Department of Radiation Oncology, City of Hope Orange County Lennar Foundation Cancer Center, Irvine, CA.
Division of Radiation Oncology, MD Anderson Cancer Center, Houston, TX.
JCO Clin Cancer Inform. 2024 Sep;8:e2400040. doi: 10.1200/CCI.24.00040. Epub 2024 Sep 30.
A major barrier to the incorporation of biometric data into clinical practice is the lack of device integration with electronic medical records (EMRs). We developed infrastructure to transmit biometric data from an Apple Watch into the EMR for physician review. The study objective was to test feasibility of using this infrastructure for patients undergoing radiotherapy.
The study included patients with breast or prostate cancer receiving ≥3 weeks of radiotherapy who reported owning an Apple Watch. Daily resting heart rate (HR), HR variability, step count, and exercise minutes were automatically transferred to our EMR using a custom app installed on each patient's iPhone. Biometric data were presented to the treating radiation oncologist for review on a weekly basis during creation of the on-treatment note. Feasibility was defined a priori as physician review of biometric data for at least 90% of patients. Time trends in biometric data were tested using the Jonckheere-Terpstra test. Patient satisfaction was assessed using the System Usability Scale (SUS), with scores above 80 considered above-average user experience.
Of the 20 patients enrolled, biometric data were successfully transmitted to the EMR and reviewed by the radiation oncologist for 95% (n = 19) of patients, thus meeting the a priori feasibility threshold. For patients with radiation courses ≥4 weeks, exercise minutes decreased over time ( = .01) and daily mean HR variability increased over time ( = .02). The median SUS was 82.5 (IQR, 70-87.5).
Our study demonstrates the feasibility of real-time integration of biometric data collected from an Apple Watch into the EMR with subsequent physician review. The high rates of physician review and patient satisfaction provide support for further development of large-scale collection of wearable device data.
将生物识别数据纳入临床实践的主要障碍是缺乏与电子病历（EMR）的设备集成。我们开发了一种基础设施，可将来自 Apple Watch 的生物识别数据传输到 EMR 以供医生审查。本研究的目的是测试该基础设施在接受放射治疗的患者中使用的可行性。
该研究纳入了接受≥3 周放射治疗的乳腺癌或前列腺癌患者，这些患者报告自己拥有 Apple Watch。每位患者的 iPhone 上安装了一个自定义应用程序，可自动将日常静息心率（HR）、HR 变异性、步数和运动分钟数传输到我们的 EMR 中。在创建治疗期间记录时，每周都会将生物识别数据呈现给主治放射肿瘤学家进行审查。可行性预先定义为医生审查至少 90%的患者的生物识别数据。使用 Jonckheere-Terpstra 检验测试生物识别数据的时间趋势。使用系统可用性量表（SUS）评估患者满意度，得分高于 80 分被认为是高于平均用户体验。
在纳入的 20 名患者中，有 95%（n = 19）的患者成功将生物识别数据传输到 EMR 并由放射肿瘤学家审查，因此达到了预先设定的可行性阈值。对于放射治疗疗程≥4 周的患者，运动分钟数随时间减少（ =.01），每日平均 HR 变异性随时间增加（ =.02）。SUS 的中位数为 82.5（IQR，70-87.5）。
我们的研究表明，将来自 Apple Watch 的生物识别数据实时集成到 EMR 中并随后由医生审查是可行的。高比例的医生审查和患者满意度为进一步开发大规模可穿戴设备数据收集提供了支持。
