Skip to main content
Download PDF

Diurnal variation in the performance of rapid response systems: the role of critical care services—a review article

Journal of Intensive Care volume 4, Article number: 15 (2016) Cite this article

Abstract

The type of medical review before an adverse event influences patient outcome. Delays in the up-transfer of patients requiring intensive care are associated with higher mortality rates. Timely detection and response to a deteriorating patient constitute an important function of the rapid response system (RRS). The activation of the RRS for at-risk patients constitutes the system’s afferent limb. Afferent limb failure (ALF), an important performance measure of rapid response systems, constitutes a failure to activate a rapid response team (RRT) despite criteria for calling an RRT.

There are diurnal variations in hospital staffing levels, the performance of rapid response systems and patient outcomes. Fewer ward-based nursing staff at night may contribute to ALF. The diurnal variability in RRS activity is greater in unmonitored units than it is in monitored units for events that should result in a call for an RRT. RRT events include a significant abnormality in either the pulse rate, blood pressure, conscious state or respiratory rate. There is also diurnal variation in RRT summoning rates, with most activations occurring during the day. The reasons for this variation are mostly speculative, but the failure of the afferent limb of RRT activation, particularly at night, may be a factor.

The term “circadian variation/rhythm” applies to physiological variations over a 24-h cycle. In contrast, diurnal variation applies more accurately to extrinsic systems. Circadian rhythm has been demonstrated in a multitude of bodily functions and disease states.

For example, there is an association between disrupted circadian rhythms and abnormal vital parameters such as anomalous blood pressure, irregular pulse rate, aberrant endothelial function, myocardial infarction, stroke, sleep-disordered breathing and its long-term consequences of hypertension, heart failure and cognitive impairment. Therefore, diurnal variation in patient outcomes may be extrinsic, and more easily modifiable, or related to the circadian variation inherent in human physiology. Importantly, diurnal variations in the implementation and performance of the RRS, as gauged by ALF, the RRT response to clinical deterioration and any variations in quality and quantity of patient monitoring have not been fully explored across a diverse group of hospitals.

Introduction

Timely patient assessment and effective triage, both have a major role in influencing the subsequent progress and outcome of acutely ill patients [1, 2]. Timely reviews by senior specialist physicians of new and acute patient admissions can be delayed [3]. There may also be inadequate oversight of a junior medical officer’s assessment and delivery of patient care, with the consequence of inefficiencies, inappropriate resource utilization and potential patient harm [4]. Senior clinicians may also fail to recognize acute deterioration and patterns of acute illness [3]. As a consequence, there can be a delay in formulating an appropriate plan, undertaking a procedure, instituting therapy or in imposing limits of care [5] for a potentially unstable inpatient.

Critical care areas provide critically ill patients with intense observation and treatment that cannot be provided on general wards [6]. These areas include intensive care units (ICUs), high-dependency units (HDUs), emergency departments (EDs) and operating theatres. Close monitoring enables early identification of patients with acute deterioration and the implementation of timely treatment by staff with critical care skills. In contrast, management of similar patients on general wards can be suboptimal and may be associated with higher mortality rates [3, 7].

The rapid response systems (RRSs) are becoming widely adopted. The RRS is the overarching system under which the rapid response team (RRT) operates. These teams evolved upon the basis that adverse events, such as deaths, cardiac arrests (CAs) and unanticipated ICU admissions, are often preceded by documented abnormalities in vital signs [8, 9] and that failure to respond to these signs is associated with increased mortality [10–12]. In the setting of an RRS, patients are identified when they meet one or more predefined criteria such as abnormalities in the heart rate, blood pressure, respiratory rate and neurological status.

The presence of any such criteria, or if a staff member is “worried” about the patient, is expected to trigger a prompt response from an RRT. Rapid response teams are staffed by clinicians with critical care skills who can assess and manage acute patient deterioration. The first described RRT, the medical emergency team (MET), was a critical care physician-led team [13]. Rapid response systems may therefore be physician led (MET) or nurse practitioner led (RRT and outreach teams) depending upon the hospital environment in which they operate. Since the advent of RRSs, cardiac arrests and associated mortality rates have fallen by up to 20–50 % in various institutions [14, 15] as well as across entire health regions [16].

Based on this premise, many safety and quality organizations have adopted the implementation of RRSs. In Australia, the Australian [17] Commission on Safety and Quality in Health Care (ACSQHC) has made the recognition of, and response to, deteriorating patients (standard 9) one of the 10 national standards (Additional file).

The RRSs have two key aspects: the afferent limb, which involves the detection, recognition of and response to acutely deteriorating patients, and the efferent limb, encompassing RRT patient assessment, management and dispatch (Fig. 1).

Fig. 1
figure 1

Diagram depicting the two limbs of the rapid response system

Full size image

Review

Recognising the acute deteriorating patient

Medicine is becoming increasingly super-specialized, in part as a way of retaining expertise in the setting of ever expanding medical knowledge. Super-speciality medicine [18], by its nature, is restricted to a limited number of diagnoses, and has the benefits of better outcomes for those with specific conditions, particularly when super-speciality clinicians deliver care. However, patients and their clinical problems are becoming more diverse and complex [19], and those that die often have several co-morbid conditions.

Thus, patients are becoming less suitable for management by a super-specialized physician. In contrast, for the less complex and less well-differentiated patient, hospitalists (acute hospital medicine) can deliver a more efficient and complete service [20]. This does not mean that acute hospital medicine and super-speciality medicine are mutually exclusive. Some super-specialists are less likely to have the necessary skill set and infrastructure (i.e. monitoring environment) to provide acute medical care 24 h a day, 7 days a week, for patients who are critically unwell and are at risk of suffering an adverse event [20]. The RRSs were introduced to respond to acutely deteriorating patients [21] who in the past were “trapped” within the medical “silos” that have evolved with super-specialization.

Delay in the transfer of patients from the emergency department to intensive care is associated with a higher mortality [22]. Similarly, delays in the transfer of critically ill patients from the wards to the ICU and delays in responding to documented clinical deterioration are also associated with worse outcomes [23]. Patients recently discharged from an ICU are also at risk of a subsequent adverse event [24]. In this context, RRSs especially the critical care outreach teams behave as the “safety net” for the hospital at large.

Acute deterioration may be unexpected or go undetected. For example, the vast majority of in-hospital mortality can be accounted for by a small number of preceding conditions [25]. There are various scoring systems [21, 26] and tools [27–29] that utilize a combination of patient demographics, illness and biochemical measures to ascertain the risk of physiological deterioration or inpatient mortality. The deteriorating patient whose deterioration has not been recognized is at high risk of an adverse event (e.g. a cardiac arrest, unanticipated ICU admission, MET attendance) and associated morbidity.

It is also not uncommon for patients to have an adverse event despite having had a critical care review (e.g. MET or ICU) or despite having been discharged from a critical care area (e.g. ED, ICU or OR) in the preceding 24 h [30]. However, compared to an admitting team-only review, a critical care review is less likely to be associated with a subsequent adverse event [30].

Responding to an acute deteriorating patient

Adverse events are potentially preventable if patients’ vital signs are recorded in a timely fashion, are accurately documented, and there is an established RRS in place to respond to acute patient deterioration. Ward staff must recognize and respond promptly to abnormal patient vital signs, and trigger an RRT as appropriate. However, this process can, and does, fail at multiple levels. Even if abnormal observations are recorded and documented, their significance may not be recognized. Within that segmented structure, admitting teams, which are best at functioning within a narrow speciality paradigm, may fail to quantify accurately the risk of imminent death of their inpatients (Fig. 2).

Fig. 2
figure 2

Flow diagram representing detecting and responding to clinical deterioration and afferent limb failure. (# indicates an admission to ICU which was not planned or elective; usually follows a sudden, unexpected clinical deterioration)

Full size image

Despite coming up with plausible diagnoses and treatment plans, medical teams may not call for help until the patient is moribund. Instead, inexperienced junior doctors are placed in a difficult position while liaising with interdisciplinary colleagues. In the quest for a unifying diagnosis, unnecessary investigations and consultations may distract clinicians from opportune treatment, including resuscitation.

Failure to respond to an acute deteriorating patient: afferent limb failure

Even though the RRT system is well accepted in most hospitals, there are barriers to its full implementation. The hospital’s “cultural” awareness of an RRT and education of its healthcare personnel to demystify the concept of an RRT can positively impact upon the use of an RRT [31]. The expertise of the nursing staff, particularly its seniority and experience, may affect the rates of activation and rates of delayed/denied calling of the RRT [32]. Afferent limb failure (ALF) constitutes a failure to activate an RRT despite criteria for calling an RRT [33], and is an important performance measure of an RRS. Afferent limb failure can be an absolute phenomenon, wherein the RRT system is not activated at all. It could also be a relative concept, where the RRT system is activated, but activation is delayed relative to the actual or observed clinical deterioration (Fig. 3).

Fig. 3
figure 3

Contributors to afferent limb failure. * Davies et al. [76]. ø Tirkkonen et al. [77]. § Bragshaw et al. [78]. ϕ Galhotra et al. [79]. β Jacques et al. [80]. Ω Jones et al. [81]. α Azzopardi et al. [82]. + Radeschi et al. [83]

Full size image

Afferent limb failure could occur at three stages: detection, recording and action. There may be a failure of detection of deranged vital signs [34]. For example, two Australian studies [35, 36] conducted after the implementation of the MET system identified afferent limb failure as a persistent problem.

In particular, the MERIT study [37], a large cluster randomized controlled study, showed that failure to detect a deteriorating patient and call an MET was common, despite documented MET criteria >15 min before the event, and occurred in 30 % of cardiac arrests, 51 % of unplanned ICU admissions and 50 % of unexpected deaths. Alternatively, there may be a failure to record patient vital signs. The respiratory rate is the most poorly recorded vital sign [38] and contributes to a significant proportion of ALF. Documentation of a complete set of vital signs is also often lacking. Only 17 % of surgical inpatients had a complete set of documentation of vital signs and a complete medical and nursing review within the first three post-operative days [39].

In addition to incomplete vital sign documentation, there may be a failure to document ward reviews by medical (14.9 %) and nursing (5.6 %) staff within the first seven post-operative days [40]. The final stage of afferent limb failure occurs at the level of MET criteria [39] where there is a failure to act on criteria and escalate [41] activation of the rapid response teams.

Performance measurement of rapid response systems

Performance measurement of clinical systems is an important aspect of system maintenance, not only to ensure maximal efficiency and efficacy but also to improve patient outcomes [42]. The sustainability of any system whose aims include the prevention of adverse events is in part reliant upon a process of audit and feedback based upon agreed performance indicators [43].

For example, major trauma systems that evaluate the first responders to a critical event have swift feedback mechanisms in place that improve overall effectiveness by identifying areas of concern and then stimulating appropriate change [44].

Preferred measurements for evaluating the performance of RRS are still evolving. Commonly used measures are the rates of cardiac arrests and unanticipated admissions to the ICU from general wards [33]. In this context, ALF is a useful performance measure, as it is linked to a modifiable process.

Dealing with afferent limb failure

Depending upon its cause, remedial measures are paramount in dealing with ALF (Fig. 2). For example, the detection of a deteriorating patient could improve with electronic monitoring of vital signs, particularly overnight [45]. A recent study [46] showed that the afferent limb of the rapid response system can be strengthened by an educational intervention (e-learning) specifically aimed at early detection of changes in vital signs. Having a tailored [46] management plan, not only for monitoring of vital signs but also for clinical handover, will help. This can be achieved, for example, by a structured clinical assessment and intervention focusing on the airway, breathing, circulation, disability and exposure or by reporting clinical deterioration using the ISBAR handover tool [46] (i.e. identity, situation, background, assessment and recommendation).

If staff shortages rather than staff performance are responsible for afferent limb failure, these can be remedied. Even if staff performance is responsible, it is also very important not to be critical of the ward staff who do not activate the MET appropriately or activate the MET inappropriately because this can affect team morale and productivity [47]. Process design rather than personal performance should be considered. A greater emphasis on repeated reviews of vulnerable patients is essential.

Even though it has been shown that ALF is associated with increased mortality [48], it remains to be fully elucidated as to how much of that mortality is due to issues surrounding delayed/absent decision-making in relation to end-of-life care. Sociologically informed models of interprofessional practice when dealing with cognitive and sociocultural aspects of ALF were shown to be helpful in dealing with ALF. The cognitive aspects contributing to ALF relate to perception (recording and measurement of vital signs), comprehension (how the vital signs relate to MET criteria and why) and projection (the clinical response required and the consequences). The sociocultural aspects revolve around the interpersonal and interprofessional aspects of the MET system.

Recently, there have been improved processes of care for recognizing the deteriorating patient with the help of education and widespread use of information tools [49, 50] such as posters, algorithms, electronic alerts. The most recent addition to this armamentarium is colour-coded track and trigger vital sign charts [49] that are based on the principle of patrolling surf lifesavers. It is imperative to evaluate these “between the flag” charts in terms of how they could influence the prevalence of ALF. Digital technology [50] has the potential to maximize the purported benefits from the track and trigger chart. What remains relatively unexplored is the effect of time of day upon the RRS performance and ALF in particular.

Diurnal variation and the deteriorating patient

Circadian variation and diurnal variation

The term “circadian variation” applies to physiological variations over a 24-h cycle. In contrast, diurnal variation as a concept applies more appropriately to extrinsic systems.

Circadian variation as defined by Franz Halberg [51] refers to daily rhythms that are endogenously regulated and repeated over a period of approximately 24 h in the absence of external stimuli. It is well known that the circadian system influences multiple human biochemical and physiological parameters, including sleep-wake cycles, thermoregulation, metabolic, endocrine and immune functions. Circadian rhythm has been demonstrated in an assortment of pathophysiological states. For example, there is an association between disrupted circadian rhythms and abnormal vital parameters (Table 1). There is also emerging evidence on the role of circadian misalignment and adverse consequences in patients admitted to an intensive care unit [52]. The environmental and genetic predisposition to maintenance and restoration of human circadian rhythms is a topic of ongoing research and still remains unexplored.

Table 1 Pathophysiological conditions that demonstrate diurnal variation
Full size table

Diurnal variation, on the other hand, refers to the fluctuations that happen during the day and the variations in the day-night cycle that are not regulated by intrinsic or endogenous mechanisms but rather by extraneous factors. Thus, in the setting of the RRS performance, diurnal, rather than circadian, variation is more likely to be influenced by modifiable hospital processes.

Diurnal variation in recognizing clinical deterioration

Staffing levels and expertise have an inverse relationship with patient outcomes [53]. There is consistent evidence to link diurnal variation with physician staffing and associated patient harm [54]. There is diurnal variation in the patient-physician ratio [55] and patient throughput (i.e. admission and discharge rates) in the ICU, this being maximal during day shifts and lower during night shifts.

In contrast, the ICU nurse-patient ratio may be more consistent throughout the day and night cycles. The mean nurse-patient ratio [55] was similar between day and night shifts with an average of 1.8 patients per nurse. On the contrary, physician-patient ratio [55] varied dramatically between day and night shifts, with a mean of 3.6 patients per physician during the day versus 8.5 patients per physician during the night. The impact of nurse-patient ratio in a general ward on ICU admissions has not been thoroughly evaluated across diverse hospitals and further research is needed.

There is also diurnal variation in patient outcomes. For example, outcomes for cardiac arrests, trauma [56], and elective and emergency surgery are worse at night. The relative role of extrinsic (diurnal) versus intrinsic (circadian) rhythms in these outcomes is unclear. Diurnal variation in shift times and duration also influences staff performance. Staff performance decreases during the night [57]. Also, patients admitted to an ICU during early morning hours tend to be older and sicker than those admitted later in the day [58]. The standard method of reporting RRT utilization rates is the number of RRT calls per 1000 patient admissions or discharges [13]. Afferent limb activation and rates of detection and response to clinical deterioration can, therefore, be expressed using the concept of MET dose [13]. Extending this analogy, we can describe a dose-response relationship, made obvious where there is diurnal variation in the MET dose. If we map cardiac arrest and RRT calls, their call pattern indicates a diurnal variation, whereby as the RRT dose decreases at night, the cardiac arrest rate increases [59]. It is important to ensure that this is not merely a chronological coincidence of a diurnal rhythm with a circadian one.

There is a similar relationship between diurnal variation in the RRT dose and hospital mortality and outcomes at the time of an RRT call. Our experience in a tertiary referral centre mirrors previously published [59] data (Figs. 4 and 5).

Fig. 4
figure 4

Diurnal variation in MET and cardiac arrest occurrence

Full size image
Fig. 5
figure 5

Diurnal variation in MET outcomes (based upon patients who had a MET call during their hospital stay)

Full size image

In patients admitted to the ICU, there is an established link between overnight/weekend admissions and harm [60]. There is also evidence to suggest adverse outcomes among patients discharged after hours [61] from the ICU. A recent study [62] found that timing of discharge from ICU did not have an independent association with mortality, in contrary to previous studies. With regard to the RRS, further research is needed to explore and explain performance outcomes and their associations with diurnal variation.

Diurnal variation in afferent limb failure

It may be that diurnal variation in the intensity with which inpatients are monitored or acute deterioration is responded to (e.g. ALF) may impact upon patient outcomes. There is a preponderance of RRT calls during the day. The reasons for this are mostly speculative, but the failure of the afferent limb of RRT activation, particularly at night, may be a factor. A large-scale retrospective observational study [63] demonstrated that the MET event rate was higher during the day than at night in unmonitored wards (62 % during the day vs. 38 % at night; p < .001) and monitored wards (59 % during the day vs. 41 % at night; p < .001) but not in the ICUs (47 % during the day vs. 53 % at night; p = .20). Unmonitored units had a greater daytime increase in MET event rate than monitored units (63 vs. 46 %), whereas the ICUs showed an 11 % decline in the MET event rate during the day compared with night. The day versus night difference was greater on weekdays (65 % during the day vs. 35 % at night; p < .001) than at weekends (56 % during the day vs. 44 % at night; p < .001) for MET activity in both monitored and unmonitored ward beds in the hospital.

A recent Australian [30] study identified that there were fewer RRT calls during the night than during the day (45 % of MET calls occur between 2000 and 0800 h). Even though ALF was prevalent, there was no diurnal variation in the pattern of ALF occurrence. Patients with afferent limb failure, compared to those without afferent limb failure, were significantly more likely to have an unanticipated ICU admission [36] (45/131 (34.4 %) versus 100/443 (22.5 %), p = 0.01). If there is a biological plausibility that major physiologic perturbations happen during the late night/early morning hours (Table 1) then, theoretically at least, there should be more MET calls during those hours. The absence of this pattern may either stem from afferent limb failure or the presence of another phenomenon that needs to be explored further.

Diurnal variation in responding to clinical deterioration

Studies on diurnal variation in unanticipated ICU admissions, particularly regarding afferent limb failure and patient monitoring, are few. Patients admitted to hospitals after hours and at weekends have a higher observed and risk-adjusted mortality than patients admitted at other times [60, 64]. Current evidence is sparse with regard to the diurnal variation in the way we respond to acute deteriorations in patients who have to be cared for in hospital areas without the appropriate skill set. Delaying/deflecting admission to ICUs for this group of critically ill patients has been shown to be associated with worse outcomes [65].

From a health economics and risk management perspective, it is not unreasonable to have a 24/7 hospital-wide acute medical service [66] in addition to the critical care service. In particular, the response of a hospital’s acute services, e.g. trauma teams, critical care teams, RRTs, acute medical/acute surgical units and operation room (OR) availability with senior anaesthetist oversight, should be consistent across the day/night. In major hospitals during the day, a patient who has an RRT call gets the RRT team.

The RRT subsequently does a handover to the home team [67]. Overnight, the RRT operates [68] like a “hospitalist” service. That is, it sees any patient (no matter what the super-speciality home team is) and manages them in the absence of the home team. It may, if the complexity of the problem exceeds their and the ICU’s capacity or required super-speciality input, contact the home team overnight [62]. Otherwise, they deal with the issues and hand them over the next day to the home team. The burden of managing patients on the wards after hours in the absence of a member of the home team impacts significantly on the workload [55, 62] of the RRT and could divert them from their main role as “crisis managers”, which primarily revolves around troubleshooting clinical conundrums.

A hospitalist may work in parallel to the RRS in the early detection and response [69] to deteriorating patients, consistently across day and night time. Medically complex, elderly patients at risk of acute deterioration are more likely to populate acute hospitals. Increasing hospitalist workload has been associated with increased length of stay for patients and a high financial cost to the exchequer. In this scenario, the desire to maintain acute hospital [70] performance (e.g. shorter length of stay, greater patient throughput) will be accompanied by a greater demand for immediate access to critical care services.

Challenges to hospital management at night: interface between RRT and hospitalists

The main challenge to hospital management at night would be the way the system deals with the sickest patients. These patients need the most astute doctors, and they need them at the right time. The hierarchical pyramid of a super-speciality consultant, doctors in training, interns, etc. may no longer provide efficient delivery of acute patient care. Clinicians must be comfortable dealing with diversity, complexity and chaos. The required skill set for this level of care is more often found among critical care and general medical/surgical physicians.

The transition [68] is already starting to occur. There are emerging data indicating that hospitalists [68] (i.e. generalists, general physicians), are more proficient in acute hospital care. Hospitals that employ hospitalists were potentially able to decrease the length of stay, minimize costs and improve mortality, without compromising patient outcomes or family satisfaction. Providing hospitalists [68] 24 h a day for 7 days a week is likely to be a major challenge for hospital management, particularly at night. The other important element is the environment in which acutely unwell inpatients are managed. Inpatients, regardless of their actual or perceived risk of deterioration, are often co-located (e.g. in a general ward). As a consequence, oversight of all types of patients may be equivalent, despite vast differences in their individual risks of an adverse event.

Thus, among RRSs, strategies have been developed to detect acute deterioration across the spectrum of inpatients (e.g. standardized patient observation and response charts). Despite the varying levels of evidence, the concept of locating undifferentiated/complex patients, within a critical care environment, coordinated and overseen by specialist physicians using a closed model is valid. Current evidence [69] reveals that inability to escalate care and thereby failure to rescue a deteriorating patient occurs in approximately 20 % of inpatients. Hospitalists [68] could potentially close the “treatment gap” and rescue such patients who could possibly fall between the cracks in the system.

Challenges to hospital management at night: interface between RRT and palliative care

Recognizing medical futility and discussing the transition [70] from acute care to limited or palliative care based on accurate prognosis remains a challenge for both patients and clinicians, especially at night. There is a potential for therapy to become fragmented [71] and less tailored to the patient as a result of diurnal variation in the number and seniority of physicians available to make urgent clinical decisions.

Also, hospitals which have high nurse-staffing levels [71] achieve better satisfaction scores among patients, and this is an area for hospital administrators to be cognizant about, particularly with reference to the quality of clinical care. Improving senior medical oversight [72] at night with aims to improve system outcomes, ascertain medical futility, avoid inappropriate referrals, admissions to critical care and facilitate accurate prognostication is a way forward and the hospital at night [72] initiative is a positive step in that direction.

Patient and clinician expectations may not always be aligned [73], and this could pose difficulties in formulating a consensus on the medical management of a critically ill patient. The involvement of the rapid response teams in end-of-life decision-making [74] has also increased in recent times and, coupled with the diurnal variation in patients’ clinical condition and system issues [33] (i.e. afferent limb failure), management of patients in high-acuity ICU’s and hospitals, particularly at night [75], has become more complex and arduous.

Implications

The overarching implications of diurnal variation within the RRSs and afferent limb failure, in particular, are that it impacts on the quality of care that patients receive. This literature review has shown that data are sparse on variations in outcomes through the 24-h day/night period. Variations, if they exist, might be physiological and unmodifiable. Equally, they may be diurnal and modifiable. However, we lack robust evidence to explain the complex interrelationship between circadian rhythm (intrinsic) and diurnal variation (extrinsic). Observational and interventional studies evaluating nocturnal surveillance and its association with resource limitations, circadian variation and confounding factors are needed.

Conclusions

Diurnal variation exists in the activity of rapid response systems in the context of physiological circadian rhythms. Diurnal variation in the performance of hospitals, as measured by the quality and adequacy of patient monitoring, is a clear and immediate concern. Also, diurnal variation in the prevalence of afferent limb failure and its consequences has not been fully elucidated. The nexus between extrinsic hospital processes and innate human physiology across all critical and non-acute areas of a hospital in a 24-h period needs to be further investigated as this could potentially influence nocturnal patient management in hospitals.

Abbreviations

AMU:

Acute Medical Unit

ASU:

Acute Surgical Unit

CCU:

Coronary Care Unit

OR:

Operating Room

HDU:

High Dependency Unit

RRT:

rapid response teams

ALF:

afferent limb failure

ICU:

intensive care unit

MET:

medical emergency team

RRSs:

rapid response systems

References

  1. Herlitz J, Bang A, Aune S, et al. Characteristics and outcome among patients suffering in-hospital cardiac arrest in monitored and non-monitored areas. Resuscitation. 2001;48(2):125–35.

    Article  CAS  PubMed  Google Scholar 

  2. Buist M et al. Six-year audit of cardiac arrests and medical emergency team calls in an Australian outer metropolitan teaching hospital. BMJ. 2007;335:1210–12.

    Article  PubMed Central  PubMed  Google Scholar 

  3. McQuillan P, Pilkington S, Allan A, et al. Confidential inquiry into quality of care before admission to intensive care. BMJ. 1998;316:1853–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Maloney ED et al. Do consultants differ? Inferences drawn from hospital inpatient enquiry (HIPE) discharge coding at an Irish teaching hospital. Postgrad Med J. 2005;81:327–32.

    Article  Google Scholar 

  5. Mullins CF, Psirides A. Activities of a Medical Emergency Team: a prospective observational study of 795 calls. Anaesth Intensive Care. 2016;44(1):34–43.

    CAS  PubMed  Google Scholar 

  6. Smith G, Nielsen M. ABC of intensive care. Criteria for admission. BMJ. 1999;318:1544–7.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Simchen E, Sprung CL, Galai N, et al. Survival of critically ill patients hospitalized in and out of intensive care. Crit Care Med. 2007;35:449–57.

    Article  PubMed  Google Scholar 

  8. Leuvan CH, Mitchell I. Missed opportunities? An observational study of vital sign measurements. Crit Care Resusc. 2008;10(2):111–15.

    PubMed  Google Scholar 

  9. Devita MA, Bellomo R, Hillman K, et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med. 2006;34:2463–78.

    Article  PubMed  Google Scholar 

  10. Hillman KM, Bristow PJ, Chey T, et al. Antecedents to hospital deaths. Int Med J. 2001;31:343–8.

    Article  CAS  Google Scholar 

  11. Buist MD, Jarmolowski E, Burton PR, Bernard SA, Waxman BP, Anderson J. Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care. A pilot study in a tertiary-care hospital. Med J Aust. 1999;171:22–5.

    CAS  PubMed  Google Scholar 

  12. Franklin C, Mathew J. Developing strategies to prevent in hospital cardiac arrest: analysing responses of physicians and nurses in the hours before the event. Crit Care Med. 1994;22:244–7.

    Article  CAS  PubMed  Google Scholar 

  13. Jones D, Bellomo R, DeVita MA. Effectiveness of the medical emergency team: the importance of dose. Crit Care. 2009;13(5):313.

    Article  PubMed Central  PubMed  Google Scholar 

  14. Buist MD, Moore GE, Bernard SA, Waxman BP, Anderson JN, Nguyen TV. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. BMJ. 2002;324:387.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Jones D, Bellomo R, Bates S, et al. Long-term effect of a medical emergency team on cardiac arrests in a teaching hospital. Crit Care. 2005;9:R808–15.

    Article  PubMed Central  PubMed  Google Scholar 

  16. Chen J, Hillman KM. Cardiopulmonary arrest and mortality trends, and their association with rapid response system expansion. Med J Aust. 2015;202(1):20.

    Article  PubMed  Google Scholar 

  17. Australian Commission on Safety and Quality in Health Care. National consensus statement: essential elements for recognising and responding to clinical deterioration. Sydney: ACSQHC; 2010.

    Google Scholar 

  18. Khan SA, Hasan AS. South Asian health: what is to be done? Who cares about super-specialisation? BMJ. 2004;328(7443):839.

    Article  Google Scholar 

  19. Smith GB et al. Knowledge of aspects of acute care in trainee doctors. Postgrad Med J. 2002;78:335–8.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Kellett J. Acute hospital medicine—a new sub-specialty or internal medicine reborn? Euro J Int Med. 2011;22:334–8.

    Article  Google Scholar 

  21. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before-and-after trial of a medical emergency team. Med J Aust. 2003;179:283–7.

    PubMed  Google Scholar 

  22. Chalfin DB, Trzeciak S, Likourezos A, Baumann BM, Dellinger RP. Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit. Crit Care Med. 2007;35:1477–83.

    Article  PubMed  Google Scholar 

  23. Harris S, Singer M, Rowan K, Sanderson C. Delay to admission to critical care and mortality among deteriorating ward patients in UK hospitals: a multicentre, prospective, observational cohort study. Lancet. 2015;26:385.

    Google Scholar 

  24. McLaughlin NI, Leslie GD, Williams TA, Dobb GJ. Examining the occurrence of adverse events within 72 hours of discharge from the intensive care unit. Anaesth Intensive Care. 2007;35(4):486–93.

    CAS  PubMed  Google Scholar 

  25. Schein RM, Hazday N, Pena M. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–92.

    Article  CAS  PubMed  Google Scholar 

  26. Ludikhuize J, Smorenburg SM, de Rooij SE, de Jonge E. Identification of deteriorating patients on general wards: measurement of vital parameters and potential effectiveness of the Modified Early Warning Score. Journal of Critical Care. 2012;27(4):424.e7–424.e13.

    Article  Google Scholar 

  27. Alam N, Hobbelink EL, van Tienhoven AJ. The impact of the use of the Early Warning Score (EWS) on patient outcomes: a systematic review. Resuscitation. 2014;85(5):587–94.

    Article  CAS  PubMed  Google Scholar 

  28. Badriyah T, Briggs JS, Meredith P, Jarvis SW, Schmidt PE, Featherstone PI, et al. Decision-tree early warning score (DTEWS) validates the design of the National Early Warning Score (NEWS). Resuscitation. 2014;85(3):418–23.

  29. Smith GB, Prytherch DR, Meredith P, Schmidt PE, Featherstone PI. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013;84(4):465–70.

    Article  PubMed  Google Scholar 

  30. Trinkle R, Flabouris A. Critical care patient reviews preceding adverse events: their nature and impact upon patient outcome. Critical Care and Resuscitation. 2011;13:175–80.

    PubMed  Google Scholar 

  31. Jones D, Bellomo R, Bates S, Warrillow S, Goldsmith D, Hart G, et al. Patient monitoring and the timing of cardiac arrests and medical emergency team calls in a teaching hospital. Intensive Care Med. 2006;32(9):1352–6.

    Article  PubMed  Google Scholar 

  32. Marshall SDI, Kitto S, Shearer W, Wilson SJ, Finnigan MA, Sturgess T, et al. Why don’t hospital staffs activate the rapid response system (RRS)? How frequently is it needed and can the process be improved? Implement Sci. 2011;6:39.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Sandroni C, Cavallaro F. Failure of the afferent limb: a persistent problem in rapid response systems. Resuscitation. 2011;82:797–8.

    Article  PubMed  Google Scholar 

  34. Fieselmann JF, Hendryx MS, Helms CM, Wakefield DS. Respiratory rate predicts cardiopulmonary arrest for internal medicine inpatients. Journal of General Internal Medicine. 1993;8:354–60.

    Article  CAS  PubMed  Google Scholar 

  35. Guinane JL, Bucknall TK, Currey J, Jones DA. Missed medical emergency team activations: tracking decisions and outcomes in practice. Crit Care Resusc. 2013;15(4):266–72.

    PubMed  Google Scholar 

  36. Trinkle R, Flabouris A. Documenting rapid response system afferent limb failure and associated patient outcomes. Resuscitation. 2011;43(8):1587–94.

    Google Scholar 

  37. Hillman K, Chen J, Cretikos M. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. MERIT study investigators. Lancet. 2005;365(9477):2091–7.

    Article  PubMed  Google Scholar 

  38. Cretikos MA, Bellomo R, Hillman K, Chen J, Finfer S, Flabouris A. Respiratory rate: the neglected vital sign. Med J Aust. 2008;188:657–9.

    PubMed  Google Scholar 

  39. Chen J, Hillman K, Bellomo R, MERIT Study Investigators for the Simpson Centre, ANZICS Clinical Trials Group, et al. The impact of introducing medical emergency team system on the documentations of vital signs. Resuscitation. 2009;80:35–43.

    Article  PubMed  Google Scholar 

  40. McGain FI, Cretikos MA, Jones D. Documentation of clinical review and vital signs after major surgery. Med J Aust. 2008;189(7):380–3.

    PubMed  Google Scholar 

  41. Fagan K, Sabel A, Mehler PS, MacKenzie TD. Vital sign abnormalities, rapid response, and adverse outcomes in hospitalized patients. American Journal of Medical Quality. 2012;27:480–6.

    Article  PubMed  Google Scholar 

  42. Cherry RA, King TS, Carney DE, Bryant P, Cooney RN. Trauma team activation and the impact on mortality. J Trauma. 2007;63:326–30.

    Article  PubMed  Google Scholar 

  43. Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD. Cochrane Database Syst Rev. 2012;13(6):CD000259.

  44. Yates DW, Bancewicz J, Woodford M, et al. Trauma audit—closing the loop. Injury. 1994;25:511–14.

    Article  CAS  PubMed  Google Scholar 

  45. Bellomo R, Ackerman M, Bailey M. A controlled trial of electronic automated advisory vital signs monitoring in general hospital wards. Crit Care Med. 2012;40(8):2349–61.

    Article  PubMed  Google Scholar 

  46. Liaw SY, Wong LF, Ang SB. Strengthening the afferent limb of rapid response systems: an educational intervention using web-based learning for early recognition and responding to deteriorating patients. BMJ Qual Saf. 2015 Aug 21. PMID: 26297379

  47. Kitto S, Marshall SD, McMillan SE. Rapid response systems and collective (in) competence: an exploratory analysis of intra-professional and interprofessional activation factors. J Interprof Care. 2015;29(4):340–6. Epub 2014 Nov 28.

    Article  PubMed  Google Scholar 

  48. Tirkkonen J, Ylä-Mattila J, Olkkola KT. Factors associated with delayed activation of medical emergency team and excess mortality: an Utstein-style analysis. Resuscitation. 2013;84(2):173–8.

    Article  PubMed  Google Scholar 

  49. Cahill H, Jones A, Herkes R, et al. Introduction of a new observation chart and education programme is associated with higher rates of vital sign ascertainment in hospital wards. British Medical Journal Quality Safety. 2012;20:791–6.

    Article  Google Scholar 

  50. Smith GB, Prytherch DR, Schmidt P. Hospital-wide physiological surveillance: a new approach to the early identification and management of the sick patient. Resuscitation. 2006;71(1):19–28. Epub 2006 Aug 30.

    Article  PubMed  Google Scholar 

  51. Cornelissen G, Halberg F, Halberg J, Schwartzkopff O, Cugini P. Remembering the father of chronobiology and chronomics: Franz Halberg, MD (5 July 1919–9 June 2013). Clin Ter. 2013;164(4):I–VI.

    CAS  PubMed  Google Scholar 

  52. Oldham MA, Lee HB, Desan PH. Circadian rhythm disruption in the critically ill: an opportunity for improving outcomes. Crit Care Med. 2015 Aug 25. [Epub ahead of print]

  53. Needleman J et al. Nurse staffing and inpatient hospital mortality. N Engl J Med. 2011;364:1037–45.

    Article  CAS  PubMed  Google Scholar 

  54. Pronovost PJ, Angus DC, Dorman T, et al. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA. 2002;288:2151–62.

    Article  PubMed  Google Scholar 

  55. Neuraz A, Guérin C, Payet. Patient mortality is associated with staff resources and workload in the ICU: a multicenter observational study. Crit Care Med. 2015;43(8):1587–94.

    Article  PubMed  Google Scholar 

  56. Dybdal B, Svane C, Hesselfeldt R, et al. Is there a diurnal difference in mortality of severely injured trauma patients? Emergency Medicine Journal. 2015;32(4):287–90.

    Article  PubMed  Google Scholar 

  57. Amirian I, Andersen LT, Rosenberg J, Gögenur I. Working night shifts affects surgeons’ biological rhythm. Am J Surg. 2015;210(2):389–95.

    Article  PubMed  Google Scholar 

  58. Bisbal M, Pauly V, Gainnier M. Does admission during morning rounds increase the mortality of patients in the medical ICU? Chest. 2012;142(5):1179–84.

    Article  PubMed  Google Scholar 

  59. Jones D, Bates S, Warrillow S. Circadian pattern of activation of the medical emergency team in a teaching hospital. Crit Care. 2005;9(4):R303–6. Epub 2005 Apr 28.

    Article  PubMed Central  PubMed  Google Scholar 

  60. Bhonagiri D, Pilcher DV, Bailey MJ. Increased mortality associated with after-hours and weekend admission to the intensive care unit: a retrospective analysis. Med J Aust. 2011;194:287–92.

    PubMed  Google Scholar 

  61. Gartner D, Farley K, Bailey M, Huckson S, Hicks P, Pilcher D. Mortality related to after-hours discharge from intensive care in Australia and New Zealand, 2005–2012. Intensive Care Med. 2014;40(10):1528–35.

    Article  Google Scholar 

  62. Santamaria JD, Duke GJ, Pilcher DV. The timing of discharge from the intensive care unit and subsequent mortality. A prospective, multicentre study. Am J Respir Crit Care Med. 2015;191(9):1033–9.

    Article  PubMed  Google Scholar 

  63. Galhotra S, DeVita MA, Simmons RL, Schmid A. Impact of patient monitoring on the diurnal pattern of medical emergency team activation. Crit Care Med. 2006;34(6):1700–6.

    Article  PubMed  Google Scholar 

  64. Desai V, Gonda D, Ryan SL. The effect of weekend and after-hours surgery on morbidity and mortality rates in pediatric neurosurgery patients. J Neurosurg Pediatr. 2015;16(6):726–31.

    Article  PubMed  Google Scholar 

  65. Bing-Hua YU. Delayed admission to intensive care unit for critically surgical patients is associated with increased mortality. Am J Surg. 2014;208(2):268–74. Epub 2014 Jan 3.

    Article  CAS  PubMed  Google Scholar 

  66. Visser P, Dwyer A, Moran J, Britton M, Heland M, Ciavarella F, et al. Medical emergency response in a sub-acute hospital: improving the model of care for deteriorating patients. Aust Health Rev. 2014;38(2):169–76.9-105.

    PubMed  Google Scholar 

  67. Mardegan K, Heland M, Whitelock T, Millar R, Jones D. Developing a medical emergency team running sheet to improve clinical handoff and documentation. Jt Comm J Qual Patient Saf. 2013;39(12):570–5.

    PubMed  Google Scholar 

  68. Wachter RM et al. The emerging role of “hospitalists” in the American health care system. New Engl J Med. 1996;335:514–7.

    Article  CAS  PubMed  Google Scholar 

  69. Johnston MJ, Arora S, King D. A systematic review to identify the factors that affect failure to rescue and escalation of care in surgery. Surgery. 2015;157(4):752–63.

    Article  PubMed  Google Scholar 

  70. Chang A, Datta-Barua I, McLaughlin B, Daly B. A survey of prognosis discussions held by health-care providers who request palliative care consultation. Palliat Med. 2014;28(4):312–7.

    Article  PubMed  Google Scholar 

  71. Ashish K et al. Patients’ perception of hospital care in the United States. N Engl J Med. 2008;359:1921–31.

    Article  Google Scholar 

  72. Beckett DJ, Gordon CF, Paterson R. Improvement in out-of-hours outcomes following the implementation of Hospital at Night. QJM. 2009;102(8):539–46.

    Article  CAS  PubMed  Google Scholar 

  73. Flannery L, Ramjan LM, Peters K. End-of-life decisions in the intensive care unit (ICU)—exploring the experiences of ICU nurses and doctors—a critical literature review. Aust Crit Care. 2015.

  74. Hilton AK, Jones D, Bellomo R. Clinical review: the role of the intensivist and the rapid response team in nosocomial end-of-life care. Crit Care. 2013;17(2):224.

    Article  PubMed Central  PubMed  Google Scholar 

  75. Kerlin MP, Small DS, Cooney E, Fuchs BD, Bellini LM, Mikelle ME. A randomized trial of night-time physician staffing in an intensive care unit. N Engl J Med. 2013;368(23):2201–9.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  76. Davies O, DeVita MA, Ayinla R, Perez X. Barriers to activation of the rapid response system. Resuscitation. 2014;85(11):1557–61.

    Article  PubMed  Google Scholar 

  77. Tirkkonen J, Yla-Mattila J, Olkkola KT, Huhtala H, Tenhunen J, Hoppu S. Factors associated with delayed activation of medical emergency team and excess mortality: an Utstein-style analysis. Resuscitation. 2013;84(2):173–78.

    Article  PubMed  Google Scholar 

  78. Bragshaw SM, Mondor EE, Scouten C, et al. A survey of nurses’ beliefs about the medical emergency team system in a Canadian tertiary hospital. Am J Crit Care. 2010;19:74–83.

    Article  Google Scholar 

  79. Galhotra S, Scholle CC, Drew MA, et al. Medical emergency teams: a strategy for improving patient care and nursing work environments. J Adv Nurs. 2006;55:180–7.

    Article  PubMed  Google Scholar 

  80. Jacques T, Harrison GA, McLaws ML. Attitudes towards and evaluation of medical emergency teams: a survey of trainees in intensive care medicine. Anaesth Intensive Care. 2008;36:90–5.

    CAS  PubMed  Google Scholar 

  81. Jones D, Baldwin I, McIntyre T, et al. Nurses’ attitudes to a medical emergency team service in a teaching hospital. Qual Saf Health Care. 2006;15:427–32.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  82. Azzopardi P, Kinney S, Moulden A, Tibballs J. Attitudes and barriers to a medical emergency team system at a tertiary paediatric hospital. Resuscitation. 2011;82:167–174.

    Article  PubMed  Google Scholar 

  83. Radeschi G, Urso F, Campagna S, Berchialla P, Borga S, Mina A, Penso R, Di Pietrantonj C, Sandroni C. Factors affecting attitudes and barriers to a medical emergency team among nurses and medical doctors: a multi-centre survey. Resuscitation. 2015;88:92–8.

    Article  PubMed  Google Scholar 

  84. Curtis AM, Cheng Y, Kapoor S, et al. Circadian variation of blood pressure and the vascular response to asynchronous stress. Proc Natl Acad Sci USA. 2007; 104:3450–3455.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  85. Malik M, Farrell T, Camm AJ. Circadian rhythm of heart rate variability after acute myocardial infarction and its influence on the prognostic value of heart rate variability. Am J Cardiol. 1990;66:1049–54.

    Article  CAS  PubMed  Google Scholar 

  86. Tofler GH, Brezinski D, Schafer AI, et al. Concurrent morning increase in platelet aggregability and the risk of myocardial infarction and sudden cardiac death. N Engl J Med. 1987;316:1514–518.

    Article  CAS  PubMed  Google Scholar 

  87. Butler MP, Smales C. The circadian system contributes to apnoea lengthening across the night in obstructive sleep apnoea. Sleep. 2015;28.

  88. Goldberg RJ, Ye C, Sermer M, Circadian variation in the response to the glucose challenge test in pregnancy: implications for screening for gestational diabetes mellitus. Diabetes Care. 2012;35(7):1578–84.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  89. Weller JA, Buchanan TW, Shackleford C, Diurnal cortisol rhythm is associated with increased risky decision-making in older adults. Psychol Aging. 2014;29(2):271–83.

    Article  PubMed Central  PubMed  Google Scholar 

  90. Luik AI, Zuurbier LA, Hofman A, Van Someren EJ, Ikram MA, Tiemeier H. Associations of the 24-h activity rhythm and sleep with cognition: a population-based study of middle-aged and elderly persons. Sleep Med. 2015;16(7):850–5.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

None.

Author information

Authors and Affiliations

  1. Intensive Care Unit, Royal Adelaide Hospital and Discipline of Acute Care Medicine, University of Adelaide, Level 4, ICU, Robert Gerard Wing, Adelaide, 5000, South Australia, Australia

    Krishnaswamy Sundararajan & Arthas Flabouris

  2. Department of Medicine, University of Adelaide and the Royal Adelaide Hospital, Adelaide, 5000, South Australia, Australia

    Campbell Thompson

Authors
  1. Krishnaswamy Sundararajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arthas Flabouris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Campbell Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Krishnaswamy Sundararajan.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

KS conceived the idea, formulated the research question, conducted the literature review, collected and collated the data, prepared the manuscript, proof read and submitted to the journal. AF assisted with the literature search, verified the references, manuscript editing and prepared the graphs and assisted with proof reading. CT supervised the preparation of the manuscript, edited the manuscript and offered intellectual input. All authors read and approved the final manuscript.

Additional file

Additional file 1:

Australian Commission on Safety and Quality in Health Care (ACSQHC) standards. (PDF 1013 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sundararajan, K., Flabouris, A. & Thompson, C. Diurnal variation in the performance of rapid response systems: the role of critical care services—a review article. j intensive care 4, 15 (2016). https://doi.org/10.1186/s40560-016-0136-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40560-016-0136-5

Keywords

Journal of Intensive Care

ISSN: 2052-0492