Temporal distribution of instability events in continuously monitored step-down unit patients: Implications for Rapid Response Systems

RESUSCITATION

卷:89

Article

Hraynak, Marilyn¹  Chen, Lujie²  Dubrawski, Artur²  Bose, Eliezer¹  Pinskya, Michael R.³ 

[1] Univ Pittsburgh, Sch Nursing, Pittsburgh, PA 15261 USA

[2] Carnegie Mellon Univ, Inst Robot, Auton Lab, Pittsburgh, PA 15213 USA

[3] Univ Pittsburgh, Sch Med, Pittsburgh, PA 15261 USA

关键词: Instability;    Machine learning;    Medical emergency teams;    Noninvasive monitoring;    Physiologic monitoring;    Rapid response systems;   

DOI  :  10.1016/j.resuscitation.2015.01.015

来源: Elsevier

【 摘 要 】

Aim: Medical Emergency Teams (MET) activations are more frequent during daytime and weekdays, but whether due to greater patient instability, proximity from admission time, or caregiver concentration is unclear. We sought to determine if instability events, when they occurred, varied in their temporal distribution. Methods: Monitoring data were recorded (frequency 1/20 Hz) in 634 SDU patients (41,635 monitoring hours). Vital sign excursion beyond our MET trigger thresholds defined alerts. The resultant 1399 alerts from 216 patients were tallied according to clock hour and time elapsed since admission. We fit patient ID (n = 216), clock hour, time since SDU admission, and alert present into a null model and three mixed effect logistic regression models: clock hour, hours elapsed since admission, and both clock hour and time elapsed since admission as fixed effect covariates. We performed likelihood ratio tests on these models to assess if, among all alerts, there were proportionally more alerts for any given clock hour, or proximity to admission time. Results: Only time elapsed since admission (p < 0.001), and not clock hour adjusting for time elapsed since admission (p = 0.885), was significant for temporal disproportion. Results were unchanged if the first 24 h following admission were excluded from the models. Conclusion: Although instability alerts are distributed most frequently within 24 h after SDU admission in unstable patients, they are otherwise not more likely to distribute proportionally more frequently during certain clock hours. If MET utilization peaks do not coincide with admission time peaks, other variables contributing to unrecognized instability should be explored. (C) 2015 Elsevier Ireland Ltd. All rights reserved.

【 授权许可】

Free