Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study

Abstract

Background

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.

Objective

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.

Methods

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.

Results

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.

Conclusions

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.