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Journal of Clinical Monitoring and Computing

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18.08.2018 | Original Research

Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit

verfasst von: Caroline M. Ruminski, Matthew T. Clark, Douglas E. Lake, Rebecca R. Kitzmiller, Jessica Keim-Malpass, Matthew P. Robertson, Theresa R. Simons, J. Randall Moorman, J. Forrest Calland

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 4/2019

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Abstract

Predictive analytics monitoring, the use of patient data to provide continuous risk estimation of deterioration, is a promising new application of big data analytical techniques to the care of individual patients. We tested the hypothesis that continuous display of novel electronic risk visualization of respiratory and cardiovascular events would impact intensive care unit (ICU) patient outcomes. In an adult tertiary care surgical trauma ICU, we displayed risk estimation visualizations on a large monitor, but in the medical ICU in the same institution we did not. The risk estimates were based solely on analysis of continuous cardiorespiratory monitoring. We examined 4275 individual patient records within a 7 month time period preceding and following data display. We determined cases of septic shock, emergency intubation, hemorrhage, and death to compare rates per patient care pre-and post-implementation. Following implementation, the incidence of septic shock fell by half (p < 0.01 in a multivariate model that included age and APACHE) in the surgical trauma ICU, where the data were continuously on display, but by only 10% (p = NS) in the control Medical ICU. There were no significant changes in the other outcomes. Display of a predictive analytics monitor based on continuous cardiorespiratory monitoring was followed by a reduction in the rate of septic shock, even when controlling for age and APACHE score.

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Titel: Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit
verfasst von: Caroline M. Ruminski
Matthew T. Clark
Douglas E. Lake
Rebecca R. Kitzmiller
Jessica Keim-Malpass
Matthew P. Robertson
Theresa R. Simons
J. Randall Moorman
J. Forrest Calland
Publikationsdatum: 18.08.2018
Verlag: Springer Netherlands
Erschienen in: Journal of Clinical Monitoring and Computing / Ausgabe 4/2019
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI: https://doi.org/10.1007/s10877-018-0194-4

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