Outcomes of Vital Sign Monitoring of an Acute Surgical Cohort With Wearable Sensors and Digital Alerting Systems: A Pragmatically Designed Cohort Study and Propensity-Matched Analysis

Fahad Mujtaba Iqbal, Meera Joshi, Rosanna Fox, Tonia Koutsoukou, Arti Sharma, Mike Wright, Sadia Khan, Hutan Ashrafian, Ara Darzi, Fahad Mujtaba Iqbal, Meera Joshi, Rosanna Fox, Tonia Koutsoukou, Arti Sharma, Mike Wright, Sadia Khan, Hutan Ashrafian, Ara Darzi

Abstract

Background: The implementation and efficacy of wearable sensors and alerting systems in acute secondary care have been poorly described. Objectives: to pragmatically test one such system and its influence on clinical outcomes in an acute surgical cohort. Methods: In this pragmatically designed, pre-post implementation trial, participants admitted to the acute surgical unit at our institution were recruited. In the pre-implementation phase (September 2017 to May 2019), the SensiumVitals™ monitoring system, which continuously measures temperature, heart, and respiratory rates, was used for monitoring alongside usual care (intermittent monitoring in accordance with the National Early Warning Score 2 [NEWS 2] protocol) without alerts being generated. In the post-implementation phase (May 2019 to March 2020), alerts were generated when pre-established thresholds for vital parameters were breached, requiring acknowledgement from healthcare staff on provided mobile devices. Hospital length of stay, intensive care use, and 28-days mortality were measured. Balanced cohorts were created with 1:1 'optimal' propensity score logistic regression models. Results: The 1:1 matching method matched the post-implementation group (n = 141) with the same number of subjects from the pre-implementation group (n = 141). The median age of the entire cohort was 52 (range: 18-95) years and the median duration of wearing the sensor was 1.3 (interquartile range: 0.7-2.0) days. The median alert acknowledgement time was 111 (range: 1-2,146) minutes. There were no significant differences in critical care admission (planned or unplanned), hospital length of stay, or mortality. Conclusion: This study offered insight into the implementation of digital health technologies within our institution. Further work is required for optimisation of digital workflows, particularly given their more favourable acceptability in the post pandemic era. Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04638738.

Keywords: ambulatory; clinical trial; monitoring; patient deterioration; patient deterioration detection; remote sensing technology.

Conflict of interest statement

AD is Chair of the Health Security initiative and HA is the Chief Scientific Officer at Flagship Pioneering UK Ltd. Flagship Pioneering had no role in the development, conduct or analysis of the current study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Iqbal, Joshi, Fox, Koutsoukou, Sharma, Wright, Khan, Ashrafian and Darzi.

Figures

FIGURE 1
FIGURE 1
Participant flow diagram.
FIGURE 2
FIGURE 2
Love plot depicting covariate balance with standardized mean differences following propensity score matching.
FIGURE 3
FIGURE 3
Time series displaying the alert acknowledgement time by healthcare staff.

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