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

Background and objectives Intermittent 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. Design In an observational methods comparisons study, patients were measured with both the wireless sensor and bedside routine standard for at least 24 hours. Setting University teaching hospital, single centre. Participants Twenty-five postoperative surgical patients admitted to a step-down unit. Outcome measures Primary 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. Results 1568 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). Conclusions The 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