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首页> 外文期刊>JMIR public health and surveillance. >Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis
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Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis

机译：使用远程医疗风险评估工具预测Covid-19与Covid-19的496名门诊病人的风险：回顾性分析

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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 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.
机译：背景技术急性Covid-19在远程医疗背景下的患者的风险评估尚未得到很好的描述。在大量患者的环境中，风险评估工具可能导致资源配置不仅适用于患者护理，而且还可用于最大的医疗保健和公共卫生利益。目的本研究的目标是确定Covid-19远程医疗风险评估工具是否准确预测住院治疗。方法对佐治亚州亚特兰大的亚特兰大的Covid-19远程医疗家庭监测计划进行了回顾性研究，佐治亚州亚特兰大的亚特兰大社区，从3月24日至5月26日到2020年5月26日;最终的呼叫范围是从3月27日至6月19日到19日。所有患者通过医疗提供者使用制度Covid-19风险评估工具评估，指定患者作为第1级（住院风险低），第2层（住院中的中间风险） ，或第3层（住院的高风险）。遵循患者定期电话呼叫改善或住院的终点。使用COX回归使用生存分析与日期为公制，我们分析了风险层的表现，并探索了与住院风险相关的个体患者因素。结果提供风险评估的提供商将496分的门诊分配给层次：第1级，237分中为496（47.8％）;第2级，185分，满分496（37.3％）; 496（14.9％）中的第3层，74分。后续住院337（1.3％）的第1层，15分中的第2层，第2层，17分，17分，17分钟，3.从COX回归模型中为60岁或者年龄较大，性别和报告的肥胖是协变量，使用Tier 1作为参考的调整后的危险比作为参考为3.74（95％CI 1.06-13.27; p = .04），适用于2和10.87（95％CI 3.09-38.27; P结论前瞻性地将远程医疗风险评估工具应用于具有低，中级和高住院风险的Covid-19所识别的人口。

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