Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 21, 2021
Date Accepted: Jun 24, 2021
Date Submitted to PubMed: Sep 24, 2021
Utility of a Telephone Triage Hotline in Response to the COVID-19 Pandemic
ABSTRACT
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:
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 3,929 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 highest from 6a.m.-11a.m. and during evening hours. Callers were most often directed to the online patient portal (42%), nursing hotlines (34%), or employee health services (18%). Cough (34% of callers), shortness of breath (27%), upper respiratory infection (25%), and fever (24%) were the most commonly reported symptoms. Immunocompromised state (6%) and age >65 years (5%) were the most commonly reported risk factors.
Conclusions:
The triage algorithm successfully diverted low-risk patients to suitable algorithm endpoints, which helped conserve scarce medical resources during the pandemic and directed 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.
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