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. 2020 Dec;8(4):100493.
doi: 10.1016/j.hjdsi.2020.100493. Epub 2020 Oct 26.

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

Affiliations

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

Lucinda Lai et al. Healthc (Amst). 2020 Dec.

Abstract

The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, 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.

Keywords: Artificial intelligence; COVID-19; Chatbot; Digital health; Pandemic; Triage.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Mass General Brigham pre-hospital COVID-19 triage system which receives inquiries from different populations through a combination of existing and new care settings. A standardized testing and triage algorithm ensures common, evidence-based testing and disposition recommendations across all care settings. The triage algorithm was developed based on resource availability and guidelines from the CDC, Massachusetts Department of Public Health, and MGB's expert input, as well as patient risk factors to determine how patients would be directed to the most appropriate end-disposition point. PHOD = Partners (now MGB) Healthcare on Demand (virtual urgent care).
Fig. 2
Fig. 2
Covid-19 Nurse Hotline calls per day and caller abandonment rate from the period of March 9, 2020 to April 29, 2020.
Fig. 3
Fig. 3
Mass General Brigham robotic automation process chatbot's basic clinical decision algorithm upon which more refined algorithmic inputs could be built each day as testing criteria, resources, and parameters changed.
Fig. 4
Fig. 4
Covid-19 Nurse Hotline call volume and Chatbot Screener Use, March–April 2020. The chatbot screener use peaked with increased visibility and promotion on the MGB Patient Gateway portal around the same time as COVID + case incidences occurred in the Boston area and as seen in the Mass General Brigham system COVID + inpatient volume.
Fig. 5
Fig. 5
Chatbot Screener Completions by Endpoint, March–April 2020. Terms of service declined were high on day one as it was in a Beta-launch test phase on that day. The worried well peaked at the same time as the symptomatic population and the COVID + inpatient volume throughout the MGB (formerly Partners Healthcare System (PHS)), emphasizing the importance of utilizing AI during high volumes of case incidences and peak anxiety among the population needing triage.

References

    1. Iansiti M., Lakhani K.R. Harvard Business Press; 2020. Competing in the Age of AI: Strategy and Leadership when Algorithms and Networks Run the World.
    1. Kucharski A.J., Russell T.W., Diamond C. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis. March 2020 doi: 10.1016/S1473-3099(20)30144-4. S1473309920301444. - DOI - PMC - PubMed
    1. Schwirtz M. Nurses die, doctors fall sick and panic rises on virus front lines. The New York Times. https://www.nytimes.com/2020/03/30/nyregion/ny-coronavirus-doctors-sick..... Published March 30, 2020... Accessed April 16, 2020.
    1. Rose C. Am I part of the cure or Am I part of the disease? Keeping coronavirus out when a doctor comes home. N Engl J Med. March. 2020 doi: 10.1056/NEJMp2004768. - DOI - PubMed
    1. Wu J.T., Leung K., Bushman M. Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nat Med. 2020;26(4):506–510. doi: 10.1038/s41591-020-0822-7. - DOI - PMC - PubMed