A Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study.

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dc.contributor.authorLee, Jang Ho
dc.contributor.authorPark, Yu Rang
dc.contributor.authorKweon, Solbi
dc.contributor.authorKim, Seulgi
dc.contributor.authorJi, Wonjun
dc.contributor.authorChoi, Chang-Min
dc.date.accessioned2020-06-08T14:28:28Z
dc.date.available2020-06-08T14:28:28Z
dc.date.issued0000-00-00
dc.description.abstractBACKGROUND During intrahospital transport adverse events are inevitable Real time monitoring can be helpful for preventing these events during intrahospital transport OBJECTIVE We attempted to determine the viability of risk signal detection using wearable devices and mobile apps during intrahospital transport An alarm was sent to clinicians in the event of oxygen saturation below 90 heart rate above 140 or below 60 beats per minute bpm and network errors We validated the reliability of the risk signal transmitted over the network METHODS We used two wearable devices to monitor oxygen saturation and heart rate for 23 patients during intrahospital transport for diagnostic workup or rehabilitation To determine the agreement between the devices records collected every 4 seconds were matched and imputation was performed if no records were collected at the same time by both devices We used intraclass correlation coefficients ICC to evaluate the relationships between the two devices RESULTS Data for 21 patients were delivered to the cloud over LTE and data for two patients were delivered over Wi Fi Monitoring devices were used for 20 patients during intrahospital transport for diagnostic work up and for three patients during rehabilitation Three patients using supplemental oxygen before the study were included In our study the ICC for the heart rate between the two devices was 0 940 95 CI 0 939 0 942 and that of oxygen saturation was 0 719 95 CI 0 711 0 727 Systemic error analyzed with Bland Altman analysis was 0 428 for heart rate and 1 404 for oxygen saturation During the study 14 patients had 20 risk signals nine signals for eight patients with less than 90 oxygen saturation four for four patients with a heart rate of 60 bpm or less and seven for five patients due to network error CONCLUSIONS We developed a system that notifies the health care provider of the risk level of a patient during transportation using a wearable device and a mobile app Although there were some problems such as missing values and network errors this paper is meaningful in that the previously mentioned risk detection system was validated with actual patients
dc.identifier.urihttp://dx.doi.org/10.2196/12048
dc.identifier.urihttps://lib.digitalsquare.io/handle/123456789/64286
dc.relation.uriJMIR mHealth and uHealth
dc.titleA Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study.en
dcterms.abstractBACKGROUND During intrahospital transport adverse events are inevitable Real time monitoring can be helpful for preventing these events during intrahospital transport OBJECTIVE We attempted to determine the viability of risk signal detection using wearable devices and mobile apps during intrahospital transport An alarm was sent to clinicians in the event of oxygen saturation below 90 heart rate above 140 or below 60 beats per minute bpm and network errors We validated the reliability of the risk signal transmitted over the network METHODS We used two wearable devices to monitor oxygen saturation and heart rate for 23 patients during intrahospital transport for diagnostic workup or rehabilitation To determine the agreement between the devices records collected every 4 seconds were matched and imputation was performed if no records were collected at the same time by both devices We used intraclass correlation coefficients ICC to evaluate the relationships between the two devices RESULTS Data for 21 patients were delivered to the cloud over LTE and data for two patients were delivered over Wi Fi Monitoring devices were used for 20 patients during intrahospital transport for diagnostic work up and for three patients during rehabilitation Three patients using supplemental oxygen before the study were included In our study the ICC for the heart rate between the two devices was 0 940 95 CI 0 939 0 942 and that of oxygen saturation was 0 719 95 CI 0 711 0 727 Systemic error analyzed with Bland Altman analysis was 0 428 for heart rate and 1 404 for oxygen saturation During the study 14 patients had 20 risk signals nine signals for eight patients with less than 90 oxygen saturation four for four patients with a heart rate of 60 bpm or less and seven for five patients due to network error CONCLUSIONS We developed a system that notifies the health care provider of the risk level of a patient during transportation using a wearable device and a mobile app Although there were some problems such as missing values and network errors this paper is meaningful in that the previously mentioned risk detection system was validated with actual patients
dcterms.contributorLee, Jang Ho
dcterms.contributorPark, Yu Rang
dcterms.contributorKweon, Solbi
dcterms.contributorKim, Seulgi
dcterms.contributorJi, Wonjun
dcterms.contributorChoi, Chang-Min
dcterms.identifierhttp://dx.doi.org/10.2196/12048
dcterms.relationJMIR mHealth and uHealth
dcterms.titleA Cardiopulmonary Monitoring System for Patient Transport Within Hospitals Using Mobile Internet of Things Technology: Observational Validation Study.en
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