JMIR Publications

ABSTRACT

Background:

Pressure on the United States (US) healthcare systems has been increasing for several decades due to a combination of aging populations, increases in chronic health conditions, and rising healthcare expenditures. While other sectors have been fast to digitize (with attendant gains in productivity), healthcare has lagged behind and still relies on highly trained healthcare professionals to complete basic tasks, such as simple symptom assessment and triage. Digital symptom checkers are artificial intelligence (AI)-supported software tools that use a conversational “chatbot” format to support rapid and consistent triage, and can suggest potential explanations for causes of new symptoms. The COVID-19 pandemic has brought new attention to these tools, with the need to avoid face-to-face contact and preserve urgent care capacity. However, there is a need to understand the user demographics and associated triage recommendations generated by a large, general population.

Objective:

In this study we evaluate the user demographics and levels of triage acuity provided by one digital symptom checker tool deployed in partnership with a large integrated health system in the US.

Methods:

Population-based descriptive study including all online symptom assessments completed on the website and patient portal of the Sutter Health system (24 hospitals in Northern California) from April 24th, 2019 to February 1st, 2020. User demographics were compared to relevant US Census population data.

Results:

A total of 26,646 symptom assessments were completed during the study period. Most assessments (17,816/26,646, 66.9%) were completed by female users. Mean user age was 34.3 years (SD: 14.4 years), compared to a median age of 37.3 years of the general population. A substantial portion (12,357/26,646, 46.4%) was completed outside of typical physician office hours. Most users were advised to seek medical care the same day (7,299/26,646, 27.4%) or within 2-3 days (6,301/26,646, 23.6%). Over one quarter of assessments required a high degree of urgency (7,723/26,646, 29.0%).

Conclusions:

Users of the symptom checker were broadly representative of our patient population, though skewed towards younger and female users. Triage recommendations are comparable to those of nurse-staffed phone triage lines. While the emergence of COVID-19 increases the enthusiasm for remote medical assessment tools, it is important to take an evidence-based approach to their deployment.