TY - JOUR
T1 - Developing the accuracy of vital sign measurements using the lifelight software application in comparison to standard of care methods
T2 - Observational study protocol
AU - Jones, Thomas L.
AU - Heiden, Emily
AU - Mitchell, Felicity
AU - Fogg, Carole
AU - McCready, Sharon
AU - Pearce, Laurence
AU - Kapoor, Melissa
AU - Bassett, Paul
AU - Chauhan, Anoop J.
N1 - Publisher Copyright:
© Thomas L Jones, Emily Heiden, Felicity Mitchell, Carole Fogg, Sharon McCready, Laurence Pearce, Melissa Kapoor, Paul Bassett, Anoop J Chauhan.
PY - 2021/1/28
Y1 - 2021/1/28
N2 - Background: Vital sign measurements are an integral component of clinical care, but current challenges with the accuracy and timeliness of patient observations can impact appropriate clinical decision making. Advanced technologies using techniques such as photoplethysmography have the potential to automate noncontact physiological monitoring and recording, improving the quality and accessibility of this essential clinical information. Objective: In this study, we aim to develop the algorithm used in the Lifelight software application and improve the accuracy of its estimated heart rate, respiratory rate, oxygen saturation, and blood pressure measurements. Methods: This preliminary study will compare measurements predicted by the Lifelight software with standard of care measurements for an estimated population sample of 2000 inpatients, outpatients, and healthy people attending a large acute hospital. Both training datasets and validation datasets will be analyzed to assess the degree of correspondence between the vital sign measurements predicted by the Lifelight software and the direct physiological measurements taken using standard of care methods. Subgroup analyses will explore how the performance of the algorithm varies with particular patient characteristics, including age, sex, health condition, and medication. Results: Recruitment of participants to this study began in July 2018, and data collection will continue for a planned study period of 12 months. Conclusions: Digital health technology is a rapidly evolving area for health and social care. Following this initial exploratory study to develop and refine the Lifelight software application, subsequent work will evaluate its performance across a range of health characteristics, and extended validation trials will support its pathway to registration as a medical device. Innovations in health technology such as this may provide valuable opportunities for increasing the efficiency and accessibility of vital sign measurements and improve health care services on a large scale across multiple health and care settings.
AB - Background: Vital sign measurements are an integral component of clinical care, but current challenges with the accuracy and timeliness of patient observations can impact appropriate clinical decision making. Advanced technologies using techniques such as photoplethysmography have the potential to automate noncontact physiological monitoring and recording, improving the quality and accessibility of this essential clinical information. Objective: In this study, we aim to develop the algorithm used in the Lifelight software application and improve the accuracy of its estimated heart rate, respiratory rate, oxygen saturation, and blood pressure measurements. Methods: This preliminary study will compare measurements predicted by the Lifelight software with standard of care measurements for an estimated population sample of 2000 inpatients, outpatients, and healthy people attending a large acute hospital. Both training datasets and validation datasets will be analyzed to assess the degree of correspondence between the vital sign measurements predicted by the Lifelight software and the direct physiological measurements taken using standard of care methods. Subgroup analyses will explore how the performance of the algorithm varies with particular patient characteristics, including age, sex, health condition, and medication. Results: Recruitment of participants to this study began in July 2018, and data collection will continue for a planned study period of 12 months. Conclusions: Digital health technology is a rapidly evolving area for health and social care. Following this initial exploratory study to develop and refine the Lifelight software application, subsequent work will evaluate its performance across a range of health characteristics, and extended validation trials will support its pathway to registration as a medical device. Innovations in health technology such as this may provide valuable opportunities for increasing the efficiency and accessibility of vital sign measurements and improve health care services on a large scale across multiple health and care settings.
KW - Health technology
KW - Patient deterioration
KW - Remote monitoring
KW - Vital signs
UR - http://www.scopus.com/inward/record.url?scp=85100456325&partnerID=8YFLogxK
U2 - 10.2196/14326
DO - 10.2196/14326
M3 - Article
AN - SCOPUS:85100456325
SN - 1929-0748
VL - 10
JO - JMIR Research Protocols
JF - JMIR Research Protocols
IS - 1
M1 - e14326
ER -