Utility of a Telephone Triage Hotline in Response to the COVID-19 Pandemic: Longitudinal Observational Study.

BACKGROUND: During the initial months of the COVID-19 pandemic, rapidly rising disease prevalence in the United States created a demand for patient-facing information exchanges that addressed questions and concerns about the disease. One approach to managing increased patient volumes during a pandemic involves the implementation of telephone-based triage systems. During a pandemic, telephone triage hotlines can be employed in innovative ways to conserve medical resources and offer useful population-level data about disease symptomatology and risk factor profiles. OBJECTIVE: The aim of this study is to describe and evaluate the COVID-19 telephone triage hotline used by a large academic medical center in the midwestern United States. METHODS: Michigan Medicine established a telephone hotline to triage inbound patient calls related to COVID-19. For calls received between March 24, 2020, and May 5, 2020, we described total call volume, data reported by callers including COVID-19 risk factors and symptomatology, and distribution of callers to triage algorithm endpoints. We also described symptomatology reported by callers who were directed to the institutional patient portal (online medical visit questionnaire). RESULTS: A total of 3929 calls (average 91 calls per day) were received by the call center during the study period. The maximum total number of daily calls peaked at 211 on March 24, 2020. Call volumes were the highest from 6 AM to 11 AM and during evening hours. Callers were most often directed to the online patient portal (1654/3929, 42%), nursing hotlines (1338/3929, 34%), or employee health services (709/3929, 18%). Cough (126/370 of callers, 34%), shortness of breath (101/370, 27%), upper respiratory infection (28/111, 25%), and fever (89/370, 24%) were the most commonly reported symptoms. Immunocompromised state (23/370, 6%) and age >65 years (18/370, 5%) were the most commonly reported risk factors. CONCLUSIONS: The triage algorithm successfully diverted low-risk patients to suitable algorithm endpoints, while directing high-risk patients onward for immediate assessment. Data collected from hotline calls also enhanced knowledge of symptoms and risk factors that typified community members, demonstrating that pandemic hotlines can aid in the clinical characterization of novel diseases.

Comparing Clinical Features and Outcomes in Mechanically Ventilated Patients with COVID-19 and Acute Respiratory Distress Syndrome.

Rationale: Patients with severe coronavirus disease (COVID-19) meet clinical criteria for the acute respiratory distress syndrome (ARDS), yet early reports suggested they differ physiologically and clinically from patients with non-COVID-19 ARDS, prompting treatment recommendations that deviate from standard evidence-based practices for ARDS. Objectives: To compare respiratory physiology, clinical outcomes, and extrapulmonary clinical features of severe COVID-19 with non-COVID-19 ARDS. Methods: We performed a retrospective cohort study, comparing 130 consecutive mechanically ventilated patients with severe COVID-19 with 382 consecutive mechanically ventilated patients with non-COVID-19 ARDS. Initial respiratory physiology and 28-day outcomes were compared. Extrapulmonary manifestations (inflammation, extrapulmonary organ injury, and coagulation) were compared in an exploratory analysis. Results: Comparison of patients with COVID-19 and non-COVID-19 ARDS suggested small differences in respiratory compliance, ventilatory efficiency, and oxygenation. The 28-day mortality was 30% in patients with COVID-19 and 38% in patients with non-COVID-19 ARDS. In adjusted analysis, point estimates of differences in time to breathing unassisted at 28 days (adjusted subdistributional hazards ratio, 0.98 [95% confidence interval (CI), 0.77-1.26]) and 28-day mortality (risk ratio, 1.01 [95% CI, 0.72-1.42]) were small for COVID-19 versus non-COVID-19 ARDS, although the confidence intervals for these estimates include moderate differences. Patients with COVID-19 had lower neutrophil counts but did not differ in lymphocyte count or other measures of systemic inflammation. Conclusions: In this single-center cohort, we found no evidence for large differences between COVID-19 and non-COVID-19 ARDS. Many key clinical features of severe COVID-19 were similar to those of non-COVID-19 ARDS, including respiratory physiology and clinical outcomes, although our sample size precludes definitive conclusions. Further studies are needed to define COVID-19-specific pathophysiology before a deviation from evidence-based treatment practices can be recommended.