By Samuel Nadler, MD, PhD
Critical Care, Pulmonary Medicine, The Polyclinic Madison Center, Seattle; Clinical Instructor, University of Washington, Seattle
Dr. Nadler reports no financial relationships relevant to this field of study.
SYNOPSIS: The addition of an automated real-time clinical deterioration alert system to a rapid response system had marginal effects.
SOURCE: Kollef MH, et al. Mortality and length of stay trends following implementation of a rapid response system and real-time automated clinical deterioration alerts. Am J Med Qual 2015 Nov 13 [Epub ahead of print].
Triage of medical admissions is imprecise, and patients on general medical wards may deteriorate, requiring higher levels of care. Early detection and treatment of these individuals should improve outcomes, but current staffing models preclude clinical staff from continuously monitoring every patient. Development of an automated, real-time system could assist in identifying those high-risk patients. Kollef et al previously published a prospective study over a 6-month period that demonstrated rapid response system (RRS) activations did not reduce ICU transfers, mortality, or the need for long-term placement, but did decrease hospital length of stay (LOS).1
This study retrospectively examined trends in hospital mortality, rates of cardiopulmonary arrests (CPAs), hospital LOS, and RRS activations from 2003-2014, before, during, and after the implementation of automated real-time clinical deterioration alerts (RTCDAs). The RRS was implemented between 2006 and 2008 and RTCDAs started in 2009. The RTCDAs monitored 36 input variables with heaviest weighting of respiratory rates, oxygen (O2) saturation, shock index, systolic and diastolic blood pressure, heart rate, and coagulation modifiers. During this period, researchers monitored 163,311 consecutive patients. Linear regressions identified study year as an independent determinant of hospital mortality (r = - 0.794, P = 0.002), CPAs (r = - 0.792, P = 0.006), and LOS (r = - 0.841, P = 0.001). Accordingly, RRS activations increased (r = 0.997, P < 0.001).
COMMENTARY
At first glance, this study seems to demonstrate improvements in important clinical outcomes with the implementation of an automated alert system. However, closer examination of the data calls this conclusion into question. The linear regression models examined the 11-year study period as a whole. During this period, there does appear to be a reduction in mortality and CPAs with an increase in RRS activations. This effect is most pronounced with the development of the RRS system from 2005-2008. After the automated RTCDAs started in 2009, although the rates of RRS activations increase dramatically (~170 to > 400), if anything, there is a mild increase in hospital mortality. The rates of CPAs increased from 2010-2011 before declining once again 2012-2014. The hospital LOS is lowest in 2009 and increased through 2011 before once again decreasing. If the linear regression were calculated during the period of time when the RTCDA system was active from 2009-2014, it is not clear that there would be a significant positive association.
How does this study alter our knowledge of RRSs and RTCDAs to improve clinical outcomes? It further supports the notion that RRSs improve clinical outcomes. The most recent meta-analysis demonstrated that RRSs reduce hospital mortality and rates of CPAs.2 But the automated system in this study did not seem to improve outcomes beyond that observed with RRSs alone. An additional 200 RRS activations did not seem to affect outcomes. The RRS itself may have functioned well enough that most instances of real clinical deterioration were detected. It leaves open the question whether the automated system alone may have worked as well. Further, the automated system itself may not be sensitive enough to improve clinical outcomes. Bailey et al separately published the operating characteristics a real-time alert system within the same system.3 That study reported good sensitivity for ICU transfers and mortality (89.6% and 89.2%, respectively), but the positive predictive values were poor (15.2% and 10.4%, respectively), as these events were relatively rare. Thus, many alerts occurred when a clinical deterioration may not have happened.
Increasing evidence shows RRSs improve outcomes. The addition of RTCDAs in this study did not seem to add to this pre-existing system. Considering the diversion of time and resources these additional alerts caused, they do not seem to confer an advantage. Only with an improved RTCDA would this system improve clinical outcomes.
REFERENCES
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Kollef MH, et al. A randomized trial of real-time automated clinical deterioration alerts sent to a rapid response team. J Hosp Med 2014;9:424-429.
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Maharaj R, et al. Rapid response systems: A systematic review and meta-analysis. Crit Care 2015:19:254.
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Bailey TC, et al. A trial of a real-time alert for clinical deterioration in patients hospitalized on general medicine wards. J Hosp Med 2013:8;236-242.
