AI Talk: AI and future of health care, part 2

January 28, 2022 / By V. “Juggy” Jagannathan, PhD

In the part one of this blog series on artificial intelligence (AI) and the future of health care, we explored trends impacting the interoperability of health systems and drug costs. In the second part, we will explore trends impacting the hospital industry.

Part II. AI and future of health care: Acute care trends

In trends impacting acute care, the overarching trendline over the past two decades and more is a steady attrition of revenues from hospital inpatient settings to ambulatory outpatient settings.

Hospital at home (HAH). One of the strong trends in curbing hospitalization costs is the current phenomena of providing hospital care at home. In an interview with HIMSS Dr. John Halamka, Mayo Clinic, said, “The fact of the matter is that hospital at home is cheaper. And it gives better outcomes.” The Centers for Medicare & Medicaid (CMS) has approved (as of December 2021) 190 hospitals in 34 states to allow hospital care at home. It was zero before November 2020.

The reason for this big surge in adoption is not only the pandemic, but one influential study that clearly showed the benefits of at home care for a class of patients. Roughly 30 percent of the patient population being treated in a hospital can now be effectively taken care of in their home setting with proper remote monitoring equipment and tele-visits. A certain class of surgical patients also fall in this category. This process might also allow ambulatory surgery centers (ASCs) to offer more services with post-operative care being provided at home.

Just recently, Mayo, Kaiser, Baxter International and Cardinal Health have invested north of $100 million in a company called Medically Home that is targeting medical treatment at home. AI plays a central role in managing care delivered in a home setting.

Advances in medical devices. This CBSInsights report from last year lists literally hundreds of companies bringing new innovative solutions to the medical device market. Leading the charge are imaging companies bringing computer-aided diagnostics to practice. The FDA has approved such devices and continues to approve and regulate the AI embedded in these devices.

The CBSInsights article lists other categories of devices: AI-enabled devices range from robotic and image guided surgery, point-of-care testing, smartphone-based diagnostics, noninvasive glucose detection, 3D and bio printed devices. There are also a new range of devices targeting treatment: bioelectric neuromodulation and virtual reality (VR) therapeutics.

Accountable care organizations (ACO). The other major trend impacting acute care is tied to the evolution towards value-based care. Listen to this podcast interview with Rick Pollack, president and CEO of the American Hospital Association. Hospitals and acute care settings are simply part of the overall system of providing care. The incentives provided by Medicare through ACO and shared savings program are inexorably moving payment systems away from fee-for-service to value-based models.

Medicare Advantage (MA) plans, which are private plans funded by CMS for the senior population, utilize value-based care. These plans persistently attempt to manage its patient population – primarily to avoid hospitalization and high cost care. The following statement by Rushika Ferandopulle, chief innovation officer of a primary care organization Iora, part of a MA plan, is quite telling: “In general, the only way to really add value in the big picture is to actually make people healthier.”

In order to ensure that the care provided is appropriate and necessary, CMS mandates a whole range of quality measures which look at both process aspects (such as whether specific preventive screening happened or not) as well as outcome measures (how the patient actually fared). AI comes into play for both managing the health of the population, as well as tracking the measures applicable to a patient population. Medicare’s move to curb costs while providing quality care also permeates to general commercial insurers and their efforts to curb costs.

For once the insurers interests and patients’ interests are aligned: make the population healthy! Hospitals caught in the crosshairs of this maelstrom are seriously rethinking their collaboration strategies with other health players. AI is core to delivering value-based care and AI-based solutions are essential for payers and providers.

Process automation. I would like to highlight a few facets here. Revenue cycle management is critical for efficient operation of a hospital. Technologies infused with AI are now routinely deployed to improve this process. Another process I would like to highlight is one related to manual entry into the electronic medical record (EHR) that has contributed to widespread burnout among clinicians. Many AI-based solutions help automate the creation and management of clinical documentation using voice-based assistants. There is also a significant push to use AI in image diagnosis, robot-assisted surgeries, etc.

Another type of process inefficiency that exists in acute care facilities is one related to managing supply chains. The AI that is used to manage supply chains is also referred to as robotic process automation. There is a heightened sense of urgency for such automation given the acute shortage of many items during the pandemic.

The entire health care ecosystem is transforming before our eyes, driven by exigencies of the pandemic and relentless advances in AI technology – and this is particularly true of how we deal with hospitalization and acute care.

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V. “Juggy” Jagannathan, PhD, is Director of Research for 3M M*Modal and is an AI Evangelist with four decades of experience in AI and Computer Science research.