The health care industry has, just as every other industry has, been turned upside down by the COVID-19 crisis. There is, of course, the serious health impact on professionals and patients alike. That impact can’t be understated.
On a long-term level organizational level, there’s also the effect on health systems’ technological growth, which will affect their ability to treat patients down the line.
Many organizations have been understandably scaling back investments and other growth projects as we travel through a downturn. We and other experts, however, believe that innovation is a constant practice, and using this downtime to regroup and strategize is a good measure of an innovative organization.
One specific piece of tech innovative health systems are investing in is artificial intelligence (AI), which has frequently shown up on lists detailing the most promising, innovative pieces of tech in health care (including ours). It’s adaptable in a number of care settings, from assisting patients via virtual nurses to more quickly and specifically diagnosing diseases.
Whether your health systems has implemented any AI-powered tools, is in the process of implementing them, or has yet to do so, you should take note of some of the ways others are leveraging AI today and tomorrow.
Current AI use cases
The cornerstone of all current AI use case is assistance—that is, assisting health care professionals with both complex and simple tasks and decisions.
AI and machine learning are helping care professionals more specifically diagnose confounding illnesses, such as through training algorithms to revise and update patient surveys based on provided answers. Data analysts can team up with physicians to share tailored patient surveys and use algorithms to compare them between patients.
Once we get a database ready, we work with epidemiologists to, based on common patient variables, assess which management strategies do and don’t work, to prescribe therapies.
“How Artificial Intelligence can help fight COVID-19,” BBVA
Another way to put this use case is customization. Consultations, therapies, and medications may be more finely customized to patients and their specific circumstances. Personal health is always multi-factored, and AI is helping systems better address that concept.
Which leads us to the most relevant use case of AI today: Battling COVID-19.
One of the biggest questions physicians and other health professionals have regarding coronavirus is who is at risk for 1) infection, and 2) serious health consequences as a result of infection.
Anasse Bari and Megan Coffee, two New York University researchers specializing in the relationship between predictive analytics and infectious diseases, developed an experimental AI-powered tool after realizing January’s outbreak in China was likely going to make its way to the United States.
The pair collected data from 53 previous coronavirus cases and fed it to the group of algorithms they developed, influencing their tool to determine which mildly ill patients were likely to become severely ill.
Our experimental tool helped predict which people were going to get the most sick. In doing so, it also found some unexpected early clinical signs that predict severe cases of COVID-19.
The algorithms we designed were trained on a small dataset and at this point are only a proof-of-concept tool, but with more data we believe later versions could be extremely helpful to medical professionals.
“We designed an experimental AI tool to predict which COVID-19 patients are going to get the sickest,” Anasse Bari and Megan Coffee, The Conversation
Since Bari and Coffee’s study was released, teams of other medical researchers have jumped in to corroborate their own findings. These first iterations will prove influential down the line.
Utilizing AI—or any piece of innovative tech, for that matter—sets a precedent for other players to follow, ensuring you’re doing all you can for your patients.
AI uses post-COVID-19
There are at least three main orientations for how AI will be used in the health care sector:
• Patient oriented
• Clinician oriented
• Administration and operational oriented
All three categories help with the overall goal of improving patient journeys—from interception to long-term relationships.
While each AI technology can contribute significant value alone, the larger potential lies in the synergies generated by using them together across the entire patient journey, from diagnoses, to treatment, to ongoing health maintenance.
“The future of artificial intelligence in health care,” Modern Healthcare
In short, AI-powered tools will be more visible to the patient and widespread across systems. Health care organizations that want to stay not just ahead of the curve but with the times will need to invest more in their innovation programs.
How is your health system using technology to fight current and future health crises? How are you collecting innovative insights in and outside your org?