July 17, 2020 - by Parul Saini, Webmedy team
The COVID-19 pandemic has caused profound shifts within both the healthcare system and the world at large. The continuous and dynamic nature of this public health emergency is showing the value of having ways and solutions that are adaptable rather than fixed. Under the telemedicine and digital health umbrella, artificial intelligence, and machine learning are increasingly used and combined to analyze the data and give actionable insights to improve healthcare. Doctors have moved towards the use of digital devices, but Covid-19 is accelerating that shift.
Generally talking, when we are attempting to make a decision based on a lot of data - for example, if 100,000 participating factors influence an outcome - it can be a daunting task for humans. As the number of factors keeps increasing, it becomes difficult to discover the relationship linking the inputs and the outputs. That is why machine learning and AI are playing a vital role. Though machines are not entirely smart, they help make a balanced decision based on data and assist us in scaling the way we manage data.
The continuous spread of COVID 19 is stretching the healthcare's operational systems and beyond. We have seen deficiencies of everything, from masks and gloves to ventilators, and from emergency room space to ICU beds to the rate and safety of internet connectivity. The situation is terrifying: Our economy and health care systems can manage linear, incremental demand, while the virus spreads at an exponential rate. Our public health system cannot protect with this kind of explosive need without the fast and large-scale selection of digital working models. While we race to deaden the virus's spread, we can optimize our response mechanisms, digitizing as many steps as possible. Conventional processes - those that rely on people to work in the risky path of signal processing - are forced by the rate at which we can prepare, plan, and use human labor. Moreover, traditional processes produce diminishing returns as they scale. On the other hand, digital systems can scale up without such restrictions, at practically unlimited rates. The only technical bottlenecks are computing power and room capacity - and we have an abundance of both.
Organizations are recognizing that rules-based systems are not able to handle the fast and dynamic changes brought about by COVID-19 in the world today. As a result, they are turning to solutions that are more flexible and can be retrained. AI and ML enable systems to relearn the rules rather than rewrite the rules. Monitoring and analyzing data is critical. And with viruses, this monitoring is vital for quicker public health response times. For example, some organizations are examining nation-wide transmission levels and demographic data to decide the rate of transmission for particular areas. Others are looking into the connection between social determinants of health and hospitalizations. There are also claims about how machine learning can be used to diagnose COVID-19 from chest x-rays.
COVID-19 has accelerated the acceptance and scaling of virtual and AI tools. From the AI bots used by Providence and Partners HealthCare to the Smart Field Hospital in Wuhan, speedy digital transformation is being applied to fight the exponentially rising COVID-19 threat. We hope and expect that our experience with COVID-19 will result in drastically improving and maturing the way we deliver health care in the future.