Background: Risk assessment of patients with acute COVID-19 in a telemedicine context is not well described. In settings of large numbers of patients, a risk assessment tool may guide resource allocation not only for patient care but also for maximum health care and public health benefit. Objective: The goal of this study was to determine whether a COVID-19 telemedicine risk assessment tool accurately predicts hospitalizations. Methods: We conducted a retrospective study of a COVID-19 telemedicine home monitoring program serving health care workers and the community in Atlanta, Georgia, with enrollment from March 24 to May 26, 2020; the final call range was from March 27 to June 19, 2020. All patients were assessed by medical providers using an institutional COVID-19 risk assessment tool designating patients as Tier 1 (low risk for hospitalization), Tier 2 (intermediate risk for hospitalization), or Tier 3 (high risk for hospitalization). Patients were followed with regular telephone calls to an endpoint of improvement or hospitalization. Using survival analysis by Cox regression with days to hospitalization as the metric, we analyzed the performance of the risk tiers and explored individual patient factors associated with risk of hospitalization. Results: Providers using the risk assessment rubric assigned 496 outpatients to tiers: Tier 1, 237 out of 496 (47.8%); Tier 2, 185 out of 496 (37.3%); and Tier 3, 74 out of 496 (14.9%). Subsequent hospitalizations numbered 3 out of 237 (1.3%) for Tier 1, 15 out of 185 (8.1%) for Tier 2, and 17 out of 74 (23%) for Tier 3. From a Cox regression model with age of 60 years or older, gender, and reported obesity as covariates, the adjusted hazard ratios for hospitalization using Tier 1 as reference were 3.74 (95% CI 1.06-13.27; P=.04) for Tier 2 and 10.87 (95% CI 3.09-38.27; P<.001) for Tier 3. Conclusions: A telemedicine risk assessment tool prospectively applied to an outpatient population with COVID-19 identified populations with low, intermediate, and high risk of hospitalization.

Objective Describe the disease course in a cohort of outpatients with COVID-19 and evaluate factors predicting duration of symptoms. Design Retrospective cohort study. Setting Telemedicine clinic at a large medical system in Atlanta, Georgia. Participants 337 patients with acute COVID-19. Exclusion criteria included intake visit more than 10 days after symptom onset and hospitalisation prior to intake visit. Main outcome measures Symptom duration in days. Results Common symptoms at intake visit are upper respiratory (73% cough, 55% loss of smell or taste, 57% sinus congestion, 32% sore throat) and systemic (66% headache, 64% body aches, 53% chills, 30% dizziness, 36% fever). Day of symptom onset was earliest for systemic and upper respiratory symptoms (median onset day 1 for both), followed by lower respiratory symptoms (day 3, 95% CI 2 to 4), with later onset of gastrointestinal symptoms (day 4, 95% CI 3 to 5), when present. Cough had the longest duration when present with median 17 days (95% CI 15 to 21), with 42% not resolved at final visit. Loss of smell or taste had the second longest duration with 14 days (95% CI 12 to 17), with 38% not resolved at final visit. Initial symptom severity is a significant predictor of symptom duration (p<0.01 for multiple symptoms). Conclusions COVID-19 illness in outpatients follows a pattern of progression from systemic symptoms to lower respiratory symptoms and persistent symptoms are common across categories. Initial symptom severity is a significant predictor of disease duration for most considered symptoms.