Remote Monitoring of Critically-Ill Post-Surgical Patients: Lessons from a Biosensor Implementation Trial

Abstract

Biosensors represent one of the numerous promising technologies envisioned to extend healthcare delivery. In perioperative care, the healthcare delivery system can use biosensors to remotely supervise patients who would otherwise be admitted to a hospital. This novel technology has gained a foothold in healthcare with significant acceleration due to the COVID-19 pandemic. However, few studies have attempted to narrate, or systematically analyze, the process of their implementation. We performed an observational study of biosensor implementation. The data accuracy provided by the commercially available biosensors was compared to those offered by standard clinical monitoring on patients admitted to the intensive care unit/perioperative unit. Surveys were also conducted to examine the acceptance of technology by patients and medical staff. We demonstrated a significant difference in vital signs between sensors and standard monitoring which was very dependent on the measured variables. Sensors seemed to integrate into the workflow relatively quickly, with almost no reported problems. The acceptance of the biosensors was high by patients and slightly less by nurses directly involved in the patients' care. The staff forecast a broad implementation of biosensors in approximately three to five years, yet are eager to learn more about them. Reliability considerations proved particularly troublesome in our implementation trial. Careful evaluation of sensor readiness is most likely necessary prior to system-wide implementation by each hospital to assess for data accuracy and acceptance by the staff.

Keywords: bio-monitoring system; critical care; implementation; integration; technology acceptance; vital sign monitoring; wearable biosensors.

Figure 1

Correlation between data supplanted by multimodal sensor and standard ICU monitoring. Various degrees of data consistency were demonstrated by biosensors ranging from excellent for heart rate measurements (A), to variable for respiratory rate observations (B), to suboptimal SpO₂ recordings (C). In addition to the vital signs measured (i) and the quality of the biosensor measurements (ii), the correlation (iii), and bias (iv) between biosensor and Nihon Kohden recordings were also reported according to vital sign.

Figure 2

Experience of wearing the sensor. Experience of wearing the sensor was consistently rated higher for patient users compared to providers involved in care of patients.

Figure 3

Readiness for implementation of biosensors. Physicians assessed the benefits of sensor deployment highly (A) and predicted faster implementation (B) than nurses. Nurses reported a more slightly unprepared perception of readiness to work with biosensors (C).