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ObjectiveThis analysis describes the use patterns of web-based virtual triage (VT) by pregnant patients before and during the first two years of the COVID-19 pandemic, and how the pandemic influenced frequency of VT use, nature of symptoms reported, and the associated implications for maternal healthcare delivery.MethodsAn online survey of 36,910 patients who reported pregnancy was completed between January 1, 2019 and June 30, 2022. The data were segmented into six month periods to allow comparative analyses of usage frequency and changes in initial complaints over the study period, with particular emphasis on the early months of the COVID-19 pandemic. Descriptive statistics and trend analyses were used to identify significant shifts in symptom reporting and user demographics.ResultsA marked increase in the utilization of VT by pregnant women during the pandemic occurred. The percentage of pregnant users grew from 0.32% in the first half of 2019 to 0.85% in late 2021, with the greatest rise (213%) in the first six months of 2020. The most common symptoms reported were abdominal pain, headache, nausea, back pain, fatigue and cough. Pre-pandemic, VT use focused on prospective mothers learning about the potential causes of typical symptoms occurring during pregnancy, but during the pandemic there was a substantial increase in reporting symptoms associated with acute respiratory infections such as cough, nasal congestion, and dyspnea.ConclusionsThe COVID-19 pandemic significantly influenced the use of VT by pregnant women, with a shift towards addressing concerns related to respiratory symptoms and potential COVID-19 exposure. These findings underline the significant role of digital health tools in maintaining access to health information during times of crisis and highlight the evolving needs of pregnant patients in such settings.

ObjectiveTo evaluate the extent to which patient-users reporting symptoms of five severe/acute conditions requiring emergency care to an AI-based virtual triage (VT) engine had no intention to get such care, and whose acuity perception was misaligned or decoupled from actual risk of life-threatening symptoms.MethodsA dataset of 3,022,882 VT interviews conducted over 16 months was evaluated to quantify and describe patient-users reporting symptoms of five potentially life-threatening conditions whose pre-triage healthcare intention was other than seeking urgent care, including myocardial infarction, stroke, asthma exacerbation, pneumonia, and pulmonary embolism.ResultsHealthcare intent data was obtained for 12,101 VT patient-user interviews. Across all five conditions a weighted mean of 38.5% of individuals whose VT indicated a condition requiring emergency care had no pre-triage intent to consult a physician. Furthermore, 61.5% intending to possibly consult a physician had no intent to seek emergency medical care. After adjustment for 13% VT safety over-triage/referral to ED, a weighted mean of 33.5% of patient-users had no intent to seek professional care, and 53.5% had no intent to seek emergency care.ConclusionAI-based VT may offer a vehicle for early detection and care acuity alignment of severe evolving pathology by engaging patients who believe their symptoms are not serious, and for accelerating care referral and delivery for life-threatening conditions where patient misunderstanding of risk, or indecision, causes care delay. A next step will be clinical confirmation that when decoupling of patient care intent from emergent care need occurs, VT can influence patient behavior to accelerate care engagement and/or emergency care dispatch and treatment to improve clinical outcomes.

ObjectiveTo describe the use patterns, impact and derived patient-user value of a mobile web-based virtual triage/symptom checker.MethodsOnline survey of 2,113 web-based patient-users of a virtual triage/symptom checker was completed over an 8-week period. Questions focused on triage and care objectives, pre- and post-triage care intent, frequency of use, value derived and satisfaction with virtual triage. Responses were analyzed and stratified to characterize patient-user pre-triage and post-triage intent relative to triage engine output.ResultsSeventy-eight percent of virtual triage users were female, and 37% were 18–24 years old or younger, 28% were 25–44, 16% were 45–54, and 19% were 55 years or older; 41.2% completed the survey from the U.S., 12.5% from the U.K., 9.1% from Canada, 5.6% from India, 3.8% from South Africa. Motivations were to determine need to consult a physician (44.2%), to secure medical advice without visiting a physician (21.0%), and to confirm a diagnosis received (14.2%). Forty-three percent were first time users of virtual triage, 36.6% utilized a triage engine at least once every few months or more often. Pre-triage, 40.5% did not know what level of healthcare they were planning to utilize, 33.9% stated they intended to seek a physician consultation, 23.7% engage self-care and 1.8% seek emergency care. Virtual triage recommended 56.8% of patient-users consult a physician, 33.8% seek emergency care and 9.4% engage self-care. In three-fourths, virtual triage helped users decide level of care to pursue. Among 74.1%, triage recommended care different than pre-triage intentions. Post-triage, those who remained uncertain of their care path decreased by 25.4%. Patient-user experience and satisfaction with virtual triage was high, with 80.1% stating that they were highly likely or likely to use it again, and interest in and willingness to use telemedicine doubled.ConclusionVirtual triage successfully redirected patient-users who initially planned to seek an inappropriate level of care acuity, reduced patient uncertainty of care path, and doubled the percentage of patients amenable to telemedicine and virtual health engagement. Patient-users were highly satisfied with virtual triage and the virtual triage patient experience, and a large majority will use virtual triage recurrently in the future.