but from remote monitoring technology, like vital sign readings for coronary failure patients and blood glucose tests for diabetics. It's connecting this personalized, up-to-date information with the latest advances in GDMT that physicians can intervene before acute healthcare events occur, leading to substantial long-term savings for those covering the value of care.

A Collaborative Effort

We can create a “digital replica” of every patient, using the real-time data discussed above. Through the appliance of AI and machine learning, that data can then be compared against the newest accepted evidence-based guidelines, and a customized, real-time recommendation are often delivered instantaneously to the physician, patient or caregiver, alerting them to the likelihood of acute events and offering actionable interventions to assist prevent those events.

We have already got everything we'd like at our fingertips: enough information and computing power to supply an analytical bridge between medical guidelines and high-risk patients with chronic conditions. The result's prescriptive diagnostic and therapeutic solutions for physicians to include into their treatment plans. The impacts include preempted strokes, heart attacks, blindness, renal disorder, and amputations, and lives saved. By implementing such technology to hospitals and providers, I’m convinced that we as an industry can work together to really change the way healthcare is delivered.

 

Read Also

The Importance of Nutrition in Chronic Non-healing Wounds

The Importance of Nutrition in Chronic Non-healing Wounds

Greg Maeder, Medical Director, Goodness Health Group
Basic Values of Wound Care

Basic Values of Wound Care

Rashmin Adesara, Practice Medical Director, Community Health Network
Can We have Connected Health without Connected Physicians?

Can We have Connected Health without Connected Physicians?

Sarah Kramer, Chief Medical Information Officer, Yuma Regional Medical Center
The evolution of Wearable Tech

The evolution of Wearable Tech

Phillip Snider, Chief Medical Informatics Officer, Guthrie