|
Digital Symptom Checker Usage and Triage: Population-Based Descriptive Study in a Large North American Integrated Health System.
BACKGROUND: Pressure on the United States (US) healthcare system has been increasing due to a combination of aging populations, rising healthcare expenditures and, most recently, the COVID-19 pandemic. Responses are hindered in part by a reliance on a limited supply of highly trained healthcare professionals, creating a need for scalable technological solutions. Digital symptom checkers are artificial intelligence (AI)-supported software tools that use a conversational "chatbot" format to support rapid diagnosis and consistent triage. 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, evidence-based deployment of these chatbots requires an understanding of 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 symptom checker chatbot 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. The most common initial symptom was 'abdominal pain' (2,060/26,646, 7.7%). 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 chatbot 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.
CLINICALTRIAL:
|
