Rapid design and implementation of an integrated patient self-triage and self-scheduling tool for COVID-19

Abstract

Objective To 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 Methods We 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. Results This 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%). Discussion This 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. Conclusion Patient 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.

Ideas for how informaticians can get involved with COVID-19 research

“…Furthermore, systems can include an interactive component that can facilitate decision support and selftriage. One such example is a patient portal for self-triage and scheduling that was created at the University of California San Francisco to enable asymptomatic patients to report exposure history and for symptomatic patients to be triaged and paired with appropriate levels of care [17]. The system is already being used extensively and performs with high sensitivity in recommending emergency-level care for symptomatic patients.…”

Clinical deployment and validation of a radiology artificial intelligence system for COVID-19

“…Listing 2 shows the Clara pipeline definition for our model. We use a Docker 6 image tagged "pxs-score-app" for pre-processing the image and for executing inference, and another Docker container tagged "results-communicator-app" for posting inference results to our results database.…”

“…This has created demand for protocols for better resource management and optimization of hospital workflows. Rapidly diagnosing and identifying the severity risk of COVID-19 for each patients is valuable in guiding their care while optimizing hospital resource utilization 6,7 .…”

On the Front (Phone) Lines: Results of a COVID-19 Hotline in Northeast Ohio

“…Over the next five weeks, the RN triage line received more than 12,000 calls resulting in more than 5,000 physician telehealth visits. While other institutions have reported on the establishment of triage system protocols within their electronic health records (EHRs) and have updated patient portals to provide patients with self-triage and self-scheduling abilities [15][16][17], to our knowledge this is the first study to examine use of a COVID-19 hotline that provides patients with direct physician care.…”