Initial Experience in Predicting the Risk of Hospitalization of 496 Outpatients with COVID-19 Using a Telemedicine Risk Assessment Tool
Abstract
Title
Initial Experience in Validation of a Telemedicine Risk Assessment Tool for Hospitalization of Patients with COVID-19
Importance
Risk assessment of patients with acute coronavirus disease 2019 (COVID-19) in a telemedicine context is not well described. In the setting of large numbers of patients, a risk assessment tool may guide resource allocation not only for patient care but also for maximum healthcare and public health benefit.
Objective
To determine whether a risk prediction tool developed and implemented in March 2020 (“COVID-19 Telemedicine Risk Tier Assessment”) accurately predicts subsequent hospitalizations.
Design
Retrospective cohort study, enrollment from March 24 to May 26, 2020 with follow-up calls until hospitalization or clinical improvement (final call date range March 27 to June 19, 2020)
Setting
Single center “Virtual Outpatient Management Clinic” (VOMC) assessing and managing outpatients from a large quaternary medical system in Atlanta, Georgia
Participants
496 patients with COVID-19 confirmed by nasopharyngeal sampling in isolation at home at the time of diagnosis. Exclusion criteria included: (1) hospitalization prior to VOMC enrollment, (2) immediate discharge from VOMC with no follow-up calls due to resolution.
Exposure
Acute COVID-19 illness
Main Outcome and Measures
Hospitalization was the outcome. Days to hospitalization was the metric. Survival analysis using Cox regression was used to determine factors associated with hospitalization.
Results
The risk-assessment rubric assigned 496 outpatients to tiers as follows: Tier 1, 237 (47.8%); Tier 2, 185 (37.3%); Tier 3, 74 (14.9%). Subsequent hospitalizations numbered 3 (1%), 15 (7%), and 17 (23%) and for Tiers 1-3, respectively. From a Cox regression model with age ≥ 60, gender, and self-reported obesity as covariates, the adjusted hazard ratios using Tier 1 as reference were: Tier 2 HR=3.74 (95% CI, 1.06-13.27; P=0.041); Tier 3 HR=10.87 (95% CI, 3.09-38.27; P<0.001). Tier was the strongest predictor of time to hospitalization.
Conclusions and Relevance
A telemedicine risk assessment tool prospectively applied to an outpatient population with COVID-19 identified both low-risk (Tier 1) and high-risk (Tier 3) patients with better performance than individual risk factors alone. This approach may be appropriate for optimum allocation of resources.
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