By Dr. John Showalter, MD, MSIS, Chief Product Officer, Jvion.
COVID-19 catalyzed a rapid shift to telehealth that was years in the making. Reimbursement, once a barrier to adoption, was overcome when CMS announced that Medicare would cover telehealth to allow socially-distant care to continue. As a result, 69% of all patient encounters were done via telehealth in April, with that proportion even higher in areas with severe outbreaks of COVID-19.
Today, April feels like a lifetime ago, and telehealth accounts for only 21% of visits. But the consensus is clear: telehealth is here to stay.
A recent survey found almost 70% of providers were more motivated to continue using telehealth after the pandemic, citing better access to care (68%), more timely care (83%), improved patient health (60%), and improved financial health for their practices (57%). And now that CMS has permanently expanded telehealth coverage, any uncertainty over the long-term financial viability of telehealth can be put to rest.
Of course, not everything can be done via telehealth. Telehealth works great for chronic disease management, behavioral health, hospital/ED follow-ups and preventative care, but there are many procedures that can only be done in person. How then can providers determine which patients should be seen in person and who can be seen via telehealth?
This question is now more urgent than ever, as hospitals nationwide confront a surge in patients admitted with Covid-19. To manage capacity and keep patients safe, providers will want to see patients virtually whenever possible.
Deferred care is another concern for providers. Some 41% of US adults deferred medical care they needed this year to avoid the coronavirus. To prevent these patients from deteriorating and suffering worse health outcomes in the future, it’s critical that providers re-engage with these patients as soon as possible before it’s too late. Telehealth is often the safest way to do so.
Artificial intelligence (AI) is transforming healthcare, especially on its clinical side, where 62% of providers have already adopted an AI strategy. The American Hospital Association recently reported that when successfully implemented, clinical AI can improve patient outcomes and lower costs at each stage of the care cycle, from prevention and detection to diagnosis and treatment. Expect to see continued growth in AI adoption in 2020.
Here are a few of the most exciting AI trends to watch for:
Social Determinants of Health (SDoH) will become a core focus for healthcare AI solutions: AI has significant potential for helping reduce socioeconomic barriers to care. Across 2019, we have seen investment by CMS in the Accountable Health Communities Model, which is the first model to include social determinants of health. This model codifies what we already know — that socioeconomic factors influence an individual’s health and risk. Emerging AI technologies are actively creating value for patients by helping to make sense of large socioeconomic and environmental datasets, driving meaningful investments and action that will help to prevent avoidable utilization and guide effective distribution of community resources.
We will start to move into the “Slope of Enlightenment” within the Hype Cycle: Healthcare AI will move out of the “Trough of Disillusionment” as more evidence of AI’s ability to improve health outcomes emerge. AI-related topics will continue to gain prominence in research and the media. And the results of funded projects and pilots will become available to the broader industry.
The AI discussion will broaden beyond imaging and natural language processing: With the exponential increase in patient data, it’s only logical that it’s time for AI – the best way to synthesize that data – to have its moment. While imaging and natural language processing have dominated the healthcare AI conversation over the past few years, 2020 will mark an expanded understanding of AI solutions to include those focused on clinical decision support. These solutions integrate into existing clinical workflows to help direct resources to modifiable patients at risk of a target adverse event. Expect to see more investment and discussion around these solutions across 2020.