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BACKGROUND: Poor communication contributes to adverse events (AEs). In our hospital, following an experience of a fatal incident in 2014, we developed an educational programme aimed at improving communication for better teamwork that led to a reduction in AEs. METHODS: We developed and implemented an intervention bundle comprising external investigation committee reviews, the establishment of a working group (WG), standards and emergency response guidelines, as well as educational programmes and tools. To determine the effectiveness of the educational programmes, we measured communication abilities among doctors and nurses by administering psychological scales focused on their confidence in speaking up. Furthermore, we applied the trigger tool methodology in a retrospective study to determine if our interventions had reduced AEs. RESULTS: The nurses' scores for 'perceived barriers to speaking up' and 'negative attitude toward voicing opinions in the healthcare team' decreased significantly after the training from 3.20 to 3.00 and from 2.47 to 2.29 points, respectively. The junior doctors' scores for the same items also decreased significantly after the training from 3.34 to 2.51 and from 2.42 to 2.11 points, respectively. The number of AEs was 32.1 (median) before the WG, 39.9 (median) before the general training, 22.2 (median) after the general training and 18.4 (median) after implementing the leadership educational programmes. During the intervention period the hospital's incident reports per employee kept increasing. CONCLUSION: Our new educational programmes improved junior doctors and nurses' perceptions of speaking up. We speculated that our intervention may have improved staff communication, which in turn may have led to a reduction in AEs and a sustained increase in incident reports per employee.

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Clinical tools for use in practice-such as medicine reconciliation charts, diagnosis support tools and track-and-trigger charts-are endemic in healthcare, but relatively little attention is given to how to optimise their design. User-centred design approaches and co-design principles offer potential for improving usability and acceptability of clinical tools, but limited practical guidance is currently available. We propose a framework (FRamework for co-dESign of Clinical practice tOols or 'FRESCO') offering practical guidance based on user-centred methods and co-design principles, organised in five steps: (1) establish a multidisciplinary advisory group; (2) develop initial drafts of the prototype; (3) conduct think-aloud usability evaluations; (4) test in clinical simulations; (5) generate a final prototype informed by workshops. We applied the framework in a case study to support co-design of a prototype track-and-trigger chart for detecting and responding to possible fetal deterioration during labour. This started with establishing an advisory group of 22 members with varied expertise. Two initial draft prototypes were developed-one based on a version produced by national bodies, and the other with similar content but designed using human factors principles. Think-aloud usability evaluations of these prototypes were conducted with 15 professionals, and the findings used to inform co-design of an improved draft prototype. This was tested with 52 maternity professionals from five maternity units through clinical simulations. Analysis of these simulations and six workshops were used to co-design the final prototype to the point of readiness for large-scale testing. By codifying existing methods and principles into a single framework, FRESCO supported mobilisation of the expertise and ingenuity of diverse stakeholders to co-design a prototype track-and-trigger chart in an area of pressing service need. Subject to further evaluation, the framework has potential for application beyond the area of clinical practice in which it was applied.

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INTRODUCTION: Adverse events (AEs) in helicopter emergency medical services (HEMS) remain poorly reported, despite the potential for harm to occur. The trigger tool (TT) represents a novel approach to AE detection in healthcare. The aim of this study was to retrospectively describe the frequency of AEs and their proximal causes (PCs) in Qatar HEMS. METHODS: Using the Pittsburgh Adverse Event Tool to identify AEs in HEMS, we retrospectively analysed 804 records within an existing AE TT database (21-month period). We calculated outcome measures for triggers, AEs and harm per 100 patient encounters, plotted measures on statistical process control charts, and conducted a multivariate analysis to report harm associations. RESULTS: We identified 883 triggers in 536 patients, with a rate of 1.1 triggers per patient encounter, where 81.2% had documentation errors (n=436). An AE and harm rate of 27.7% and 3.5%, respectively, was realised. The leading PC was actions by HEMS Crew (81.6%; n=182). The majority of harm (57.1%) stemmed from the intervention and medication triggers (n=16), where deviation from standard of care was common (37.9%; n=11). Age and diagnosis-adjusted odds were significant in the patient condition (6.50; 95% CI 1.71 to 24.67; p=0.01) and interventional (11.85; 95% CI 1.36 to 102.92; p=0.03) trigger groupings, while age and diagnosis had no effect on harm. CONCLUSION: The TT methodology is a robust, reliable and valid means of AE detection in the HEMS domain. While an AE rate of 27.7% is high, more research is required to understand prehospital clinical decision-making and reasons for guideline deviance. Furthermore, focused quality improvement initiatives to reduce AEs and documentation errors should also be addressed in future research.

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BACKGROUND: Adverse events (AEs) cause suffering for hospitalised children, a fragile patient group where the delivery of adequate timely care is of great importance. OBJECTIVE: To report the incidence and characteristics of AEs, in paediatric inpatient care, as detected with the Global Trigger Tool (GTT), the Trigger Tool (TT) or the Harvard Medical Practice Study (HMPS) method. METHOD: MEDLINE, Embase, Web of Science and Google Scholar were searched from inception to June 2021, without language restrictions. Studies using manual record review were included if paediatric data were reported separately. We excluded studies reporting: AEs for a specific disease/diagnosis/treatment/procedure, or deceased patients; study protocols with no AE outcomes; conference abstracts, editorials and systematic reviews; clinical incident reports as the primary data source; and studies focusing on specific AEs only. Methodological risk of bias was assessed using a tool based on the Quality Assessment Tool for Diagnostic Accuracy Studies 2. Primary outcome was the percentage of admissions with ≥1 AEs. All statistical analyses were stratified by record review methodology (GTT/TT or HMPS) and by type of population. Meta-analyses, applying random-effects models, were carried out. The variability of the pooled estimates was characterised by 95% prediction intervals (PIs). RESULTS: We included 32 studies from 44 publications, conducted in 15 countries totalling 33 873 paediatric admissions. The total number of AEs identified was 8577. The most common types of AEs were nosocomial infections (range, 6.8%-59.6%) for the general care population and pulmonary-related (10.5%-36.7%) for intensive care. The reported incidence rates were highly heterogeneous. The PIs for the primary outcome were 3.8%-53.8% and 6.9%-91.6% for GTT/TT studies (general and intensive care population). The equivalent PI was 0.3%-33.7% for HMPS studies (general care). The PIs for preventable AEs were 7.4%-96.2% and 4.5%-98.9% for GTT/TT studies (general and intensive care population) and 10.4%-91.8% for HMPS studies (general care). The quality assessment indicated several methodological concerns regarding the included studies. CONCLUSION: The reported incidence of AEs is highly variable in paediatric inpatient care research, and it is not possible to estimate a reliable single rate. Poor reporting standards and methodological differences hinder the comparison of study results.

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Aim: To evaluate the contribution of medical imaging request forms as trigger tools to detect patient adverse event (AE) occurring during hospitalization. Material and Methods: This is a retrospective study in a single institution. Between January and June 2019, the hospital information system (HIS) was fetched for request forms of radiological examinations performed for inpatients >48 hours after the admission date. The investigated request forms were: Doppler ultrasound of the upper limbs, Doppler ultrasound of the lower limbs, and the repetition of three consecutive requests of chest radiographs within 24 hrs, to detect upper or lower limb venous thrombosis, or AEs related to the respiratory system, respectively. Patients' medical charts and radiological examinations were evaluated to document the presence or absence of an AE. The frequencies of AEs in the three groups of trigger tools were compared to corresponding control groups, matched according to age, sex and length of stay. Results: Among a total of 2798 hospital admissions during the study period, there were 74 files triggered by the three types of radiological request forms. There were 6/24 AE (25%) related to upper limb venous thrombosis, 4/33 (12.1%) AE related to lower limb venous thrombosis, and 6/17 (35.3%) AE related to the respiratory system. For all the trigger tools, the frequency of AE in the study groups was significantly higher than that in the control groups. Conclusion: Medical imaging requests could be used as potential trigger tools to detect adverse events related to hospital stay.

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PURPOSE: While the use of Pediatric Track and Trigger Tools as a standard to discriminate high level of urgency in pediatric care has received considerable attention, less focus has been given to other important factors such as nurses' clinical observations and judgement. The purpose of this study was to explore nurses' observational practice and focus on which non-measurable signs and symptoms nurses find important when identifying inpatient pediatric patients at risk of clinical deterioration. DESIGN AND METHODS: This was an inductive qualitative study based on an interpretive description methodology. Data were obtained through participant observation of experienced nurses working in a Danish pediatric unit and focus group interviews with pediatric nurses. Field notes were taken, and focus group interviews were audio taped and transcribed. A thematic text condensation method was used to analyse data. RESULTS: Findings revealed the following four main themes of non-measurable signs and symptoms that nurses find important when identifying children at risk of clinical deterioration: Colour and skin tone; sounds; movement patterns; behavioural signs. CONCLUSIONS: This study suggest that pediatric patients show signs and symptoms that go beyond the objective measurements integrated in Pediatric Track and Trigger Tools and they should not be ignored as they are highly valuable to nurses who are responsible for observing inpatient pediatric patients at risk of clinical deterioration. IMPLICATIONS: More empirical research on nurses' observational practice is recommended, especially research to identify the signs and symptoms - both measurable and non-measurable - that are significant to nurses at the bedside.

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BACKGROUND: Administration of antibiotics to septic patients within 1 h was recommended in 2018 by the Surviving Sepsis Campaign (SSC) as a strategy to improve survival outcomes. The use of sepsis screening tools in emergency departments (EDs) is important for early diagnosis and initiation of sepsis care. This study aimed to assess the impact of the Ramathibodi early warning score (REWs) on the administration of antibiotics within 1 h of presentation. METHODS: This was an observational retrospective cohort study with propensity score matching between the sepsis-3 criteria (pre-period) and the REWs (post-period) as screening tools in adult patients with sepsis in EDs. The primary outcome was the proportion of receiving antibiotics within 1 h of presentation in the pre- and post-periods. RESULTS: A total of 476 patients were analyzed without propensity matching. The proportion of antibiotic administration within 1 h was higher in patients screened using the REWs compared with standard of care in the total study population (79.5% vs. 61.4%, p < 0.001). After propensity score matching, 153 patients were included in both groups. The proportion of antibiotic administration within 1 h was similar in patients screened using the REWs and those receiving standard of care (79.7% vs. 80.4%, p = 0.886). However, time to intensive care unit (ICU) admission was faster in patients screened using the REWs. Delays in receiving antibiotics of longer than 3 h were associated with increased mortality (adjusted hazard ratio 7.04, 95% confidence interval 1.45 to 34.11, p = 0.015). CONCLUSIONS: Implementing the REWs as a tool in sepsis screening protocols in EDs did not improve rates of antibiotic administration within 1 h as recommended by the SSC. However, time to ICU admission was improved after implementation of the REWs.

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BACKGROUND: Previous studies evaluated the SARS-CoV-2 vaccine safety or compared adverse events following vaccination to those from infection. Limited data about the impact of prior infection on post-vaccine adverse events are available. The objective of this study was to evaluate the impact of prior SARS-CoV-2 infection on outcomes shortly after vaccination using a longitudinal design. METHODS: Nationwide, multicenter, retrospective cohort study of hospitalization, death, and pre-specified adverse event rates among Veterans who received mRNA vaccines within the Veterans Health Administration between 12/11/2020 and 8/31/2021. Daily incidence rates were compared before and after vaccine doses, stratified by history of microbiologically-confirmed SARS-CoV-2. RESULTS: 3,118,802 patients received a first dose and 2,979,326 a second, including 102,829 with a history of SARS-CoV-2 infection. Daily incident hospitalization rates were unchanged before and after the second dose among patients without previous infection (28.8/100,000 post-dose versus 28.6/100,000 pre-dose, p = 0.92). In previously-infected patients, the hospitalization rate increased above baseline one day following vaccination (158.2/100,000 after dose 2 versus 57.3/100,000 pre-dose, p < 0.001), then returned to baseline. Chart review indicated vaccine side effects, such as fever, constitutional symptoms, weakness, or falls, as the definite (39%) or possible (18%) cause of hospitalization. Affected patients had mean age 75, and 90% had at least one serious comorbidity. Hospitalizations were brief (median 2 days), with rapid return to baseline health. Worse baseline health among previously-infected patients prevented conclusions about mortality risk. CONCLUSIONS: Two-dose mRNA vaccine regimens are safe in a population with many comorbidities. Transient increased risks of hospitalization were identified among patients with prior SARS-CoV-2, absolute risk ∼1:1000. Findings support additional study regarding the optimal dosing schedule in this population. FUNDING: None.

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INTRODUCTION: Palliative care within intensive care units (ICU) benefits decision-making, symptom control, and end-of-life care. It has been shown to reduce the length of ICU stay and the use of non-beneficial and unwanted life-sustaining therapies. However, it is often initiated late or not at all. There is increasing evidence to support screening ICU patients using palliative care referral criteria or "triggers". The aim of the project was to assess the need for palliative care referral during ICU admission using "trigger" tools. METHODS: Electronic record review of cancer patients who died in or within 30 days of discharge from oncology ICU, between 2016 and 2018. Patients referred to palliative care before or during ICU admission were identified. Three sets of palliative care referral "triggers" were applied: one that is being tested locally and two internationally derived tools. The proportion of patients who met any of these triggers during their final ICU admission was calculated. RESULTS: Records of 149 patients were reviewed: median age 65 (range 20-83). Most admissions (89%) were unplanned, with the most common diagnoses being haemato-oncology (31%) and gastrointestinal (16%) cancers. Most (73%) were unknown to palliative care pre-ICU admission; 44% were referred between admission and death. The median time from referral to death was 0 day (range 0-19). On ICU admission, 97-99% warranted referral to palliative care using locally and internationally derived triggers. CONCLUSION: All "trigger" tools identified a high proportion of patients who may have warranted a palliative care referral either before or during admission to ICU. The routine use of trigger tools could help streamline referral pathways and underpin the development of an effective consultative model of palliative care within the ICU setting to enhance decision-making about appropriate treatment and patient-centred care.

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BACKGROUND: Timely identification of palliative care needs can reduce hospitalizations and improve quality of life. The Supportive & Palliative Care Indicators Tool (SPICT) identifies patients with advanced medical conditions who may need special care planning. The Rothman Index (RI) detects patients at high risk of acutely decompensating in the inpatient setting. SPICT and RI among cancer patients were utilized in this study to evaluate their potential roles in palliative care referrals. METHODS: Advanced cancer patients admitted to an institution in Baltimore, Maryland in 2019 were retrospectively reviewed. Patient demographics, length of hospital stay (LOS), palliative care referrals, RI scores, and SPICT scores were obtained. Patients were divided into SPICT positive or negative and RI > 60 or RI < 60.Unpaired t-tests and chi-square tests were utilized to determine the associations between SPICT and RI and early palliative care needs and mortality. RESULTS: 227 patients were included, with a mean age of 68 years, 63% Black, 59% female, with the majority having lung and GI malignancies. Sixty percent were SPICT +, 21% had RI < 60. SPICT + patients were more likely to have RI < 60 (p = 0.001). SPICT + and RI < 60 patients were more likely to have longer LOS, change in code status, more palliative/hospice referrals, and increased mortality (p <0.05). CONCLUSIONS: SPICT and RI are valuable tools in predicting mortality and palliative/hospice care referrals. These can also be utilized to initiate early palliative and goals of care discussions in patients with advanced cancer.

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The rate of medication errors in anaesthesia is a critical safety indicator but the methods to estimate this metric are imperfect. A number of factors that are difficult to control impact their incidence. Newer methods involving computerised records are improving retrospective and real-time monitoring of medication errors.

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OBJECTIVE: To identify existing obstetric trigger tools, evaluate their sensitivity and specificity to correctly identify women in need of care escalation, and describe clinicians' experiences of using these tools while caring for women in labor. DATA SOURCES: Iterative searches of three databases, CINAHL, PubMed, and SCOPUS, in October 2019 and June 2020 using the keywords maternal surveillance system, obstetric∗, early warning scores, early warning systems, and trigger tools. STUDY SELECTION: Primary quantitative and qualitative studies on the utility or implementation of trigger tools for women in labor that were written in English. Through the initial search, I identified 208 articles and included 11 full-text articles in this review. DATA EXTRACTION: I extracted data related to aims, population, methodology, outcomes, and key findings for each study and entered them into a matrix based on the Joanna Briggs Institute Review Guidelines. DATA SYNTHESIS: Quantitative researchers found that the sensitivity and specificity to correctly identify women in need of care escalation of tools varied and recommended that institutions should consider the burdens of false positives versus the risks of false negatives when choosing a tool for their contexts. Qualitative researchers described clinicians' experiences with the use of trigger tools and systems-level barriers to implementation, including lack of training, poor management of implementation, increased workload due to redundant charting, and belief that tools were not appropriate for women with low-risk pregnancies. Greater rates of false positives led clinicians to use trigger tools only for women with high-risk pregnancies rather than as a screening tool for all women. CONCLUSION: Trigger tools may help with early identification of worsening clinical condition, but further research is needed to refine and improve tools, as well as understand best practices for tool implementation. Systems-level factors should be considered in tool selection.

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BACKGROUND: We have designed a prospective adverse event (AE) surveillance method. We performed this study to evaluate this method's performance in several hospitals simultaneously. OBJECTIVES: To compare AE rates obtained by prospective AE surveillance in different hospitals and to evaluate measurement factors explaining observed variation. METHODS: We conducted a multicentre prospective observational study. Prospective AE surveillance was implemented for 8 weeks on the general medicine wards of five hospitals. To determine if population factors may have influenced results, we performed mixed-effects logistic regression. To determine if surveillance factors may have influenced results, we reassigned observers to different hospitals midway through surveillance period and reallocated a random sample of events to different expert review teams. RESULTS: During 3560 patient days of observation of 1159 patient encounters, we identified 356 AEs (AE risk per encounter=22%). AE risk varied between hospitals ranging from 9.9% of encounters in Hospital D to 35.8% of encounters in Hospital A. AE types and severity were similar between hospitals-the most common types were related to clinical procedures (45%), hospital-acquired infections (21%) and medications (19%). Adjusting for age and comorbid status, we observed an association between hospital and AE risk. We observed variation in observer behaviour and moderate agreement between clinical reviewers, which could have influenced the observed rate difference. CONCLUSION: This study demonstrated that it is possible to implement prospective surveillance in different settings. Such surveillance appears to be better suited to evaluating hospital safety concerns within rather than between hospitals as we could not definitively rule out whether the observed variation in AE risk was due to population or surveillance factors.

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BACKGROUND: An innovative programme to improve identification and management of chronic kidney disease (CKD) in primary care was implemented across three clinical commissioning groups (CCGs) in 2016. This included a falling estimated glomerular filtration rate (eGFR) trigger tool built from data in the electronic health record (EHR). This tool notifies GP practices of falling eGFR values. By alerting clinicians to patients with possible CKD progression the tool invites clinical review, a referral option, and written reflection on management. AIM: To identify practitioner perceptions of trigger tool use from interviews, and compare these with reflections on clinical management recorded within the tools. DESIGN AND SETTING: A qualitative analysis set in 136 practices across East London during 2016-2018. METHOD: Eight semi-structured interviews with GPs and practice staff were recorded, and thematic analysis was undertaken using framework analysis. The reflective comments recorded in the trigger tools of 1921 cases were categorised by age group, referral status, and by the drop in eGFR (>15 or >25 ml/min). RESULTS: Three themes emerged from the interviews: getting started, patient safety, and trigger tools for learning. Well-organised practices found the tool was readily embedded into workflow and expressed greater motivation for using it. The tool was seen to support patient safety, and was used for learning about CKD management, both individually and as a practice. Reflective comments from 1921 trigger tools were reviewed. These supported the theme of patient safety. The free-text data, stratified by age, challenged the expectation that younger cases, at higher risk of progressive CKD, would have higher referral rates. CONCLUSION: Building electronic trigger tools from the EHR can identify patients with a falling eGFR, prompting review of the eGFR trajectory and management plan. Interview and reflective data illustrated that practice use of the tool supports the patient safety agenda and encourages learning about CKD management.

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OBJECTIVE: The need for clinical staff to reliably identify patients with a shortened life expectancy is an obstacle to improving palliative and end-of-life care. We developed and evaluated the feasibility of an automated tool to identify patients with a high risk of death in the next year to prompt treating physicians to consider a palliative approach and reduce the identification burden faced by clinical staff. METHODS: Two-phase feasibility study conducted at two quaternary healthcare facilities in Toronto, Canada. We modified the Hospitalised-patient One-year Mortality Risk (HOMR) score, which identifies patients having an elevated 1-year mortality risk, to use only data available at the time of admission. An application prompted the admitting team when patients had an elevated mortality risk and suggested a palliative approach. The incidences of goals of care discussions and/or palliative care consultation were abstracted from medical records. RESULTS: Our model (C-statistic=0.89) was found to be similarly accurate to the original HOMR score and identified 15.8% and 12.2% of admitted patients at Sites 1 and 2, respectively. Of 400 patients included, the most common indications for admission included a frailty condition (219, 55%), chronic organ failure (91, 23%) and cancer (78, 20%). At Site 1 (integrated notification), patients with the notification were significantly more likely to have a discussion about goals of care and/or palliative care consultation (35% vs 20%, p = 0.016). At Site 2 (electronic mail), there was no significant difference (45% vs 53%, p = 0.322). CONCLUSIONS: Our application is an accurate, feasible and timely identification tool for patients at elevated risk of death in the next year and may be effective for improving palliative and end-of-life care.

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The incidence and impacts of adverse drug events (ADE) have been extensively studied, but there is an emerging focus on real-time detection systems. These can play an important role, along with systems pharmacology and population-level epidemiology, in a multipronged approach to prevent ADEs and mitigate their harm. Tailoring ADE detection systems to a particular health care setting or ADE type can improve predictive accuracy, but the added complexity reduces its wider applicability. As this approach becomes increasingly used we can imagine detection algorithms of greater complexity but also a set of algorithms encompassing the full range of health care settings and ADE types, thus creating a system that is both accurate and widely applicable.

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BACKGROUND: Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals. METHODS: We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure. RESULTS: We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics. CONCLUSION: EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.

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BACKGROUND: In hospital, staff need to routinely monitor patients to identify those who are seriously ill, so that they receive timely treatment to improve their condition. A Paediatric Early Warning System is a multi-faceted socio-technical system to detect deterioration in children, which may or may not include a track and trigger tool. It functions to monitor, detect and prompt an urgent response to signs of deterioration, with the aim of preventing morbidity and mortality. The purpose of this study is to develop an evidence-based improvement programme to optimise the effectiveness of Paediatric Early Warning Systems in different inpatient contexts, and to evaluate the feasibility and potential effectiveness of the programme in predicting deterioration and triggering timely interventions. METHODS: This study will be conducted in two district and two specialist children's hospitals. It deploys an Interrupted Time Series (ITS) design in conjunction with ethnographic cases studies with embedded process evaluation. Informed by Translational Mobilisation Theory and Normalisation Process Theory, the study is underpinned by a functions based approach to improvement. Workstream (1) will develop an evidence-based improvement programme to optimise Paediatric Early Warning System based on systematic reviews. Workstream (2) consists of observation and recording outcomes in current practice in the four sites, implementation of the improvement programme and concurrent process evaluation, and evaluation of the impact of the programme. Outcomes will be mortality and critical events, unplanned admission to Paediatric Intensive Care (PICU) or Paediatric High Dependency Unit (PHDU), cardiac arrest, respiratory arrest, medical emergencies requiring immediate assistance, reviews by PICU staff, and critical deterioration, with qualitative evidence of the impact of the intervention on Paediatric Early Warning System and learning from the implementation process. DISCUSSION: This paper presents the background, rationale and design for this mixed methods study. This will be the most comprehensive study of Paediatric Early Warning Systems and the first to deploy a functions-based approach to improvement in the UK with the aim to improve paediatric patient safety and reduce mortality. Our findings will inform recommendations about the safety processes for every hospital treating paediatric in-patients across the NHS. TRIAL REGISTRATION: Sponsor: Cardiff University, 30-36 Newport Road, Cardiff, CF24 0DE Sponsor ref.: SPON1362-14. Funder: National Institute for Health Research, Health Services & Delivery Research Programme (NIHR HS&DR) Funder reference: 12/178/17. Research Ethics Committee reference: 15/SW/0084 [13/04/2015]. PROSPERO reference: CRD42015015326 [23/01/2015]. ISRCTN: 94228292 https://doi.org/10.1186/ISRCTN94228292 [date of application 13/05/2015; date of registration: 18/08/2015]. Prospective registration prior to data collection and participant consent commencing in September 2014.

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