Reliability of wireless monitoring using a wearable patch sensor in high-risk surgical patients at a step-down unit in the Netherlands: a clinical validation study

Abstract

Background and objectivesIntermittent vital signs measurements are the current standard on hospital wards, typically recorded once every 8 hours. Early signs of deterioration may therefore be missed. Recent innovations have resulted in ‘wearable’ sensors, which may capture patient deterioration at an earlier stage. The objective of this study was to determine whether a wireless ‘patch’ sensor is able to reliably measure respiratory and heart rate continuously in high-risk surgical patients. The secondary objective was to explore the potential of the wireless sensor to serve as a safety monitor.DesignIn an observational methods comparisons study, patients were measured with both the wireless sensor and bedside routine standard for at least 24 hours.SettingUniversity teaching hospital, single centre.ParticipantsTwenty-five postoperative surgical patients admitted to a step-down unit.Outcome measuresPrimary outcome measures were limits of agreement and bias of heart rate and respiratory rate. Secondary outcome measures were sensor reliability, defined as time until first occurrence of data loss.Results1568 hours of vital signs data were analysed. Bias and 95% limits of agreement for heart rate were −1.1 (−8.8 to 6.5) beats per minute. For respiration rate, bias was −2.3 breaths per minute with wide limits of agreement (−15.8 to 11.2 breaths per minute). Median filtering over a 15 min period improved limits of agreement of both respiration and heart rate. 63% of the measurements were performed without data loss greater than 2 min. Overall data loss was limited (6% of time).ConclusionsThe wireless sensor is capable of accurately measuring heart rate, but accuracy for respiratory rate was outside acceptable limits. Remote monitoring has the potential to contribute to early recognition of physiological decline in high-risk patients. Future studies should focus on the ability to detect patient deterioration on low care environments and at home after discharge.

Insights into postoperative respiration by using continuous wireless monitoring of respiratory rate on the postoperative ward: a cohort study

“…In line with previous data [9] we had more valuable data during the night-time, when patients are less mobile. A recent study exploring a similar patch type showed less accuracy of RespR between a wireless patch and a reference monitor [12]. However, the measurements with the patch showed much less intra-individual variability than measurements with the standard monitor, and thus it is possible that the reduced inaccuracy was due to the variability of RespR measurement by the reference monitor.…”

“…However, it has been shown previously that the SensiumVitals® patch reliably measured RespR when compared to a standard approach (e.g., counting RespR for a random 60 s interval during a 5 min period in a quietly breathing patient who is blinded to measurement period) [32]. In addition, the new wireless systems might be even more accurate than currently used reference methods, making prudent interpretation of received data necessary [12]. Notifications of incorrect measurements may result in false alarms, increasing workload of nurses and finally leading to alarm fatigue [45], with subsequent failure of the whole response system [46].…”

A System for Monitoring Breathing Activity Using an Ultrasonic Radar Detection with Low Power Consumption

“…The range of the BR varies with age, weight, exercise tolerance, and body conditions, but the normal range at rest is between 12-20 breaths/min for adults [1]. During normal breathing, the BR is sometimes called eupnea while breathing abnormality occurs when BR falls outside the normal range and it can be classified into several events; tachypnea (a medical condition that occurs when BR exceeds the normal range), bradypnea (a medical condition occurs when BR is lower than the normal range), and central apnea (a medical condition occurs when there is no breathing for more than 10 s) [51,55].…”

Fitbit data show poor correlation with measures of activity and sleep among hospitalized general medicine patients

“…These devices could provide more frequent monitoring to detect deterioration earlier and avoid failures to rescue. 8 Increased awareness of patients' low activity or poor sleep may prompt interventions to improve these parameters, potentially reduce rehospitalizations and ultimately help reintegrate patients into the community.…”