By Krishna Kurapati, CEO, QliqSOFT.
For the first time in our lives, we have been able to see how artificial intelligence would influence a pandemic from identification and tracking to treatment and vaccination. Two things had to perfectly align to make this happen.
Technology had to advance to a place where it could analyze, predict, and engage with extreme accuracy and a virus had to be dangerous enough to spur massive funding and demand for action. We reached that tipping point in 2020. As the year comes to a close it is time to consider all that AI has done and where it is likely to continue to impact epidemiology and disaster response moving forward.
HealthMap, an AI application run by Boston Children’s Hospital, was launched in 2006 and was one of the first tools used to detect and track the COVID-19 outbreak in China. The algorithm uses online data about infectious disease events from news outlets and social media in more than a dozen languages. It then applied machine learning and natural language processing (NLP) to track outbreaks.
Tracking or predicting where cases might show up is just one step in a long journey to stopping the spread of the virus. An article published in May 2020 by researchers in the U.S. and China would reveal that Artificial Intelligence was accurately diagnosing COVID-19 in 68% of patients who had previously been thought to be negative and had normal results on chest imaging. The AI algorithm used to compare imaging, symptoms, medical history, and exposure was said to have “equal sensitivity as compared to a senior thoracic radiologist.” I have also had the pleasure of reading some yet-to-be-published articles about how AI is helping in the ICU to predictively determine ventilator utilization but it’s not just ventilators.
When it came time to harness AI in the diagnosis of COVID-19, even the CDC jumped on board. In partnership with Microsoft’s Azure platform, they embedded a symptom checker chatbot on their website. Likely out of an abundance of caution, their bot uses what I term “light-AI” to guide patients through a very basic decision tree. Answering simple yes-no questions to determine their likelihood of needing a test.
As long as we continue to prioritize data, AI will have the information needed to analyze and predict, it’s a very logical application of the technology — but what about using it to engage patients and address widespread misinformation and fear?
COVID-19 is guilty of creating a widening gap in patient and provider communication for several reasons. It forced clinical attention away from nearly everything else, it overburdened providers, and it created a physical barrier where people no longer felt safe to visit their doctors- and in many cases were restricted from seeing their own families.
Shortly into the pandemic technology providers like myself realized there were at least two key roles AI could play to help the suddenly overwhelmed healthcare system. The roles of educator and coordinator.
As an educator, AI is being used to disseminate accurate, science-sourced information about the COVID-19 virus. When speaking to physician friends their frustration has been very clear. They have had to spend valuable time combating misinformation. Telling their patients not to drink fish tank additives or that they weren’t immune because they were young. But by leveraging a HIPAA-compliant communication platform capable of sending out conversational AI chatbots, these providers could be freed up to continue clinical care and allow the technology to address the educational needs of their patients.
As a coordinator, AI technology is being used across the country to allow patients to self-schedule virtual visits with their providers or to check-in digitally from their vehicles, decongesting and decentralizing the waiting room.
COVID-19 has been particularly challenging for patients with co-morbidities, including those in long-term care or being monitored for chronic conditions. It’s no wonder then that remote patient monitoring is getting a huge boost as well. Companies like Caresignal have adapted AI in their platform capable of predicting and preventing patient disengagement by up to 50%. The system uses more than 80 different data points in its algorithm to assess risk and trigger targeted follow-ups. Artificial intelligence is being used so successfully in this model not because it’s doing something humans can’t, but because it’s taking what the best care coordinators and navigators are capable of doing and doing it on a massive scale.
AI in telemedicine
You may not see telehealth as an AI technology but it can be. When it’s married to healthcare chatbots that use AI and NLP to triage symptoms before the visit or harness AI digital assistance to complete documentation and follow-ups, AI is very much a part of digital care, or connected care as we like to call it. With major swings in legislation and new inclusions by Medicare and Medicaid, we’re seeing more providers financially able to take part in this type of care.
That wasn’t the case just a year ago. Nor were patients as eager to jump on board. This summer we participated in a study with the Martec Group, “Re-engaging With The Healthcare Ecosystem Post COVID-19”. It was an in-depth study of the behaviors, attitudes, and emotions of US consumers during the pandemic. A few key insights related to patients and AI emerged.
The study found a dramatic 44% increase in patient concerns related to seeing physicians face-to-face, where just a year before it was the overwhelming preference. This increase was seen across all age groups and socioeconomic classes. This was quite telling from a “sensing demand” perspective, but with increased demand and an influx of “new” technology providers trying to meet that demand you’d expect to see a dip in satisfaction, but by contrast, the study found 69% to 80% of patients who newly began engaging with AI technology (healthcare chatbots, digital triage, intelligent reminders) and those receiving virtual care – were highly satisfied.
Convenience and ease of use were the common driving factors. Satisfaction on the provider side has been tied to technologies being able to complete workflows end to end, ideally in a single platform. However, the option to add on services like Suki’s voice-enabled documentation assistant, winner of Google Cloud Technology Partner of the year for AI & ML Award or Binah’s vital sign monitor that turns a selfie into real-time diagnostics, are proving to be valuable add-ons to completing a digital care package.
Again, it’s a once in a lifetime alignment of demand and the tools to meet that demand successfully, and importantly — at scale.
The pandemic has shown us this augmentation or clinical automation is critical for health system viability, particularly in times of national health crisis. But that doesn’t mean the technology is ready to run the show. AI will never fully replace human intelligence, interaction, or interpretation. Providers must remain the trusted source of clinical information for their patients. Can their workflows be augmented? Yes. But the role of human oversight in the design, implementation, and refinement of these systems will never go away.
AI has already been tapped to help healthcare providers distribute and document COVID-19 vaccination, and it’s more than capable of doing so. You’ll see in the coming months that these technologies will be used to address vaccine hesitancy, something the World Health Organization has identified as one of the Top 10 Threats to World Health. Whether it is used to identify and takedown misinformation or to securely spread accurate information and connect patients to resources, AI will continue to be on the frontlines.
COVID-19 was a spark. It has been just severe enough to trigger rapid innovation in these technologies to spread like wildfire, yet not so devastating that all hope was lost. In other words, the pandemic has been a gateway for AI adoption. Because AI could be readily adapted to address these challenges, and governments acknowledged the need with financial support, 2020 will be viewed in hindsight as the year AI completely re-shaped the healthcare landscape.
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