Response by Richard Boyd, CEO and Co-founder, Tanjo.
One question healthcare technology professionals should be asking right now: How can I use AI and machine learning to create better communicate with patients to create better health outcomes?
Whether it’s a biological virus or a mind virus — the thing that makes it a pandemic or an insurrection crisis situation — is human behavior. The rapidly evolving nature of a crisis, and complex black swan events that are likely to come in the future, requires more than judgment calls by leaders with incomplete information.
We can absolutely train a synthetic model of a human being to predict how that person would behave in a given situation.
With the dramatic rise of telehealth as a result of COVID-19, AI is being used to create a data-driven patient-centered platform that benefits patients and caregivers in their quest for better health. 3DBioMe is a machine-learning and AI data analysis system that brings this interactive 3-D model of the major physiological systems of the body to the fight against COVID and other health issues.
Using AI a healthcare architect can quickly and dramatically explain the environmental and social choice determinants of all health interventions and outcomes showing the effect of those choices over time to a patient in a meaningful and persuasive way.
By John Danaher, MD, president, global clinical solutions, Elsevier.
At the beginning of last year, we all had our own thoughts on how the year would unfold. However, a few months into 2020, we realized that the year would be quite different than we previously imagined because of the COVID-19 pandemic. With 2021 underway, we will continue to witness the digital transformation of the healthcare industry that was accelerated by the COVID-19 pandemic.
Clinicians were quick to embrace different types of innovative technology, such as telemedicine platforms and non-contact solutions to track patient vitals, that allowed them to provide patient care remotely. I believe that in 2021, we will continue to see an evolution of technology to assist clinicians and widespread adoption of digital health services. I also expect the industry will take key learnings with them as we move towards the future, such as the importance of building more trust in science and data.
Investments in AI are paying off
We have seen the impact of AI in the fight against COVID-19, specifically in the diagnosis and tracking of cases, predicting future outbreaks and assisting in selecting treatment plans.
I hope to see more infections decline as populations receive access to the COVID-19 vaccines and I see a renewed focus in how AI can help healthcare systems recover from the pandemic. Artificial Intelligence will be paramount in aiding many healthcare systems’ return to their regular operations as they were pre-pandemic. Artificial intelligence helps systems work faster to address the backlog of patient cases across other diseases and conditions that were postponed due to the pandemic, and deal with the financial strains caused by the virus. These tools can be used in revenue cycle management to assist with staffing, bed and device management, and provide a better understanding of patient utilization.
Artificial intelligence will continue to play a larger role as telemedicine tools and solutions rise in popularity.
Widespread use of telemedicine
One of the longest lasting effects of this pandemic is how clinicians have adjusted their delivery of care. The use of telemedicine applications is now a widely used practice, with the U.S. seeing an increase of 154% in telehealth visits in March 2020, compared to the same time period in 2019. There’s no doubt that the rise in the usage of telehealth services have benefited both healthcare providers and patients.
Mainly, the adoption of services has decreased the number of patients in medical offices seeking non-emergency care and ultimately minimizing the risk of exposure to COVID-19. While telemedicine will not replace in-person care, it will remain a necessity in 2021 and beyond. As patients are now more accustomed to the convenient delivery of care services, they will be more inclined to expect these remote services, along with other services, such as drive through testing sites and at-home delivery of prescription medications that do not require in-person visits.
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.