Marilyn Hravnak1, Lujie Chen2, Artur Dubrawski2, Eliezer Bose3, Michael R Pinsky4. 1. School of Nursing, University of Pittsburgh, 336 Victoria Hall, 3500 Victoria Street, Pittsburgh, PA 15261-6314, United States. Electronic address: mhra@pitt.edu. 2. Auton Lab, The Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213-3890, United States. 3. School of Nursing, University of Pittsburgh, 336 Victoria Hall, 3500 Victoria Street, Pittsburgh, PA 15261-6314, United States. 4. School of Medicine, University of Pittsburgh, 606 Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15261-1616, United States.
Abstract
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 1/20Hz) 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 24h following admission were excluded from the models. CONCLUSION: Although instability alerts are distributed most frequently within 24h 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.
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 1/20Hz) in 634 SDUpatients (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 24h following admission were excluded from the models. CONCLUSION: Although instability alerts are distributed most frequently within 24h 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.
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