使用远程医疗风险评估工具预测 496 名 COVID-19 门诊患者住院风险：回顾性分析。
Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis.
机构信息
Division of General Internal Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.
Taylor Engineering, Inc, Atlanta, GA, United States.
出版信息
JMIR Public Health Surveill. 2021 Apr 30;7(4):e25075. doi: 10.2196/25075.
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.
背景
在远程医疗环境下，对急性 COVID-19 患者进行风险评估的描述尚不完善。在大量患者的情况下，风险评估工具不仅可以指导患者护理的资源分配，还可以最大限度地提高医疗保健和公共卫生的效益。
目的
本研究的目的是确定 COVID-19 远程医疗风险评估工具是否能准确预测住院。
方法
我们对佐治亚州亚特兰大市的一项 COVID-19 远程医疗家庭监测计划进行了回顾性研究，该计划面向医护人员和社区开放，入组时间为 2020 年 3 月 24 日至 5 月 26 日；最后一次随访时间范围为 2020 年 3 月 27 日至 6 月 19 日。所有患者均由医疗服务提供者使用机构 COVID-19 风险评估工具进行评估，该工具将患者分为 1 级（住院风险低）、2 级（住院风险中等）或 3 级（住院风险高）。通过定期电话随访，以患者病情改善或住院为终点。使用 Cox 回归的生存分析，以住院天数为指标，分析风险等级的表现，并探讨与住院风险相关的个体患者因素。
结果
使用风险评估量表的提供者将 496 名门诊患者分配到以下级别：1 级 237 人（47.8%）；2 级 185 人（37.3%）；3 级 74 人（14.9%）。随后的住院人数为 1 级 3 人（1.3%），2 级 15 人（8.1%），3 级 17 人（23%）。在包含年龄 60 岁或以上、性别和报告的肥胖作为协变量的 Cox 回归模型中，以 1 级为参照，2 级和 3 级的住院调整后危险比分别为 3.74（95%CI 1.06-13.27；P=.04）和 10.87（95%CI 3.09-38.27；P<.001）。
结论
一项前瞻性应用于 COVID-19 门诊患者的远程医疗风险评估工具确定了低、中、高住院风险人群。
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