Department of Medicine, Division of Hematology and Oncology, University of Alabama at Birmingham, Birmingham, AL.
Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL.
JCO Clin Cancer Inform. 2023 Jun;7:e2300015. doi: 10.1200/CCI.23.00015.
Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analysis evaluated the association between the severity of patient-reported symptom alerts and time to response by the health care team.
This secondary analysis included women with stage I-IV breast cancer who received care at a large academic medical center in the Southeastern United States (October 2020-September 2022). Symptom surveys with at least one severe symptom alert were categorized as severe. Response time was categorized as optimal if the alert was closed by a health care team member within 48 hours. Odds ratios (ORs), predicted probabilities, and 95% CIs were estimated using a patient-nested logistic regression model.
Of 178 patients with breast cancer included in this analysis, 63% of patients identified as White and 85% of patients had a stage I-III or early-stage cancer. The median age at diagnosis was 55 years (IQR, 42-65). Of 1,087 surveys included, 36% reported at least one severe symptom alert and 77% had an optimal response time by the health care team. When compared with surveys that had no severe symptom alerts, surveys with at least one severe symptom alert had similar odds of having an optimal response time (OR, 0.97; 95% CI, 0.68 to 1.38). The results were similar when stratified by cancer stage.
Response times to symptom alerts were similar for alerts with at least one severe symptom compared with alerts with no severe symptoms. This suggests that alert management is being incorporated into routine workflows and not prioritized based on disease or symptom alert severity.
通过电子患者报告结局进行远程症状监测（RSM），使癌症患者能够在面对面就诊之间报告症状。更好地了解 RSM 实施的关键结果对于提高效率和指导实施工作至关重要。本分析评估了患者报告症状警报严重程度与医疗团队响应时间之间的关联。
本二次分析纳入了在位于美国东南部的一家大型学术医疗中心接受治疗的 I-IV 期乳腺癌女性患者（2020 年 10 月至 2022 年 9 月）。将至少有一个严重症状警报的症状调查归类为严重。如果医疗团队成员在 48 小时内关闭警报，则将响应时间归类为最佳。使用患者嵌套逻辑回归模型估计比值比（OR）、预测概率和 95%CI。
在本分析纳入的 178 例乳腺癌患者中，63%的患者为白人，85%的患者为 I-III 期或早期癌症。诊断时的中位年龄为 55 岁（IQR，42-65）。在纳入的 1087 份调查中，36%报告至少有一个严重症状警报，77%的调查有医疗团队的最佳响应时间。与没有严重症状警报的调查相比，有至少一个严重症状警报的调查具有相似的最佳响应时间的可能性（OR，0.97；95%CI，0.68 至 1.38）。按癌症阶段分层的结果相似。
与没有严重症状警报的警报相比，至少有一个严重症状警报的响应时间相似。这表明警报管理已被纳入常规工作流程，而不是根据疾病或症状警报严重程度进行优先排序。
