Bin Kaio Jia, De Pretto Lucas Ramos, Sanchez Fábio Beltrame, De Souza E Castro Fabio Pacheco Muniz, Ramos Vinicius Delgado, Battistella Linamara Rizzo
Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
JMIR Form Res. 2023 Sep 12;7:e47388. doi: 10.2196/47388.
Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Proteção de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome.
This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws.
A functional model was built following the Brazilian Lei Geral de Proteção de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home.
In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life.
On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.
自新冠疫情大流行以来，人类社会的数字化转型得到了推动，智能手表等可穿戴设备已经能够以连续且自然的方式测量生命体征；然而，个人数据的安全性和隐私性是卫生专业人员在临床随访中扩大使用这些数据以进行决策的一个挑战。与欧洲《通用数据保护条例》类似，在巴西，《数据保护总法》制定了处理个人数据的规则和指南，包括用于患者护理的数据，如智能手表捕获的数据。因此，在任何远程监测场景中，都需要遵守规则和法规，这使得这个问题成为一个需要克服的挑战。
本研究旨在建立一个数字解决方案模型，用于从可穿戴设备捕获数据，并按照现行法律以安全、敏捷的方式将其提供给临床和研究使用。
根据巴西《数据保护总法》（2018年）构建了一个功能模型，智能手表捕获的数据可以通过物联网进行匿名传输，并在医院内部稍后进行识别。总共选择了80名志愿者进行为期24周的随访临床试验，分为两组，一组先前诊断为新冠，另一组为未先前诊断为新冠的对照组，以测量该平台与设备的同步率以及智能手表在院外条件下的准确性和精确性，以模拟在家中的远程监测。
在为期35周的临床试验中，收集了超过1120万条记录，系统无停机；每分钟连续心跳的66%在24小时内同步（79%在2天内同步，91%在一周内同步）。在一致性界限分析中，氧饱和度、舒张压、收缩压和心率的平均差异分别为-1.280%（标准差5.679%）、-1.399（标准差19.112）毫米汞柱、-1.536（标准差24.244）毫米汞柱和0.566（标准差3.114）次/分钟。此外，在数据分析方面，两个研究组之间没有差异（既未使用智能手表也未使用金标准设备），但值得一提的是，新冠组的所有志愿者均已从感染中康复，并且在日常生活工作中功能良好。
根据所获得的结果，考虑到准确性和精确性的验证条件以及模拟院外使用环境，本研究构建的功能模型能够从智能手表捕获数据，并将其匿名提供给医疗服务机构，在那里可以根据法律进行处理，并用于支持远程监测期间的临床决策。
