You are here

  • Home
  • Archive
  • Volume 9, Issue 11
  • Optimising paediatric afferent component early warning systems: a hermeneutic systematic literature review and model development

Article Text

Article menu

Download PDFPDF

XML
Paediatrics
Original research
Optimising paediatric afferent component early warning systems: a hermeneutic systematic literature review and model development
  1. Nina Jacob1,
  2. Yvonne Moriarty1,
  3. Amy Lloyd1,
  4. Mala Mann2,
  5. Lyvonne N Tume3,
  6. Gerri Sefton4,
  7. Colin Powell5,6,
  8. Damian Roland7,8,
  9. Robert Trubey1,
  10. Kerenza Hood1,
  11. Davina Allen9
  1. 1 Centre for Trials Research, Cardiff University, Cardiff, UK
  2. 2 University Library Services, Cardiff University, Cardiff, UK
  3. 3 Faculty of Health and Applied Sciences (HAS), University of the West of England Bristol, Bristol, UK
  4. 4 Alder Hey Children's NHS Foundation Trust, Liverpool, UK
  5. 5 Department of Pediatric Emergency Medicine, Sidra Medical and Research Center, Doha, Qatar
  6. 6 Division of Population Medicine, School of Medicine, Cardiff University, Cardiff, UK
  7. 7 Emergency Department, Paediatric Emergency Medicine Leicester Academic (PEMLA) Group, Leicester, UK
  8. 8 SAPPHIRE Group, University of Leicester Department of Health Sciences, Leicester, UK
  9. 9 School of Healthcare Sciences, Cardiff University, Cardiff, UK
  1. Correspondence to Dr Nina Jacob; Jacobn{at}cardiff.ac.uk

Abstract

Objective To identify the core components of successful early warning systems for detecting and initiating action in response to clinical deterioration in paediatric inpatients.

Methods A hermeneutic systematic literature review informed by translational mobilisation theory and normalisation process theory was used to synthesise 82 studies of paediatric and adult early warning systems and interventions to support the detection of clinical deterioration and escalation of care. This method, which is designed to develop understanding, enabled the development of a propositional model of an optimal afferent component early warning system.

Results Detecting deterioration and initiating action in response to clinical deterioration in paediatric inpatients involves several challenges, and the potential failure points in early warning systems are well documented. Track and trigger tools (TTT) are commonly used and have value in supporting key mechanisms of action but depend on certain preconditions for successful integration into practice. Several supplementary interventions have been proposed to improve the effectiveness of early warning systems but there is limited evidence to recommend their wider use, due to the weight and quality of the evidence; the extent to which systems are conditioned by the local clinical context; and the need to attend to system component relationships, which do not work in isolation. While it was not possible to make empirical recommendations for practice, the review methodology generated theoretical inferences about the core components of an optimal system for early warning systems. These are presented as a propositional model conceptualised as three subsystems: detection, planning and action.

Conclusions There is a growing consensus of the need to think beyond TTTs in improving action to detect and respond to clinical deterioration. Clinical teams wishing to improve early warning systems can use the model to consider systematically the constellation of factors necessary to support detection, planning and action and consider how these arrangements can be implemented in their local context.

PROSPERO registration number CRD42015015326.

  • PEWS
  • track and trigger scores
  • early warning scores
  • clinical deterioration
  • children
  • systematic review

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/bmjopen-2018-028796

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Strengths and limitations of this study

    • The literature in this field is heterogeneous and better at identifying system weakness than it is effective improvement interventions. By deploying social theories and a hermeneutic review methodology it was possible to develop a propositional model of the core components of an afferent component paediatric early warning system.

    • The model is derived from logical inferences drawing on the overall evidence synthesis, social theories and clinical expertise, rather than strong empirical evidence of single intervention effectiveness.

    • There is a growing consensus of the need to take a whole systems approach to improve the detection and response to deterioration in the inpatient paediatric population and this paper offers an evidence-based framework for this purpose.

    Introduction

    Failure to recognise and act on signs of clinical deterioration in the hospitalised child is an acknowledged safety concern.1 Track and trigger tools (TTT) are a common response to this problem. A TTT consists of sequential recording and monitoring of physiological, clinical and observational data. When a certain score or trigger is reached then a clinical action should occur including, but not limited to, altered frequency of observation, senior review or more appropriate treatment or management. Tools may be paper based or electronic and monitoring can be automated or undertaken manually by staff.

    Despite the growing use of TTTs there is limited evidence of their effectiveness as a single intervention in reducing mortality or arrest rates in hospitalised children.2 3 Results from the largest international cluster randomised controlled trial of a TTT (the Bedside Paediatric Early Warning System (BedsidePEWS)) did not support TTT use to reduce mortality, and highlighted the multifactorial mechanisms involved in detecting and initiating action in response to deterioration.4 These findings lend further weight to a developing consensus about the need to look beyond TTTs to the impact of wider system factors on detecting and responding to deterioration in the inpatient paediatric population.2 5–9 This paper reports on a theoretically informed systematic hermeneutic literature review10 to identify the core components and mechanisms of action of successful afferent component early warning systems (EWS) in paediatric hospitals and is one of three linked reviews undertaken as part of a wider UK study commissioned to develop and evaluate an evidence-based paediatric warning system.3 11 It addressed the following question:

    ​What sociomaterial and contextual factors are associated with successful or unsuccessful Paediatric Early Warning Systems (with or without TTTs)?

    Method

    Design

    We performed a hermeneutic systematic review of the relevant literature. A hermeneutic systematic review is an iterative process, integrating analysis and interpretation of evidence with literature searching and is designed to develop a better understanding of the field.10 The popularity of the method is growing in health services research where it has value in generating insights from heterogeneous literatures that cannot be synthesised through standard review methodology12 and would otherwise produce inconclusive findings (see ref 9). The purpose of the review was not exhaustive aggregation of evidence, but to develop an understanding of the social, material and contextual factors associated with successful or unsuccessful paediatric early warning systems (PEWS).

    Theoretical framework

    Data extraction and interpretation was informed by translational mobilisation theory (TMT)13 14 and normalisation process theory (NPT).15 16 TMT is a practice theory which explains how goal-oriented collaborative activity is mobilised in unpredictable environments (box 1) and how the relevant mechanisms of action are conditioned by the local context. It is well suited for understanding EWS which require the organisation of action in evolving conditions, in a variety of clinical environments, with different teams, skill mixes, resources, structures and technologies. NPT shares the same domain assumptions as TMT and is concerned with ‘how and why things become, or do not become, routine and normal components of everyday work’,15 16 directing attention to the preconditions necessary for successful implementation of interventions. The theoretical framework informed our data extraction strategy, interpretation of the evidence and the development of a propositional model of an optimal paediatric early warning system.

    Box 1

    Mechanisms of translational mobilisation and their application to rescue trajectories14

    Object formation—how people draw on the interpretative resources available to them within a strategic action field to create the objects of their practice. Enrolment into an escalation trajectory requires multiple examples of object formation beginning with construction of an individual as at risk of deterioration and a regime of vital signs monitoring instigated, through recognition that the patient’s physiological status is a cause for concern, to the identification of the patient as requiring a specific intervention. How this is achieved is highly dependent on the features of the local strategic action field.

    Translation—the processes that enable practice objects to be shared and different understandings accommodated. It points to the actions necessary in order for a patient that is an object of concern for nursing staff to be translated into a clinical priority for the doctor and, if necessary, to be translated into the focus of intervention by the emergency response team.

    Articulation refers to the secondary work processes that align the actions, knowledge and resources necessary for the mobilisation of projects of collective action. It is the work that makes the work, work. Responding to deterioration is time critical and articulation work is necessary to ensure the availability of resources and materials to support clinical management. This is not a mundane observation; catastrophic failures in patient safety are often attributed to the lack of functioning equipment107 and the absence of monitoring equipment has been identified as a factor undermining the implementation of early warning track and trigger tools.48Attending to articulation in rescue trajectories also underlines the temporal ordering of action and the mechanisms required to achieve this, directing improvement efforts towards the organisation’s escalation policy, for example.

    Reflexive monitoring refers to the processes through which people collectively or individually appraise and review activity. In a distributed field of action, reflexive monitoring is the means through which members accomplish situational awareness108 of an overall project. The importance of situation awareness in rescue trajectories is well recognised, but achieving this is challenging. Reflexive monitoring is conditioned by the wider institutional context which will include a multiplicity of informal and formal mechanisms designed for this purpose: nursing and medical handovers, the ward round, safety briefings. The form, frequency and effectiveness of these processes in supporting detecting and acting on deterioration would need to be taken into account in any improvement initiative.

    Sensemaking refers to the processes through which agents create order in conditions of complexity. It draws attention to how the material and discursive processes by which members organise their work, account for their actions and construct the objects of their practice also give meaning and substance to the institutional components of strategic action fields that shape activity and condition future activity.

    Focus of the review

    The literature in this field identifies four integrated components which work together to provide a safety system for at-risk patients: (1) the afferent component which detects deterioration and triggers timely and appropriate action; (2) the efferent component which consists of the people and resources providing a response; (3) a process improvement component, which includes system auditing and monitoring; and (4) an administrative component focusing on organisational leadership and education required to implement and sustain the system.17 Our focus was limited to the afferent components of the system.

    Stages of the review

    Stage 1: scoping the literature

    Literature was identified through a recent scoping review,7 team members’ knowledge of the field, hand searches and snowball sampling techniques. The purpose was to (1) inform our review question and eligibility criteria and (2) identify emerging themes and issues. While we drew on several reviews of the literature5 12–14 we always consulted original papers. Data were extracted using data extraction template 1 (online supplementary appendix 1) and analysed to produce a provisional conceptual model of the core components of paediatric early warning systems. Additional themes of relevance were identified: family involvement, situational awareness (SA), structured handover, observations and monitoring and the impact of electronic systems and new technologies.

    Supplemental material

    Stage 2: searching for the evidence

    We undertook systematic searches of the paediatric and adult EWS literature (the goals and mechanisms of collective action in detection and rescue trajectories are the same). For the adult literature we used the same search strategies but added a qualitative filter to limit the scope to studies most likely to yield the level of sociomaterial and contextual detail of value to the review. Literature informing additional areas of interest was located through a combination of systematic and hand searches. Systematic searches (searches 2 and 3) were undertaken in areas where we anticipated locating evidence of the effectiveness of specific interventions to strengthen EWS. Theory-driven searches reflected the conceptual requirements of the model development.

    Systematic searches

    A systematic search was initially conducted across a range of databases from 1995 to September 2016 to identify relevant studies on the PEWS literature. This search was updated to cover literature from September 2016 to May 2018. An additional three systematic searches were conducted from 1995 to September 2016 to identify supplementary papers to aid in developing understanding on the PEWS literature:

    1. Adult EWS.

    2. Interventions to improve SA.

    3. Structured communication tools for handover and handoff.

    Detailed information on the search methodology can be found in online supplementary appendix 2. Grey literature was excluded in order to keep the review manageable.

    Theory-driven searches

    Additional theory-driven searches were conducted in the following areas:

    1. Family involvement.

    2. Observations and monitoring.

    3. The impact of electronic systems.

    These were a combination of exploratory, computerised, snowball and hand searches. As the analysis progressed, we continued to review new literature on EWS as this was published.

    Screening

    After removing duplicates 5284 references were identified for screening. A modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram is provided (figure 1). Papers were screened by title to assess eligibility and then by full text to assess relevance for data extraction. The PEWS and adult EWS searches were screened by two researchers, searches 2 and 3 were screened by the lead reviewer.

    Figure 1
    Figure 1

    Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram (adapted from Moher et al 109).

    Stage 3: data extraction and appraisal

    Data extraction template 2 (online supplementary appendix 3) was applied to all papers included in the review. As is typical of reviews of this kind, evidential fragments and partial lines of inquiry formed the unit of analysis rather than whole papers.18 These fragments were quality assessed according to the contribution they made to the developing analysis rather than assessing the paper as whole through the use of formal appraisal tools. Data extraction and quality appraisal were undertaken concurrently and double checked by a second reviewer.

    Stage 4: developing a propositional model

    A propositional model was developed specifying the core ingredients of a paediatric early warning system (table 1). It comprises logical inferences derived from the theoretical framework and evidence synthesis, informed by clinical experts on the team. Iterations of the model were developed in collaboration with clinical colleagues. A series of face-to-face meetings were conducted to review structure, wording and applicability to clinical practice.

    View this table:
    Table 1

    Propositional model

    Patient and public involvement

    This review was conducted as part of a larger mixed methods study (ISRCTN 94228292), which used a formal, facilitated parental advisory group. The group comprised parents of children who had experienced an unexpected adverse event in a paediatric unit and provided input which helped shape the broader research questions and wider contextual factors to consider, specifically within the family involvement element of the system. The results of the review will be disseminated to parents through this group.

    Results

    Included studies

    Eighty-two papers were included in the review. Forty-six papers focused on TTT implementation and use in paediatric and adult contexts (24 from the paediatric search and the remaining 22 from the adult-focused search); the remaining 36 papers contributed supplementary data on factors related to the wider warning system. See table 2 for a detailed breakdown of this process. No studies were located that adopted a whole systems approach to detecting and responding to deterioration.

    View this table:
    Table 2

    Screening breakdown

    Analysis

    In TMT the primary unit of analysis is the ‘project’, which defines the social and material actors (people, materials, technologies) and their relationships involved in achieving a particular goal. The goals of the afferent paediatric warning system are: first, that the child is identified as at risk and a vital signs monitoring regime instigated; second, that evidence of deterioration is identified through monitoring and categorised as such; and third, that timely and appropriate action is initiated in response to deterioration. Our analysis of the literature suggests that three subsystems within the afferent component of EWS support these processes: the detection of signs deterioration; the planning needed to ensure teams are ready to act when deterioration is detected; and the initiation of timely action. While we have focused on the afferent component, it is important to remember that all elements of the overall safety system (efferent component, process improvement and administrative arm) need to be working in concert in order to maintain an optimal paediatric early warning system. In the next section, we report on the literature in relation to each subsystem.

    Detection

    The goal of the detection subsystem is to recognise early signs of deterioration, so the child becomes the focus of further clinical attention. This requires, first, that the child is identified as at risk and a vital signs monitoring regime instigated and, second, that the child is identified as showing signs of deterioration.

    Despite widespread use, the evidence on TTT effectiveness in predicting adverse outcomes in hospitalised children is weak.3 Many TTTs have only been validated retrospectively and postpredictive values were generally low. Studies reporting significant decreases in cardiac arrest calls or mortality had methodological concerns. The literature does suggest that TTTs have value in supporting process mechanisms in the detection subsystem. Vital signs monitoring is undertaken on all hospital inpatients and, like other high-volume routine activity, is often delegated to junior staff19–38 who may not have sufficient skills to interpret results.21 22 37 TTTs have value in mitigating these risks: by specifying physiological thresholds that indicate deterioration they take knowledge to the bedside and act as prompts to action19 39 which can lead to a more systematic and frequent approach to monitoring and improved detection of deterioration.40 41

    TTT’s effectiveness in fulfilling these functions depends on certain preconditions. The review highlighted that TTT use was impacted by the availability of appropriate and functioning equipment,22 27 29 34 39 42–46 (in)adequate staffing and night-time pressures22 26 29 30 37 40 42–44 47–52 and an appropriately skilled workforce.26 28 36 43 49 50 53–57 On this latter point, while several papers report on education packages to improve the detection of deterioration, the evidence is not robust enough to recommend specific programmes.23–25 28 30 35 55 58–60 There were also times whereby nursing staff prioritised sleep over waking a patient to take vital signs.46 61

    TTTs are also used differently depending on the experience of the user. For juniors, they provide a methodology and structure for monitoring clinical instability and identifying deterioration, whereas more experienced staff reportedly use TTTs as confirmatory technologies.19–32 The importance of professional intuition in detecting deterioration is extensively reported across the literature19–22 26 27 29 31 32 36–40 42 43 45 46 48 50–53 60 62–68 and several authors recommend the inclusion of ‘staff concern’ in tool criteria.26 48 51 57 This is important; TTTs may be of less value in patients with chronic conditions because of altered normal physiology or where subtle changes are difficult to detect.64 It is also the case that TTTs are implemented in contexts governed by competing organisational logics which impact on their value and use.43 54 58 For example, Mohammed Iddrisu et al 57 show TTTs have limited value immediately after surgery because acceptable vital sign parameters are different in the immediate postoperative period.

    There is growing interest in the literature in strategies that facilitate patient and relative involvement in the early detection of deterioration.69 70 Healthcare professionals depend on families to explain their child’s normal physiological baseline and identify subtle changes in their child’s condition but this information is not always systematically obtained.71 72 Some authors propose family involvement in interdisciplinary rounds (This is an editorial paper),73 but this requires parents to have detailed information about the signs and symptoms they should be attending to72 and as yet there is little evidence on effective strategies for how they might be involved in the detection of deterioration.73

    While much of the literature reports on intermittent manual vital signs monitoring and paper-based recording systems, across the developed world there is a growing use of electronic technologies, which have important implications for the wider detection subsystem.74 We considered a number of evaluations of new technologies which indicated that electronic vital signs recording is associated with a number of positive outcomes, particularly timeliness and accuracy, when compared with paper-based systems.75 76 They can provide prompts or alerts for monitoring,77–79 which facilitates better recognition of deterioration and is associated with a reduction in mortality.78 80 These studies tend to evaluate new technologies in isolation, however, and do not engage with the literature highlighting alarm fatigue which is known to mitigate effectiveness over time or concerns about overburdening staff with alerts.81–83 Moreover, the successful implementation of new technologies is conditioned by the local context. For instance, where manual input into an electronic device is required, access to computers is an essential precondition. When computers were not available, staff ‘batch’ the collection of vital signs before data entry, thereby delaying the timely detection of deterioration.27 45 84 In another study where the electronic system was found to be cumbersome and separated the collection and entry of data from the review of vital signs, verbal reports were favoured to ensure timely communication of information.85 See table 3 for a summary of the evidence reported.

    View this table:
    Table 3

    Summary of detection evidence

    Planning

    Detecting and responding to deterioration involves the coordination of action in conditions of uncertainty and competing priorities. The goal of the ‘Planning’ subsystem is to ensure the clinical team are ready to act in the event of evidence of deterioration and is reflected in the growing interest in the literature on structures to facilitate team SA, group decisions and planning.62

    TTTs have been found to support SA. Their use enabled clinicians to have a ‘bird’s-eye’ view over all admitted patients on a ward as well as encouraging staff to consider projected acuity levels of the ward.86 A number of studies also report on ‘huddles’ in facilitating SA.32 65 87 88 A huddle is a multidisciplinary event scheduled at predetermined times where members discuss specific risk factors around deterioration and develop mitigation plans. One study combined the introduction of huddles with a ‘watchstander’, a role fulfilled by a charge nurse or senior resident, whose primary function is to know patients at high risk for deterioration.88 These initiatives were associated with a near 50% reduction in transfers from acute to intensive care determined to be unrecognised situation awareness events. A further strategy identified by Goldenhar et al describes the use of the ‘watcher’ category to designate a patient as at risk where staff have a ‘gut feeling’ deterioration is likely.87 A recent study used the category of ‘watcher’ to create a bundle of expectations to standardise communication and contingency planning. Once a patient was labelled ‘a watcher’ a series of five specific tasks, such as documentation of physician awareness of watcher status and that the family had been notified of the change in the patient’s status, needed to be completed within 2 hours.89

    Handovers are integral to clinical communication and contribute to SA. The extensive literature on handover indicates that information sharing can be of variable quality47 54 90 and there is growing evidence that structured approaches improve this.30 47 54 63 87 90–94 Ranging from a checklist system91 93 to a cognitive aid developed through consensus,23 94 most of the published interventions are variations of the Situation-Background-Assessment-Recommendation (SBAR) tool.54 90–92 While effective handover depends on communicative forms that extend beyond the information transfer that is typically the focus of structured handover tools,90 in the context of EWS a lack of standardisation allows greater margin for individualistic practices and difficulties accessing complementary knowledge and establishing shared understandings.47

    There is also a literature on the use of common information spaces—such as whiteboards—in facilitating SA in the healthcare team.23 33 47 53 55 58 67 These should be in a visible location and colour coded to correspond with the TTT score, where relevant.47 55 58 Electronic systems automate this information and allow information to be reviewed remotely. However, they disconnect vital signs data from the patient and hence other indicators of clinical status and access to data is contingent upon the availability of computers.27 45 47 84 95

    The literature indicates that SA can be facilitated in different ways in different contexts and it is the relationship between system elements that is important.47 In their study on SA in delivery suites, Mackintosh et al discuss the three main supports for SA—whiteboard, handover and coordinator role—and illustrate how these interacted in organisations with strong SA compared with those with reduced levels. Crucially, this ‘interplay’ between the different activities was highly context dependent; ‘the same supports used differently generate different outcomes’ (p 52).47 See table 4 for a summary of the planning evidence.

    View this table:
    Table 4

    Summary of planning evidence

    Action

    The goal of the ‘Action’ subsystem is to initiate appropriate action in response to evidence of deterioration. The literature suggests that mobilising action across professional boundaries/hierarchies is challenging, with differences in language between doctors and nurses and power dynamics contributory factors.27 40 41 50 52 57 60 96 TTTs are in part a response to the challenges of communication in mobilising action in response to deterioration. By transforming a series of discrete observations into a summative indicator of deterioration—such as a score or a trigger—TTTs ‘translate’ and package the patient’s status into a form that can be readily communicated enabling individual-level clinical data to be synthesised, made sense of and shared.19–29 33 39 41 42 46 48 50 51 56 62 66 74 86 One study, however, found that TTTs were regarded as a nursing tool and were therefore not valued by clinicians. Consequently, nurses encountered difficulties in summoning a response.46

    Several studies also report on the use of SBAR in this context. Like TTTs, SBAR translates information into a form that provides structure, consistency and predictability when presenting patient information. SBAR has been shown to help establish common language and expectations, minimising differences in training, experience and hierarchy and facilitating nurse–clinician communication. While several papers advocate combining SBAR with TTTs,23 25 27 30 35 45 50 none specifically evaluated SBAR use. Mackintosh et al highlight that audit data suggest resistance to SBAR, with others cautioning that overextending SBAR use carries the risk of SBAR fatigue and attenuation of its effects.27

    Structured communication tools like TTTs and SBAR do not solve all the challenges of acting in response to evidence of deterioration. Barriers to action were widely reported in the literature where these tools were in place. These include: a general disinclination to seek help,19–22 25 27 29 31 36–39 42 48 50 51 56 64 67 concerns about appearing inadequate in front of colleagues20 22 36 38 50 67 and failure of staff to invest in the escalation or calling criteria.21 22 49 A number of papers also reported negative attitudes to rapid response team (RRT) or medical emergency team (MET) use in the efferent component of safety systems. METs and RRTs operate outside the immediate medical team and create different issues in paediatric warning systems than when the escalation response is managed by the treating team. These include a reluctance to activate because of the perceived busyness of paediatric intensive care unit or medical staff,20 29 39 48 50 51 because previous expectations about an appropriate response were not met, or a sense that the situation was under control (particularly when the physiological instability is in the area of expertise of the treating team).22 29 31 38 42 50 52 64

    No literature reported on successful interventions to facilitate RRT use, but several propose strategies to support escalation where there was no designated response team in place in the efferent component. These include informal peer support, where inexperienced staff team up with more experienced staff21 29 50 64 67; clear structures to support action and a supportive culture that does not penalise individual decision-making, including the use of a ‘no false alarms’ policy so staff are not deterred from escalating care.21 29 36 73 Senior leadership is consistently identified as important8 20–23 25 27 30 32 33 35 47 52 58 66 67; lack of support from superiors meant that staff are less likely to escalate and more likely to adhere to hierarchies within the current system.25 40 66 There is some evidence to suggest that any escalation policy should be linked to an administrative arm that reinforces the system, measures outcomes and works to ensure an effective system.27 30

    There is a small literature on family involvement in the Action subsystem. Several studies report on Condition-Help, a programme developed in the USA to support families to directly activate an RRT if they have concerns about their child’s condition. Families are also becoming increasingly recognised as playing a key role in the activation of RRTs in Australia.97 Research has evaluated the appropriateness of calls that were made by patients or relatives33 97–101 but has not considered why calls were not made.70 Involving family members in escalation demands vigilance, requiring them to take a proactive and interactive role with staff with potentially some degree of confrontation, particularly if challenging the appropriateness of decisions taken.73 97 Families need both cognitive and emotional resources to raise concerns that involve negotiating hierarchies and boundaries.35 70 The literature points to a degree of professional resistance to family involvement in activation, with reports of physician concern that their role would be undermined, that resources would be stretched with an increase in calls and that it might divert attention away from those in need71 97 99 102 103 although these fears are not supported by the evidence.71 102 104 See table 5 for a summary of the evidence relating to the action component of the model.

    View this table:
    Table 5

    Summary of action evidence

    Synthesis and model development

    The literature in this field is heterogeneous and stronger on the sociomaterial barriers to successful afferent component paediatric early warning systems than it is on solutions. While a number of different single interventions have been proposed and some have been evaluated, there is limited evidence to recommend their use beyond the specific clinical contexts described in the papers. This reflects both the weight and quality of the evidence, the extent to which paediatric systems are conditioned by the local clinical context and also the need to attend to the relationship between system components and interventions which work in concert not in isolation. There is also a growing realisation in the quality improvement field that an intervention that has been successful in one context does not necessarily produce the same results elsewhere which cautions against a ‘one size fits all’ approach.105 106

    While it is not possible to make empirical recommendations for practice, a hermeneutic review methodology enabled the generation of theoretical inferences about the core components of an optimal paediatric early warning system. These model components are logical inferences derived from an overall synthesis of the evidence, informed by our theoretical framework and clinical expertise. These are presented as a propositional model conceptualised as three subsystems: detection, planning and action (see table 1).

    Discussion

    This paper reports on one of three linked reviews undertaken as part of a wider UK study commissioned to develop and evaluate an evidence-based national paediatric early warning system.3 Drawing on TMT and NPT, we have synthesised and analysed the findings from the review to develop a propositional model to specify the core components of optimal afferent component paediatric early warning systems. While there is a growing consensus of the need to think beyond TTTs to consider the whole system, no frameworks exist to support such an approach. Clinical teams wishing to improve rescue trajectories should take a whole systems perspective focused on the constellation of factors necessary to support detection, planning and action and consider how these relationships can be managed in their local setting. TTTs have value in paediatric early warning systems but they are not the sole solution and depend on certain preconditions for their use. An emerging literature highlights the importance of planning and indicates that combinations of interventions may facilitate situation awareness. Professional judgement is also important in detecting and acting on deterioration and the evidence points to the importance of a wider organisational culture that is supportive of this. Innovative approaches are needed to support family involvement in all aspects of paediatric early warning systems, which are sensitive to the cognitive and emotional resources this requires. System effectiveness requires attention to the sociomaterial relationships in the local context, senior support and leadership and continuous monitoring and evaluation. New technologies, such as moving from paper-based to electronic TTTs, have important implications for all three subsystems and critical consideration should be given to their wider impacts and the preconditions for their integration into practice.

    Limitations of the review

    The literature in this field is heterogeneous and better at identifying system weakness than it is effective improvement interventions. It was only by deploying social theories and a hermeneutic review methodology did it prove possible to develop a propositional model of the core components of an afferent component paediatric early warning system. This model is derived from logical inferences drawing on the overall evidence synthesis, social theories and clinical expertise, rather than strong empirical evidence of single intervention effectiveness. Consequently, there is a growing consensus of the need to take a whole systems approach to improve the detection and response to deterioration in the inpatient paediatric population.

    Conclusion

    Failure to recognise and act on signs of deterioration is an acknowledged safety concern1 and TTTs are a common response to this problem. There is, however, a growing recognition of the importance of wider system factors on the effectiveness of responses to deterioration.5 7 We have reviewed a wide literature and analysed this using social theories to develop a propositional model of an optimal afferent component paediatric early warning system that can be used as a framework for paediatric units to evaluate their current practices and identify areas for improvement. TTT use should be driven by the extent to which teams think that they will help improve the effectiveness of their system as a whole.

    Acknowledgments

    The authors acknowledge the contribution of Dr Heather Strange to the review. The authors also extend their thanks to the parental advisory group who have helped shape the broader questions of the research study as well as offer guidance on wider contextual factors to consider within the overall paediatric early warning system.

    References

    1. 1.↵
      2. Subbe CP ,
      3. Welch JR
      . Failure to rescue: using rapid response systems to improve care of the deteriorating patient in hospital. Clin Risk 2013;19:6–11.doi:10.1177/1356262213486451
      OpenUrlCrossRef
    2. 2.↵
      2. Chapman SM ,
      3. Wray J ,
      4. Oulton K , et al
      . Systematic review of paediatric track and trigger systems for hospitalised children. Resuscitation 2016;109:87–109.doi:10.1016/j.resuscitation.2016.07.230
      OpenUrl
    3. 3.↵
      2. Trubey R ,
      3. Huang C ,
      4. Lugg-Widger FV , et al
      . Validity and effectiveness of paediatric early warning systems and track and trigger tools for identifying and reducing clinical deterioration in hospitalised children: a systematic review. BMJ Open 2019;9:e022105.doi:10.1136/bmjopen-2018-022105
    4. 4.↵
      2. Parshuram CS ,
      3. Dryden-Palmer K ,
      4. Farrell C , et al
      . Effect of a pediatric early warning system on all-cause mortality in hospitalized pediatric patients: the epoch randomized clinical trial. JAMA 2018;319:1002–12.doi:10.1001/jama.2018.0948
      OpenUrlPubMed
    5. 5.↵
      1. The Irish Paediatric Early Warning System (PEWS)
      . NCEC national clinical guideline No. 12. Department of Health Ireland, 2015.
    6. 6.↵
      2. Rihari-Thomas J ,
      3. Newton PJ ,
      4. Sibbritt D , et al
      . Rapid response systems: where we have come from and where we need to go? J Nurs Manag 2018;26:1–2.doi:10.1111/jonm.12533
      OpenUrl
    7. 7.↵
      2. Lambert V ,
      3. O’Shea M ,
      4. Walshe C , et al
      . A systematic literature review to support the development of a national clinical guideline – paediatric early warning system (PEWS), 2014. Available: http://health.gov.ie/wp-content/uploads/2014/03/PEWS-Sytematic-Literature-Review-Oct-2014.pdf [Accessed Aug 2019].
    8. 8.↵
      2. Almblad A-C ,
      3. Siltberg P ,
      4. Engvall G , et al
      . Implementation of pediatric early warning score; adherence to guidelines and influence of context. J Pediatr Nurs 2018;38:33–9.doi:10.1016/j.pedn.2017.09.002
      OpenUrl
    9. 9.↵
      2. Lambert V ,
      3. Matthews A ,
      4. MacDonell R , et al
      . Paediatric early warning systems for detecting and responding to clinical deterioration in children: a systematic review. BMJ Open 2017;7:e014497.doi:10.1136/bmjopen-2016-014497
    10. 10.↵
      2. Boell SK ,
      3. Cecez-Kecmanovic D
      . A hermeneutic approach for conducting literature reviews and literature searches. CAIS 2014;34:257–86.doi:10.17705/1CAIS.03412
      OpenUrl
    11. 11.↵
      2. Thomas-Jones E ,
      3. Lloyd A ,
      4. Roland D , et al
      . A prospective, mixed-methods, before and after study to identify the evidence base for the core components of an effective Paediatric Early Warning System and the development of an implementation package containing those core recommendations for use in the UK: Paediatric early warning system - utilisation and mortality avoidance- the PUMA study protocol. BMC Pediatr 2018;18:244.doi:10.1186/s12887-018-1210-z
    12. 12.↵
      2. Greenhalgh T ,
      3. A’Court C ,
      4. Shaw S
      . Understanding heart failure; explaining telehealth – a hermeneutic systematic review. BMC Cardiovasc Disord 2017;17:1–16.doi:10.1186/s12872-017-0594-2
      OpenUrl
    13. 13.↵
      2. Allen D ,
      3. May C ,
      4. Practice O
      . Organizing practice and practicing organization: an outline of translational mobilization theory. Sage Open 2017;7:215824401770799–43.doi:10.1177/2158244017707993
      OpenUrl
    14. 14.↵
      2. Allen D
      . Translational mobilisation theory: a new paradigm for understanding the organisational elements of nursing work. Int J Nurs Stud 2018;79:36–42.doi:10.1016/j.ijnurstu.2017.10.010
      OpenUrl
    15. 15.↵
      2. May C ,
      3. Finch T
      . Implementing, embedding, and integrating practices: an outline of normalization process theory. Sociology 2009;43:535–54.doi:10.1177/0038038509103208
      OpenUrlCrossRefWeb of Science
    16. 16.↵
      2. May CR ,
      3. Johnson M ,
      4. Finch T
      . Implementation, context and complexity. Implement Sci 2016;11:1–12.doi:10.1186/s13012-016-0506-3
      OpenUrlCrossRef
    17. 17.↵
      2. Jagt EWvander
      . Improving pediatric survival from resuscitation events: the role and organization of hospital-based rapid response systems and code teams. Curr Pediatr Rev 2013;9:158–74.doi:10.2174/1573396311309020009
      OpenUrlCrossRefPubMed
    18. 18.↵
      2. Pawson R
      . Evidence-based policy: a realist perspective. London: Sage, 2006.
    19. 19.↵
      2. Andrews T ,
      3. Waterman H
      . Packaging: a grounded theory of how to report physiological deterioration effectively. J Adv Nurs 2005;52:473–81.doi:10.1111/j.1365-2648.2005.03615.x
      OpenUrlCrossRefPubMedWeb of Science
    20. 20.↵
      2. Azzopardi P ,
      3. Kinney S ,
      4. Moulden A , et al
      . Attitudes and barriers to a medical emergency team system at a tertiary paediatric Hospital. Resuscitation 2011;82:167–74.doi:10.1016/j.resuscitation.2010.10.013
      OpenUrlCrossRefPubMed
    21. 21.↵
      2. Bonafide CP ,
      3. Roberts KE ,
      4. Weirich CM , et al
      . Beyond statistical prediction: qualitative evaluation of the mechanisms by which pediatric early warning scores impact patient safety. J Hosp Med 2013;8:248–53.doi:10.1002/jhm.2026
      OpenUrlCrossRefPubMed
    22. 22.↵
      2. Braaten JS
      . Ce: original research: hospital system barriers to rapid response team activation: a cognitive work analysis. Am J Nurs 2015;115:22–32.doi:10.1097/01.NAJ.0000460672.74447.4a
      OpenUrl
    23. 23.↵
      2. Ennis L
      . Paediatric early warning scores on a children's ward: a quality improvement initiative. Nurs Child Young People 2014;26:25–31.doi:10.7748/ncyp.26.7.25.e478
      OpenUrl
    24. 24.↵
      2. Kaul M ,
      3. Snethen J ,
      4. Kelber ST , et al
      . Implementation of the bedside paediatric early warning system (BedsidePEWS) for nurse identification of deteriorating patients. J Spec Pediatr Nurs 2014;19:339–49.doi:10.1111/jspn.12092
      OpenUrl
    25. 25.↵
      2. Lobos A-T ,
      3. Fernandes R ,
      4. Ramsay T , et al
      . Patient characteristics and disposition after pediatric medical emergency team (Met) activation: disposition depends on who activates the team. Hosp Pediatr 2014;4:99–105.doi:10.1542/hpeds.2013-0032
      OpenUrlAbstract/FREE Full Text
    26. 26.↵
      2. McDonnell A ,
      3. Tod A ,
      4. Bray K , et al
      . A before and after study assessing the impact of a new model for recognizing and responding to early signs of deterioration in an acute Hospital. J Adv Nurs 2013;69:41–52.doi:10.1111/j.1365-2648.2012.05986.x
      OpenUrlCrossRefPubMed
    27. 27.↵
      2. Mackintosh N ,
      3. Rainey H ,
      4. Sandall J
      . Understanding how rapid response systems may improve safety for the acutely ill patient: learning from the frontline. BMJ Qual Saf 2012;21:135–44.doi:10.1136/bmjqs-2011-000147
      OpenUrlAbstract/FREE Full Text
    28. 28.↵
      2. Monaghan A
      . Detecting and managing deterioration in children. Paediatr Nurs 2005;17:32–5.doi:10.7748/paed.17.1.32.s27
      OpenUrlCrossRefPubMed
    29. 29.↵
      2. Pattison N ,
      3. Eastham E
      . Critical care outreach referrals: a mixed-method investigative study of outcomes and experiences. Nurs Crit Care 2012;17:71–82.doi:10.1111/j.1478-5153.2011.00464.x
      OpenUrlCrossRefPubMed
    30. 30.↵
      2. Pearson G ,
      3. Duncan H
      . Early warning systems for identifying sick children. Paediatr Child Health 2011;21:230–3.doi:10.1016/j.paed.2011.02.007
      OpenUrlCrossRef
    31. 31.↵
      2. Shearer B ,
      3. Marshall S ,
      4. Buist MD , et al
      . What stops Hospital clinical staff from following protocols? An analysis of the incidence and factors behind the failure of bedside clinical staff to activate the rapid response system in a multi-campus Australian metropolitan healthcare service. BMJ Qual Saf 2012;21:569–75.doi:10.1136/bmjqs-2011-000692
      OpenUrlAbstract/FREE Full Text
    32. 32.↵
      2. Stewart J ,
      3. Carman M ,
      4. Spegman A , et al
      . Evaluation of the effect of the modified early warning system on the nurse-led activation of the rapid response system. J Nurs Care Qual 2014;29:223–9.doi:10.1097/NCQ.0000000000000048
      OpenUrl
    33. 33.↵
      2. Van Voorhis KT ,
      3. Willis TS
      . Implementing a pediatric rapid response system to improve quality and patient safety. Pediatr Clin North Am 2009;56:919–33.doi:10.1016/j.pcl.2009.05.017
      OpenUrlCrossRefPubMed
    34. 34.↵
      2. Wheatley I
      . The nursing practice of taking level 1 patient observations. Intensive Crit Care Nurs 2006;22:115–21.doi:10.1016/j.iccn.2005.08.003
      OpenUrlCrossRefPubMed
    35. 35.↵
      2. McCabe A ,
      3. Duncan H ,
      4. Heward Y
      . Paediatric early warning systems: where do we go from here? Paediatr Nurs 2009;21:14–17.doi:10.7748/paed.21.1.14.s20
      OpenUrlPubMed
    36. 36.↵
      2. Chua WL ,
      3. Mackey S ,
      4. Ng EKC , et al
      . Front line nurses' experiences with deteriorating ward patients: a qualitative study. Int Nurs Rev 2013;60:501–9.doi:10.1111/inr.12061
      OpenUrlCrossRefPubMed
    37. 37.↵
      2. James J ,
      3. Butler-Williams C ,
      4. Hunt J , et al
      . Vital signs for vital people: an exploratory study into the role of the healthcare assistant in recognising, recording and responding to the acutely ill patient in the general ward setting. J Nurs Manag 2010;18:548–55.doi:10.1111/j.1365-2834.2010.01086.x
      OpenUrlCrossRefPubMed
    38. 38.↵
      2. Mackintosh N ,
      3. Humphrey C ,
      4. Sandall J
      . The habitus of 'rescue' and its significance for implementation of rapid response systems in acute health care. Soc Sci Med 2014;120:233–42.doi:10.1016/j.socscimed.2014.09.033
      OpenUrl
    39. 39.↵
      2. Endacott R ,
      3. Westley M
      . Managing patients at risk of deterioration in rural hospitals: a qualitative study. Aust J Rural Health 2006;14:275–9.doi:10.1111/j.1440-1584.2006.00829.x
      OpenUrlCrossRefPubMed
    40. 40.↵
      2. Lydon S ,
      3. Byrne D ,
      4. Offiah G , et al
      . A mixed-methods investigation of health professionals' perceptions of a physiological track and trigger system. BMJ Qual Saf 2016;25:688–95.doi:10.1136/bmjqs-2015-004261
      OpenUrlAbstract/FREE Full Text
    41. 41.↵
      2. Sønning K ,
      3. Nyrud C ,
      4. Ravn IH
      . A survey of healthcare professionals ’ experiences with the paediatric early warning score (PEWS). Nor J Clin Nurs 2018;12:e64605.
    42. 42.↵
      2. Cioffi J ,
      3. Salter C ,
      4. Wilkes L , et al
      . Clinicians' responses to abnormal vital signs in an emergency department. Aust Crit Care 2006;19:66–72.doi:10.1016/S1036-7314(06)80011-1
      OpenUrlPubMed
    43. 43.↵
      2. Endacott R ,
      3. Kidd T ,
      4. Chaboyer W , et al
      . Recognition and communication of patient deterioration in a regional Hospital: a multi-methods study. Aust Crit Care 2007;20:100–5.doi:10.1016/j.aucc.2007.05.002
      OpenUrlCrossRefPubMed
    44. 44.↵
      2. Hands C ,
      3. Reid E ,
      4. Meredith P , et al
      . Patterns in the recording of vital signs and early warning scores: compliance with a clinical escalation protocol. BMJ Qual Saf 2013;22:719–26.doi:10.1136/bmjqs-2013-001954
      OpenUrlAbstract/FREE Full Text
    45. 45.↵
      2. Watson A ,
      3. Skipper C ,
      4. Steury R , et al
      . Inpatient nursing care and early warning scores: a workflow mismatch. J Nurs Care Qual 2014;29:215–22.doi:10.1097/NCQ.0000000000000058
      OpenUrlCrossRefPubMed
    46. 46.↵
      2. Jensen CS ,
      3. Nielsen PB ,
      4. Olesen HV , et al
      . Pediatric early warning score systems, nurses perspective – a focus group study. J Pediatr Nurs 2018;41:e16–22.doi:10.1016/j.pedn.2018.02.004
      OpenUrl
    47. 47.↵
      2. Mackintosh N ,
      3. Berridge E-J ,
      4. Freeth D
      . Supporting structures for team situation awareness and decision making: insights from four delivery suites. J Eval Clin Pract 2009;15:46–54.doi:10.1111/j.1365-2753.2008.00953.x
      OpenUrlCrossRefPubMedWeb of Science
    48. 48.↵
      2. Cioffi J
      . Nurses' experiences of making decisions to call emergency assistance to their patients. J Adv Nurs 2000;32:108–14.doi:10.1046/j.1365-2648.2000.01414.x
      OpenUrlCrossRefPubMedWeb of Science
    49. 49.↵
      2. Adelstein B-A ,
      3. Piza MA ,
      4. Nayyar V , et al
      . Rapid response systems: a prospective study of response times. J Crit Care 2011;26:635.e11–e18.doi:10.1016/j.jcrc.2011.03.013
      OpenUrlPubMed
    50. 50.↵
      2. Astroth KS ,
      3. Woith WM ,
      4. Stapleton SJ , et al
      . Qualitative exploration of nurses' decisions to activate rapid response teams. J Clin Nurs 2013;22:2876–82.doi:10.1111/jocn.12067
      OpenUrlCrossRefPubMed
    51. 51.↵
      2. Cioffi J
      . Recognition of patients who require emergency assistance: a descriptive study. Heart Lung 2000;29:262–8.doi:10.1067/mhl.2000.108327
      OpenUrlCrossRefPubMedWeb of Science
    52. 52.↵
      2. Mackintosh N ,
      3. Watson K ,
      4. Rance S , et al
      . Value of a modified early obstetric warning system (MEOWS) in managing maternal complications in the peripartum period: an ethnographic study. BMJ Qual Saf 2014;23:26–34.doi:10.1136/bmjqs-2012-001781
      OpenUrlAbstract/FREE Full Text
    53. 53.↵
      2. Davies O ,
      3. DeVita MA ,
      4. Ayinla R , et al
      . Barriers to activation of the rapid response system. Resuscitation 2014;85:1557–61.doi:10.1016/j.resuscitation.2014.07.013
      OpenUrlCrossRefPubMed
    54. 54.↵
      2. McCrory MC ,
      3. Aboumatar H ,
      4. Custer JW , et al
      . "ABC-SBAR" training improves simulated critical patient hand-off by pediatric interns. Pediatr Emerg Care 2012;28:538–43.doi:10.1097/PEC.0b013e3182587f6e
      OpenUrlCrossRefPubMed
    55. 55.↵
      2. Randhawa S ,
      3. Roberts-Turner Renee' ,
      4. Woronick K , et al
      . Implementing and sustaining evidence-based nursing practice to reduce pediatric cardiopulmonary arrest. West J Nurs Res 2011;33:443–56.doi:10.1177/0193945910379585
      OpenUrlCrossRefPubMed
    56. 56.↵
      2. Salamonson Y ,
      3. van Heere B ,
      4. Everett B , et al
      . Voices from the floor: nurses' perceptions of the medical emergency team. Intensive Crit Care Nurs 2006;22:138–43.doi:10.1016/j.iccn.2005.10.002
      OpenUrlCrossRefPubMed
    57. 57.↵
      2. Mohammed Iddrisu S ,
      3. Hutchinson AF ,
      4. Sungkar Y , et al
      . Nurses' role in recognising and responding to clinical deterioration in surgical patients. J Clin Nurs 2018;27:1920–30.doi:10.1111/jocn.14331
      OpenUrl
    58. 58.↵
      2. Demmel KM ,
      3. Williams L ,
      4. Flesch L
      . Implementation of the pediatric early warning scoring system on a pediatric hematology/oncology unit. J Pediatr Oncol Nurs 2010;27:229–40.doi:10.1177/1043454209358410
      OpenUrlCrossRefPubMed
    59. 59.↵
      2. McKay H ,
      3. Mitchell IA ,
      4. Sinn K , et al
      . Effect of a multifaceted intervention on documentation of vital signs and staff communication regarding deteriorating paediatric patients. J Paediatr Child Health 2013;49:48–56.doi:10.1111/jpc.12019
      OpenUrl
    60. 60.↵
      2. Radeschi G ,
      3. Urso F ,
      4. Campagna S , et al
      . Factors affecting attitudes and barriers to a medical emergency team among nurses and medical doctors: a multi-centre survey. Resuscitation 2015;88:92–8.doi:10.1016/j.resuscitation.2014.12.027
      OpenUrl
    61. 61.↵
      2. Hope J ,
      3. Recio-Saucedo A ,
      4. Fogg C , et al
      . A fundamental conflict of care: Nurses’ accounts of balancing patients' sleep with taking vital sign observations at night. J Clin Nurs 2018;27:1860–71.doi:10.1111/jocn.14234
      OpenUrl
    62. 62.↵
      2. de Groot JF ,
      3. Damen N ,
      4. de Loos E , et al
      . Implementing paediatric early warning scores systems in the Netherlands: future implications. BMC Pediatr 2018;18:128.doi:10.1186/s12887-018-1099-6
    63. 63.↵
      2. Brady PW ,
      3. Goldenhar LM
      . A qualitative study examining the influences on situation awareness and the identification, mitigation and escalation of recognised patient risk. BMJ Qual Saf 2014;23:153–61.doi:10.1136/bmjqs-2012-001747
      OpenUrlAbstract/FREE Full Text
    64. 64.↵
      2. Donohue LA ,
      3. Endacott R ,
      4. Track ER
      . Track, trigger and teamwork: communication of deterioration in acute medical and surgical wards. Intensive Crit Care Nurs 2010;26:10–17.doi:10.1016/j.iccn.2009.10.006
      OpenUrlCrossRefPubMed
    65. 65.↵
      2. Claussen D ,
      3. Garner D ,
      4. Crow B
      . Early warning signs and the EHR: at the intersection of technology and care. Nurs Manage 2013;44:14–16.doi:10.1097/01.NUMA.0000433384.49766.b4
      OpenUrl
    66. 66.↵
      2. Jones D ,
      3. Baldwin I ,
      4. McIntyre T , et al
      . Nurses' attitudes to a medical emergency team service in a teaching hospital. Qual Saf Health Care 2006;15:427–32.doi:10.1136/qshc.2005.016956
      OpenUrlAbstract/FREE Full Text
    67. 67.↵
      2. Massey D ,
      3. Chaboyer W ,
      4. Aitken L
      . Nurses' perceptions of accessing a medical emergency team: a qualitative study. Aust Crit Care 2014;27:133–8.doi:10.1016/j.aucc.2013.11.001
      OpenUrlCrossRefPubMedWeb of Science
    68. 68.↵
      2. Burns KA ,
      3. Reber T ,
      4. Theodore K , et al
      . Enhanced early warning system impact on nursing practice: a phenomenological study. J Adv Nurs 2018;74:1150–6.doi:10.1111/jan.13517
      OpenUrl
    69. 69.↵
      2. Rainey H ,
      3. Ehrich K ,
      4. Mackintosh N , et al
      . The role of patients and their relatives in 'speaking up' about their own safety - a qualitative study of acute illness. Health Expect 2015;18:392–405.doi:10.1111/hex.12044
      OpenUrl
    70. 70.↵
      2. Mackintosh NJ ,
      3. Davis RE ,
      4. Easter A , et al
      . Interventions to increase patient and family involvement in escalation of care for acute life-threatening illness in community health and hospital settings. Cochrane Database Syst Rev 2017;50.doi:10.1002/14651858.CD012829
    71. 71.↵
      2. Paciotti B ,
      3. Roberts KE ,
      4. Tibbetts KM , et al
      . Physician attitudes toward family-activated medical emergency teams for hospitalized children. Jt Comm J Qual Patient Saf 2014;40:187–92.doi:10.1016/S1553-7250(14)40024-2
      OpenUrlPubMed
    72. 72.↵
      2. Graedon J ,
      3. Graedon T
      . Enlisting families as patient safety allies. Clin Pediatr Emerg Med 2006;7:265–7.doi:10.1016/j.cpem.2006.08.006
      OpenUrl
    73. 73.↵
      2. Entwistle V
      . Nursing shortages and patient safety problems in hospital care: is clinical monitoring by families part of the solution? Health Expect 2004;7:1–5.doi:10.1046/j.1369-7625.2003.00259.x
      OpenUrlCrossRefPubMedWeb of Science
    74. 74.↵
      2. Downey CL ,
      3. Tahir W ,
      4. Randell R , et al
      . Strengths and limitations of early warning scores: a systematic review and narrative synthesis. Int J Nurs Stud 2017;76:106–19.doi:10.1016/j.ijnurstu.2017.09.003
      OpenUrlCrossRefPubMed
    75. 75.↵
      2. Mohammed M ,
      3. Hayton R ,
      4. Clements G , et al
      . Improving accuracy and efficiency of early warning scores in acute care. Br J Nurs 2009;18:18–24.doi:10.12968/bjon.2009.18.1.32072
      OpenUrlCrossRefPubMed
    76. 76.↵
      2. Sefton G ,
      3. Lane S ,
      4. Killen R , et al
      . Accuracy and efficiency of recording pediatric early warning scores using an electronic physiological surveillance system compared with traditional Paper-Based documentation. Comput Inform Nurs 2017;35:228–36.doi:10.1097/CIN.0000000000000305
      OpenUrlPubMed
    77. 77.↵
      2. Jones S ,
      3. Mullally M ,
      4. Ingleby S , et al
      . Bedside electronic capture of clinical observations and automated clinical alerts to improve compliance with an early warning score protocol. Crit Care Resusc 2011;13:83–8.
      OpenUrlPubMed
    78. 78.↵
      2. Schmidt PE ,
      3. Meredith P ,
      4. Prytherch DR , et al
      . Impact of introducing an electronic physiological surveillance system on hospital mortality. BMJ Qual Saf 2015;24:10–20.doi:10.1136/bmjqs-2014-003073
      OpenUrlAbstract/FREE Full Text
    79. 79.↵
      2. Bellomo R ,
      3. Ackerman M ,
      4. Bailey M , et al
      . A controlled trial of electronic automated Advisory vital signs monitoring in general Hospital wards. Crit Care Med 2012;40:2349–61.doi:10.1097/CCM.0b013e318255d9a0
      OpenUrlCrossRefPubMedWeb of Science
    80. 80.↵
      2. Subbe CP ,
      3. Duller B ,
      4. Bellomo R
      . Effect of an automated notification system for deteriorating ward patients on clinical outcomes. Crit Care 2017;21:1–9.doi:10.1186/s13054-017-1635-z
      OpenUrl
    81. 81.↵
      2. Bonafide CP ,
      3. Zander M ,
      4. Graham CS , et al
      . Video methods for evaluating physiologic monitor alarms and alarm responses. Biomed Instrum Technol 2014;48:220–30.doi:10.2345/0899-8205-48.3.220
      OpenUrl
    82. 82.↵
      2. Fagan K ,
      3. Sabel A ,
      4. Mehler PS , et al
      . Vital sign abnormalities, rapid response, and adverse outcomes in hospitalized patients. Am J Med Qual 2012;27:480–6.doi:10.1177/1062860611436127
      OpenUrlCrossRefPubMed
    83. 83.↵
      2. Bonafide CP ,
      3. Localio AR ,
      4. Holmes JH , et al
      . Video analysis of factors associated with response time to physiologic monitor alarms in a children's Hospital. JAMA Pediatr 2017;171:524–31.doi:10.1001/jamapediatrics.2016.5123
      OpenUrl
    84. 84.↵
      2. Wager KA ,
      3. Schaffner MJ ,
      4. Foulois B , et al
      . Comparison of the quality and timeliness of vital signs data using three different data-entry devices. Comput Inform Nurs 2010;28:205–12.doi:10.1097/NCN.0b013e3181e1df19
      OpenUrlCrossRefPubMed
    85. 85.↵
      2. Stevenson JE ,
      3. Nilsson G
      . Nurses’ perceptions of an electronic patient record from a patient safety perspective: a qualitative study. J Adv Nurs 2012;68:667–76.doi:10.1111/j.1365-2648.2011.05786.x
      OpenUrlCrossRefPubMed
    86. 86.↵
      2. de Vries A ,
      3. Draaisma JMT ,
      4. Fuijkschot J
      . Clinician perceptions of an early warning system on patient safety. Hosp Pediatr 2017;7:579–86.doi:10.1542/hpeds.2016-0138
      OpenUrlAbstract/FREE Full Text
    87. 87.↵
      2. Goldenhar LM ,
      3. Brady PW ,
      4. Sutcliffe KM , et al
      . Huddling for high reliability and situation awareness. BMJ Qual Saf 2013;22:899–906.doi:10.1136/bmjqs-2012-001467
      OpenUrlAbstract/FREE Full Text
    88. 88.↵
      2. Brady PW ,
      3. Muething S ,
      4. Kotagal U , et al
      . Improving situation awareness to reduce unrecognized clinical deterioration and serious safety events. Pediatrics 2013;131:e298–308.doi:10.1542/peds.2012-1364
      OpenUrlAbstract/FREE Full Text
    89. 89.↵
      2. Parker MW ,
      3. Carroll M ,
      4. Bolser B , et al
      . Implementation of a communication bundle for high-risk patients. Hosp Pediatr 2017;7:523–9.doi:10.1542/hpeds.2016-0170
      OpenUrlAbstract/FREE Full Text
    90. 90.↵
      2. Pezzolesi C ,
      3. Manser T ,
      4. Schifano F , et al
      . Human factors in clinical handover: development and testing of a 'handover performance tool' for doctors' shift handovers. Int J Qual Health Care 2013;25:58–65.doi:10.1093/intqhc/mzs076
      OpenUrlCrossRefPubMedWeb of Science
    91. 91.↵
      2. Abraham J ,
      3. Kannampallil T ,
      4. Patel B , et al
      . Ensuring patient safety in care transitions: an empirical evaluation of a handoff intervention tool. AMIA Annu Symp Proc 2012;2012:17–26.
      OpenUrl
    92. 92.↵
      2. Donahue M ,
      3. Smith L ,
      4. Dykes P , et al
      . Phase 2 of the empower project: enhancing communication for paraprofessionals. J Contin Educ Nurs 2010;41:197–8.
      OpenUrlCrossRefPubMedWeb of Science
    93. 93.↵
      2. Mullan PC ,
      3. Macias CG ,
      4. Hsu D , et al
      . A novel briefing checklist at shift handoff in an emergency department improves situational awareness and safety event identification. Pediatr Emerg Care 2015;31:231–8.doi:10.1097/PEC.0000000000000194
      OpenUrl
    94. 94.↵
      2. Weiss MJ ,
      3. Bhanji F ,
      4. Fontela PS , et al
      . A preliminary study of the impact of a handover cognitive aid on clinical reasoning and information transfer. Med Educ 2013;47:832–41.doi:10.1111/medu.12212
      OpenUrl
    95. 95.↵
      2. Wong D ,
      3. Bonnici T ,
      4. Knight J , et al
      . Send: a system for electronic notification and documentation of vital sign observations. BMC Med Inform Decis Mak 2015;15:68.doi:10.1186/s12911-015-0186-y
    96. 96.↵
      2. Preece MHW ,
      3. Hill A ,
      4. Horswill MS , et al
      . Designing observation charts to optimize the detection of patient deterioriation: reliance on the subjective preferences of healthcare professionals is not enough. Aust Crit Care 2012;25:238–52.doi:10.1016/j.aucc.2012.01.003
      OpenUrlCrossRefPubMedWeb of Science
    97. 97.↵
      2. Gill FJ ,
      3. Leslie GD ,
      4. Marshall AP
      . Family initiated escalation of care for the deteriorating patient in hospital: Family centred care or just "box ticking". Aust Crit Care 2016;29:195–200.doi:10.1016/j.aucc.2016.07.004
      OpenUrl
    98. 98.↵
      2. Bogert S ,
      3. Ferrell C ,
      4. Rutledge DN
      . Experience with family activation of rapid response teams. Medsurg Nurs 2010;19:215–22.
      OpenUrlPubMed
    99. 99.↵
      2. Dean BS ,
      3. Decker MJ ,
      4. Hupp D , et al
      . Condition help: a pediatric rapid response team triggered by patients and parents. J Healthc Qual 2008;30:28–31.doi:10.1111/j.1945-1474.2008.tb01139.x
      OpenUrlCrossRefPubMed
    100. 100.↵
      2. Greenhouse PK ,
      3. Kuzminsky B ,
      4. Martin SC , et al
      . Calling a condition H(elp). Am J Nurs 2006;106:63–6.doi:10.1097/00000446-200611000-00021
      OpenUrlPubMed
    101. 101.↵
      2. Hueckel RM ,
      3. Mericle JM ,
      4. Frush K , et al
      . Implementation of condition help: family teaching and evaluation of family understanding. J Nurs Care Qual 2012;27:176–81.doi:10.1097/NCQ.0b013e318235bdec
      OpenUrlCrossRefPubMed
    102. 102.↵
      2. Brady PW ,
      3. Zix J ,
      4. Brilli R , et al
      . Developing and evaluating the success of a family activated medical emergency team: a quality improvement report. BMJ Qual Saf 2015;24:203–11.doi:10.1136/bmjqs-2014-003001
      OpenUrlAbstract/FREE Full Text
    103. 103.↵
      2. Gerdik C ,
      3. Vallish RO ,
      4. Miles K , et al
      . Successful implementation of a family and patient activated rapid response team in an adult level 1 trauma center. Resuscitation 2010;81:1676–81.doi:10.1016/j.resuscitation.2010.06.020
      OpenUrlCrossRefPubMedWeb of Science
    104. 104.↵
      2. Bavare AC ,
      3. Thomas JK ,
      4. Elliott EP , et al
      . Family-Initiated pediatric rapid response: characteristics, Impetus, and outcomes. J Healthc Qual 2018;40:103–9.doi:10.1097/JHQ.0000000000000096
      OpenUrl
    105. 105.↵
      2. Bion J ,
      3. Richardson A ,
      4. Hibbert P , et al
      . 'Matching Michigan': a 2-year stepped interventional programme to minimise central venous catheter-blood stream infections in intensive care units in England. BMJ Qual Saf 2013;22:110–23.doi:10.1136/bmjqs-2012-001325
      OpenUrlAbstract/FREE Full Text
    106. 106.↵
      2. Dixon-Woods M ,
      3. Leslie M ,
      4. Tarrant C , et al
      . Explaining matching Michigan: an ethnographic study of a patient safety program. Implement Sci 2013;8.doi:10.1186/1748-5908-8-70
    107. 107.↵
      1. National Patient Safety Agency
      . Recognising and responding appropriately to early signs of deterioration in hospitalised patients. London: NPSA, 2008.
    108. 108.↵
      2. Gilson RD
      . Special issue preface. Hum Factors 1995;37:3–4.doi:10.1518/001872095779049426
      OpenUrlCrossRefWeb of Science
    109. 109.↵
      2. Moher D ,
      3. Liberati A ,
      4. Tetzlaff J , et al
      . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009;6:e1000097.

    Footnotes

    • Twitter @YvonneCMoriarty, @SysReviews, @damian_roland

    • Contributors NJ: screening and review of papers; led the theoretical synthesis of the literature; contributed to model development; preparation and writing of the manuscript (with DA). YM: screening and review of papers; contributed to model development; contributed to the drafting of the manuscript. AL: led the model development (with DA); contributed to the drafting of the manuscript. MM: conceived and led the systematic search strategies; review of manuscript. LNT, GS, CP, DR: screening and review of papers; contributed clinical expertise; contributed to model development; contributed to the drafting of the manuscript. RT: screening and review of manuscript. KH: contributed to model development; contributed to the drafting of the manuscript. DA: conceived and designed the review; led the theoretical framing and analysis; screening and review of papers; led the model development (with AL); and led the writing of the manuscript (with NJ).

    • Funding This study is funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research (HS&DR) programme (12/178/17).

    • Disclaimer The views and opinions expressed in this paper are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.