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BackgroundElectronic visits (e-visits) are billable, asynchronous patient-initiated messages that require at least five minutes of medical decision-making by a provider. Unequal use of patient portal tools like e-visits by certain patient populations may worsen health disparities. To date, no study has attempted to qualitatively assess perceptions of e-visits in older adults.ObjectiveIn this qualitative study, we aimed to understand patient perceptions of e-visits, including their perceived utility, barriers to use, and care implications, with a focus on vulnerable patient groups.MethodsWe conducted a qualitative study using in-depth structured individual interviews with patients from diverse backgrounds to assess their knowledge and perceptions surrounding e-visits as compared with unbilled portal messages and other visit types. We used content analysis to analyze interview data.ResultsWe conducted 20 interviews, all in adults older than 65 years. We identified 4 overarching coding categories or themes. First, participants were generally accepting of the concept of e-visits and willing to try them. Second, nearly two-thirds of the participants voiced a preference for synchronous communication. Third, participants had specific concerns about the name "e-visit" and when to choose this type of visit in the patient portal. Fourth, some participants indicated discomfort using or accessing technology for e-visits. Financial barriers to the use of e-visits was not a common theme.ConclusionsOur findings suggest that older adults are generally accepting of the concept of e-visits, but uptake may be limited due to their preference for synchronous communication. We identified several opportunities to improve e-visit implementation.

The screening of healthcare workers for COVID-19 (coronavirus disease 2019) symptoms and exposures prior to every clinical shift is important for preventing nosocomial spread of infection but creates a major logistical challenge. To make the screening process simple and efficient, University of California, San Francisco Health designed and implemented a digital chatbot-based workflow. Within 1 week of forming a team, we conducted a product development sprint and deployed the digital screening process. In the first 2 months of use, over 270 000 digital screens have been conducted. This process has reduced wait times for employees entering our hospitals during shift changes, allowed for physical distancing at hospital entrances, prevented higher-risk individuals from coming to work, and provided our healthcare leaders with robust, real-time data for make staffing decisions.

The screening of healthcare workers for COVID-19 (coronavirus disease 2019) symptoms and exposures prior to every clinical shift is important for preventing nosocomial spread of infection but creates a major logistical challenge. To make the screening process simple and efficient, University of California, San Francisco Health designed and implemented a digital chatbot-based workflow. Within 1 week of forming a team, we conducted a product development sprint and deployed the digital screening process. In the first 2 months of use, over 270 000 digital screens have been conducted. This process has reduced wait times for employees entering our hospitals during shift changes, allowed for physical distancing at hospital entrances, prevented higher-risk individuals from coming to work, and provided our healthcare leaders with robust, real-time data for make staffing decisions.

ObjectiveTo rapidly deploy a digital patient-facing self-triage and self-scheduling tool in a large academic health system to address the COVID-19 pandemic.Materials and methodsWe created a patient portal-based COVID-19 self-triage and self-scheduling tool and made it available to all primary care patients at the University of California, San Francisco Health, a large academic health system. Asymptomatic patients were asked about exposure history and were then provided relevant information. Symptomatic patients were triaged into 1 of 4 categories-emergent, urgent, nonurgent, or self-care-and then connected with the appropriate level of care via direct scheduling or telephone hotline.ResultsThis self-triage and self-scheduling tool was designed and implemented in under 2 weeks. During the first 16 days of use, it was completed 1129 times by 950 unique patients. Of completed sessions, 315 (28%) were by asymptomatic patients, and 814 (72%) were by symptomatic patients. Symptomatic patient triage dispositions were as follows: 193 emergent (24%), 193 urgent (24%), 99 nonurgent (12%), 329 self-care (40%). Sensitivity for detecting emergency-level care was 87.5% (95% CI 61.7-98.5%).DiscussionThis self-triage and self-scheduling tool has been widely used by patients and is being rapidly expanded to other populations and health systems. The tool has recommended emergency-level care with high sensitivity, and decreased triage time for patients with less severe illness. The data suggests it also prevents unnecessary triage messages, phone calls, and in-person visits.ConclusionPatient self-triage tools integrated into electronic health record systems have the potential to greatly improve triage efficiency and prevent unnecessary visits during the COVID-19 pandemic.

Introduction: Telehealth has emerged as an important clinical setting for managing acute respiratory tract infections (ARIs), potentially reducing emergency department and urgent care overcrowding, and reducing nosocomial transmission. Many current algorithms for ARI management incorporate information on patient vital signs. However, the accuracy of vital signs collected by patients using readily available home devices and techniques has not been studied. Methods: A cross-sectional sample of patients seen for urgent conditions at a hospital emergency and urgent care center were given instructions and low-cost, readily available devices to collect their vital signs. A trained research coordinator collected a parallel set of vital signs using standard hospital equipment, serving as the gold standard. We analyzed the performance of patient-collected vital signs compared with vital signs collected by a trained research coordinator. Results: A total of 300 patients completed the study. Patient-collected vital signs were highly specific for traditional levels of abnormalities (HR >100 beats per min, RR >24 breaths per min, temperature >100.4 degrees Fahrenheit, oxygen saturation <94 percent); however, sensitivity was poor for elevated heart rate by pulse estimation (25%) and elevated respiratory rate (60%). Heart rate and oxygen saturation by pulse oximeter and oral temperature had higher sensitivity. Conclusions: Vital signs measured and provided by patients are not uniformly accurate, particularly when using manual techniques rather than automated devices. Telehealth algorithms that rely on these values could provide incorrect triage and management advice. [ABSTRACT FROM AUTHOR]

Introduction: Telehealth has emerged as an important clinical setting for managing acute respiratory tract infections (ARIs), potentially reducing emergency department and urgent care overcrowding, and reducing nosocomial transmission. Many current algorithms for ARI management incorporate information on patient vital signs. However, the accuracy of vital signs collected by patients using readily available home devices and techniques has not been studied. Methods: A cross-sectional sample of patients seen for urgent conditions at a hospital emergency and urgent care center were given instructions and low-cost, readily available devices to collect their vital signs. A trained research coordinator collected a parallel set of vital signs using standard hospital equipment, serving as the gold standard. We analyzed the performance of patient-collected vital signs compared with vital signs collected by a trained research coordinator. Results: A total of 300 patients completed the study. Patient-collected vital signs were highly specific for traditional levels of abnormalities (HR >100 beats per min, RR >24 breaths per min, temperature >100.4 degrees Fahrenheit, oxygen saturation <94 percent); however, sensitivity was poor for elevated heart rate by pulse estimation (25%) and elevated respiratory rate (60%). Heart rate and oxygen saturation by pulse oximeter and oral temperature had higher sensitivity. Conclusions: Vital signs measured and provided by patients are not uniformly accurate, particularly when using manual techniques rather than automated devices. Telehealth algorithms that rely on these values could provide incorrect triage and management advice.