Michigan Medicine, University of Michigan, Ann Arbor, MI, United States.
Department of Internal Medicine, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States.
J Med Internet Res. 2021 Nov 1;23(11):e28105. doi: 10.2196/28105.
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.
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.
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).
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.
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.
在 COVID-19 大流行的最初几个月，美国迅速上升的疾病流行率导致了对针对疾病的患者面对面信息交流的需求。在大流行期间，管理增加的患者数量的一种方法是实施基于电话的分诊系统。在大流行期间，可以创新地使用电话分诊热线来节省医疗资源，并提供有关疾病症状和危险因素特征的有用人群水平数据。
本研究旨在描述和评估美国中西部一家大型学术医疗中心使用的 COVID-19 电话分诊热线。
密歇根大学医学中心设立了一个电话热线，对与 COVID-19 相关的入站患者来电进行分诊。对于 2020 年 3 月 24 日至 2020 年 5 月 5 日期间收到的电话，我们描述了总通话量、来电者报告的数据，包括 COVID-19 危险因素和症状，以及分诊算法终点的来电者分布。我们还描述了被引导至机构患者门户（在线医疗访问问卷）的来电者报告的症状。
在研究期间，呼叫中心共接到 3929 个电话（平均每天 91 个）。2020 年 3 月 24 日，每日总通话量达到峰值 211 个。早上 6 点到 11 点和晚上的电话量最高。来电者最常被引导至在线患者门户（3929 个中的 1654 个，42%）、护理热线（3929 个中的 1338 个，34%）或员工健康服务（3929 个中的 709 个，18%）。咳嗽（370 个中的 126 个，34%）、呼吸急促（370 个中的 101 个，27%）、上呼吸道感染（111 个中的 28 个，25%）和发热（370 个中的 89 个，24%）是最常报告的症状。免疫功能低下（370 个中的 23 个，6%）和年龄 >65 岁（370 个中的 18 个，5%）是最常报告的危险因素。
分诊算法成功地将低风险患者分流至合适的算法终点，同时将高风险患者引导至立即评估。从热线电话收集的数据还增强了对典型社区成员症状和危险因素的了解，表明大流行热线可以帮助对新疾病进行临床特征描述。
