Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic

Abstract

The COVID-19 pandemic has created unprecedented challenges for the U.S. healthcare system due to the mismatch between healthcare system capacity and patient demand. The healthcare industry has been a slow adopter of digital innovation due to the conventional belief that humans need to be at the center of every healthcare delivery task. In the setting of the COVID-19 pandemic, however, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and allow clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare implemented an automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.

What Can COVID-19 Teach Us about Using AI in Pandemics?

“…Less extreme situations in emergency physicians and trauma surgeons result in PTSD [ 73 , 74 ]. Numerous predictive models of COVID-19 prognosis in various individuals based on AI-driven algorithms have been designed and published [ 75 , 76 , 77 , 78 , 79 , 80 ]. Their ability to distinguish between favorable outcomes and demise is significantly accurate.…”

“…Assessment of the likelihood of patient’s survival during initial triage and hospitalization may augment the allocation of healthcare assets on the level of a ward, hospital, or larger geographical area. Triage and outcome prediction are very controversial areas of AI application with the medical community and public unprepared for these applications [ 77 , 93 ]. AI can improve resource allocation and help assess the countries’ preparedness by taking into account the dynamic of the spread and available resources, factors frequently minimized in classic epidemiological models [ 94 ].…”

Machine Learning in Healthcare Communication

“…The nurse and the caller are able to have an informed discussion, and it allows the nurse to operate efficiently and quickly to come to a mutually agreeable plan. The chatbot was made available on the Mass General Brigham website so patients could access it before calling the hotline and decrease the call volume [99]. Healthcare workers' screening for COVID-19 symptoms and exposure before every shift is essential for the spread of infection control.…”

Robotics and AI for Teleoperation, Tele-Assessment, and Tele-Training for Surgery in the Era of COVID-19: Existing Challenges, and Future Vision

“…However, it has been shown that for some specific conditions, diagnosis via telemedicine could be as accurate as an in-person diagnosis when examination through telemedicine is feasible subject to limitations (Asiri et al, 2018). For example, AI can be used for digital triage to direct patients to the most appropriate medical center based on the resources and their condition before they show up in emergency rooms (Lai et al, 2020). As another example, it has been shown that blood draw and injections can be done with portable robots using AI more accurately and faster than a manual procedure (Zemmar et al, 2020).…”