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There has been substantial research on adult COVID-19 and how to treat it. But how do severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections afflict children? The COVID-19 pandemic has yielded many surprises, not least that children generally develop less severe disease than older adults, which is unusual for a respiratory disease. However, some children can develop serious complications from COVID-19, such as multisystem inflammatory syndrome in children (MIS-C) and Long Covid, even after mild or asymptomatic COVID-19. Why this occurs in some and not others is an important question. Moreover, when children do contract COVID-19, understanding their role in transmission, especially in schools and at home, is crucial to ensuring effective mitigation measures. Therefore, in addition to nonpharmaceutical interventions, such as improved ventilation, there is a strong case to vaccinate children so as to reduce possible long-term effects from infection and to decrease transmission. But questions remain about whether vaccination might skew immune responses to variants in the long term. As the experts discuss below, more is being learned about these important issues, but much more research is needed to understand the long-term effects of COVID-19 in children.

ObjectiveThis study assessed the transfer of patients from paediatric cardiac to adult congenital heart disease (ACHD) services in England and the factors impacting on this process.MethodsThis retrospective cohort study used a population-based linked data set (LAUNCHES QI data set: ‘Linking Audit and National datasets in Congenital Heart Services for Quality Improvement’) including all patients born between 1987 and 2000, recorded as having a congenital heart disease (CHD) procedure in childhood. Hospital Episode Statistics data identified transfer from paediatric to ACHD services between the ages of 16 and 22 years.ResultsOverall, 63.8% of a cohort of 10 298 patients transferred by their 22nd birthday. The estimated probability of transfer by age 22 was 96.5% (95% CI 95.3 to 97.7), 86.7% (95% CI 85.6 to 87.9) and 41.0% (95% CI 39.4 to 42.6) for severe, moderate and mild CHD, respectively. 166 patients (1.6%) died between 16 and 22 years; 42 of these (0.4%) died after age 16 but prior to transfer. Multivariable ORs in the moderate and severe CHD groups up to age 20 showed significantly lower likelihood of transfer among female patients (0.87, 95% CI 0.78 to 0.97), those with missing ethnicity data (0.31, 95% CI 0.18 to 0.52), those from deprived areas (0.84, 95% CI 0.72 to 0.98) and those with moderate (compared with severe) CHD (0.30, 95% CI 0.26 to 0.35). The odds of transfer were lower for the horizontal compared with the vertical care model (0.44, 95% CI 0.27 to 0.72). Patients who did not transfer had a lower probability of a further National Congenital Heart Disease Audit procedure between ages 20 and 30 compared with those who did transfer: 12.3% (95% CI 5.1 to 19.6) vs 32.5% (95% CI 28.7 to 36.3).ConclusionsMajority of patients with moderate or severe CHD in England transfer to adult services. Patients who do not transfer undergo fewer elective CHD procedures over the following decade.

Background Most children now survive cardiac surgery, and the focus of quality improvement initiatives has shifted toward more complex outcome measures. The aim of this investigation was to study the impact of early postoperative morbidities on parent-reported patient quality of life and parental anxiety or depression over 6 months. Methods This prospective case-matched cohort study was conducted in 5 UK children’s cardiac centers. Measures of impact for patient categories of “single morbidity,” “multiple morbidities,” and “extracorporeal life support (ECLS)” were compared with “no morbidity.” The measures used were the Pediatric Quality of Life Inventory (PedsQL) and the 4-item Patient Health Questionnaire (PHQ-4) at 6 weeks and 6 months postoperatively. The study modeled the outcomes using mixed effects regression, adjusting for case mix and clustering within centers. Results The study included 666 patients who underwent operation at a median age of 81 days (interquartile range, 10 to 325 days). At 6-week follow-up, significant adjusted differences to the reference group with no morbidity were found for total PedsQL scores, which were lower in patients with ECLS (P = .01), multiple morbidities (P < .001), and a single morbidity (P = .04), as well as the proportion of parents with anxiety and depression, which were higher in the group with multiple morbidities (P = .04 and P = .01, respectively). At 6 months, measures had improved in all morbidity groups. The only significant adjusted difference in the reference group was for physical PedsQL scores in ECLS (P = .04) and multiple morbidities (P < .01). Conclusions Patient and parent well-being are strongly influenced by postoperative morbidities early after surgery, with improvement by 6 months. Family psychological support and holistic rehabilitation are vital for children who experience postoperative morbidities.

Operational research is a collection of modelling techniques used to structure, analyse, and solve problems related to the design and operation of complex human systems. While many argue that operational research should play a key role in improving healthcare services, staff may be largely unaware of its potential applications. This Element explores operational research's wartime origins and introduce several approaches that operational researchers use to help healthcare organisations: address well-defined decision problems; account for multiple stakeholder perspectives; and describe how system performance may be impacted by changing the configuration or operation of services. The authors draw on examples that illustrate the valuable perspective that operational research brings to improvement initiatives and the challenges of implementing and scaling operational research solutions. They discuss how operational researchers are working to surmount these problems and suggest further research to help operational researchers have greater beneficial impact in healthcare improvement. This title is also available as Open Access on Cambridge Core.

Long-term survival is an important metric for health care evaluation, especially in functionally single-ventricle (f-SV) congenital heart disease (CHD). This study's aim was to evaluate the relationship between center volume and long-term survival in f-SV CHD within the centralized health care service of England and Wales.This was a retrospective cohort study of children born with f-SV CHD between 2000 and 2018, using the national CHD procedure registry, with survival ascertained in 2020.Of 56,039 patients, 3293 (5.9%) had f-SV CHD. Median age at first intervention was 7 days (interquartile range [IQR], 4, 27), and median follow-up time was 7.6 years (IQR, 1.0, 13.3). The largest diagnostic subcategories were hypoplastic left heart syndrome, 1276 (38.8%); tricuspid atresia, 440 (13.4%); and double-inlet left ventricle, 322 (9.8%). The survival rate at 1 year and 5 years was 76.8% (95% confidence interval [CI], 75.3%-78.2%) and 72.1% (95% CI, 70.6%-73.7%), respectively. The unadjusted hazard ratio for each 5 additional patients with f-SV starting treatment per center per year was 1.04 (95% CI, 1.02-1.06), P .001. However, after adjustment for significant risk factors (diagnostic subcategory; antenatal diagnosis; younger age, low weight, acquired comorbidity, increased severity of illness at first procedure), the hazard ratio for f-SV center volume was 1.01 (95% CI, 0.99-1.04) P = .28. There was strong evidence that patients with more complex f-SV (hypoplastic left heart syndrome, Norwood pathway) were treated at centers with greater f-SV case volume (P .001).After adjustment for case mix, there was no evidence that f-SV center volume was linked to longer-term survival in the centralized health service provided by the 10 children's cardiac centers in England and Wales.

Key messagesMathematical modelling is intrinsically difficult given the complexity of relationships between parameters and difficulty quantifying those parametersModelling needs input from a much wider range of sources including domain expertsData sharing and communication of results could be improvedPolicy makers and the public often had poor understanding of key concepts such as exponential growth and the limitations of long-term forecasting

Key messagesPandemic policy on children and schools reflected UK based scientific narratives that did not align with global scientific consensusGovernment relied on evidence that downplayed the seriousness of covid-19 in children, underestimated the benefits of precautionary measures, and overestimated the harms of vaccinationReturn to school in September 2020 with minimal emphasis on masking and air quality, and inadequate support for isolation may have accelerated community transmissionThe public inquiry should explore why the UK was an international outlier in its approach to protecting children and making schools and communities safer

Since 1997, special paediatric intensive care retrieval teams (PICRTs) based in 11 locations across England and Wales have been used to transport sick children from district general hospitals to one of 24 paediatric intensive care units. We develop a location allocation optimisation framework to help inform decisions on the optimal number of locations for each PICRT, where those locations should be, which local hospital each location serves and how many teams should station each location. Our framework allows for stochastic journey times, differential weights for each journey leg and incorporates queuing theory by considering the time spent waiting for a PICRT to become available. We examine the average waiting time and the average time to bedside under different number of operational PICRT stations, different number of teams per station and different levels of demand. We show that consolidating the teams into fewer stations for higher availability leads to better performance.

ObjectivesTo link five national data sets (three registries, two administrative) and create longitudinal healthcare trajectories for patients with congenital heart disease (CHD), describing the quality and the summary statistics of the linked data set.DesignBespoke linkage of record-level patient identifiers across five national data sets. Generation of spells of care defined as periods of time-overlapping events across the data sets.SettingNational Congenital Heart Disease Audit (NCHDA) procedures in public (National Health Service; NHS) hospitals in England and Wales, paediatric and adult intensive care data sets (Paediatric Intensive Care Audit Network; PICANet and the Case Mix Programme from the Intensive Care National Audit & Research Centre; ICNARC-CMP), administrative hospital episodes (hospital episode statistics; HES inpatient, outpatient, accident and emergency; A&E) and mortality registry data.ParticipantsPatients with any CHD procedure recorded in NCHDA between April 2000 and March 2017 from public hospitals.Primary and secondary outcome measuresPrimary: number of linked records, number of unique patients and number of generated spells of care. Secondary: quality and completeness of linkage.ResultsThere were 143 862 records in NCHDA relating to 96 041 unique patients. We identified 65 797 linked PICANet patient admissions, 4664 linked ICNARC-CMP admissions and over 6 million linked HES episodes of care (1.1M inpatient, 4.7M outpatient). The linked data set had 4 908 153 spells of care after quality checks, with a median (IQR) of 3.4 (1.8–6.3) spells per patient-year. Where linkage was feasible (in terms of year and centre), 95.6% surgical procedure records were linked to a corresponding HES record, 93.9% paediatric (cardiac) surgery procedure records to a corresponding PICANet admission and 76.8% adult surgery procedure records to a corresponding ICNARC-CMP record.ConclusionsWe successfully linked four national data sets to the core data set of all CHD procedures performed between 2000 and 2017. This will enable a much richer analysis of longitudinal patient journeys and outcomes. We hope that our detailed description of the linkage process will be useful to others looking to link national data sets to address important research priorities.

Short-term survival after paediatric cardiac surgery has improved significantly over the past 20 years and increasing attention is being given to measuring and reducing incidence of morbidities following surgery. How to best use routinely collected data to share morbidity information constitutes a challenge for clinical teams interested in analysing their outcomes for quality improvement. We aimed to develop a tool facilitating this process in the context of monitoring morbidities following paediatric cardiac surgery, as part of a prospective multi-centre research study in the United Kingdom.We developed a prototype software tool to analyse and present data about morbidities associated with cardiac surgery in children. We used an iterative process, involving engagement with potential users, tool design and implementation, and feedback collection. Graphical data displays were based on the use of icons and graphs designed in collaboration with clinicians.Our tool enables automatic creation of graphical summaries, displayed as a Microsoft PowerPoint presentation, from a spreadsheet containing patient-level data about specified cardiac surgery morbidities. Data summaries include numbers/percentages of cases with morbidities reported, co-occurrences of different morbidities, and time series of each complication over a time window.Our work was characterised by a very high level of interaction with potential users of the tool, enabling us to promptly account for feedback and suggestions from clinicians and data managers. The United Kingdom centres involved in the project received the tool positively, and several expressed their interest in using it as part of their routine practice.

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

BackgroundUpdatable understanding of the onset and progression of individuals COVID-19 trajectories underpins pandemic mitigation efforts. In order to identify and characterize individual trajectories, we defined and validated ten COVID-19 phenotypes from linked electronic health records (EHR) on a nationwide scale using an extensible framework.MethodsCohort study of 56.6 million people in England alive on 23/01/2020, followed until 31/05/2021, using eight linked national datasets spanning COVID-19 testing, vaccination, primary & secondary care and death registrations data. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity using a combination of international clinical terminologies (e.g. SNOMED-CT, ICD-10) and bespoke data fields; positive test, primary care diagnosis, hospitalisation, critical care (four phenotypes), and death (three phenotypes). Using these phenotypes, we constructed patient trajectories illustrating the transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsWe identified 3,469,528 infected individuals (6.1%) with 8,825,738 recorded COVID-19 phenotypes. Of these, 364,260 (11%) were hospitalised and 140,908 (4%) died. Of those hospitalised, 38,072 (10%) were admitted to intensive care (ICU), 54,026 (15%) received non-invasive ventilation and 21,404 (6%) invasive ventilation. Amongst hospitalised patients, first wave mortality (30%) was higher than the second (23%) in non-ICU settings, but remained unchanged for ICU patients. The highest mortality was for patients receiving critical care outside of ICU in wave 1 (51%). 13,083 (9%) COVID-19 related deaths occurred without diagnoses on the death certificate, but within 30 days of a positive test while 10,403 (7%) of cases were identified from mortality data alone with no prior phenotypes recorded. We observed longer patient trajectories in the second pandemic wave compared to the first.InterpretationOur analyses illustrate the wide spectrum of severity that COVID-19 displays and significant differences in incidence, survival and pathways across pandemic waves. We provide an adaptable framework to answer questions of clinical and policy relevance; new variant impact, booster dose efficacy and a way of maximising existing data to understand individuals progression through disease states.Research in ContextEvidence before the studyWe searched PubMed on October 14, 2021, for publications with the terms “COVID-19” or “SARS-CoV-2”, “severity”, and “electronic health records” or “EHR” without date or language restrictions. Multiple studies explore factors associated with severity of COVID-19 infection, and model predictions of outcome for hospitalised patients. However, most work to date focused on isolated facets of the healthcare system, such as primary or secondary care only, was conducted in subpopulations (e.g. hospitalised patients) of limited sample size, and often utilized dichotomised outcomes (e.g. mortality or hospitalisation) ignoring the full spectrum of disease. We identified no studies which comprehensively detailed severity of infections while describing disease severity across pandemic waves, vaccination status, and patient trajectories.Added value of this studyTo our knowledge, this is the first study providing a comprehensive view of COVID-19 across pandemic waves using national data and focusing on severity, vaccination, and patient trajectories. Drawing on linked electronic health record (EHR) data on a national scale (56.6 million people alive and registered with GP in England), we describe key demographic factors, frequency of comorbidities, impact of the two main waves in England, and effect of full vaccination on COVID-19 severities. Additionally, we identify and describe patient trajectory networks which illustrate the main transition pathways of COVID-19 patients in the healthcare system. Finally, we provide reproducible COVID-19 phenotyping algorithms reflecting clinically relevant stages of disease severity i.e. positive tests, primary care diagnoses, hospitalisation, critical care treatments (e.g. ventilatory support) and mortality.Implications of all the available evidenceThe COVID-19 phenotypes and trajectory analysis framework outlined produce a reproducible, extensible and repurposable means to generate national-scale data to support critical policy decision making. By modelling patient trajectories as a series of interactions with healthcare systems, and linking these to demographic and outcome data, we provide a means to identify and prioritise care pathways associated with adverse outcomes and highlight healthcare system ‘touch points’ which may act as tangible targets for intervention.

Objective To offer a quantitative risk–benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England. Setting England. Design Following the risk–benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12–17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence. Participants All 12–17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre. Main outcome measures Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12–17 year olds in England over a 16-week period under different estimates of future case incidence. Results At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date. Conclusions Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10–19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.

With high levels of the Delta variant of COVID-19 circulating in England during September 2021, schools are set to reopen with few school-based non-pharmaceutical interventions (NPIs). In this paper, we present simulation results obtained from the individual-based model, JUNE, for English school opening after a prior vaccination campaign using an optimistic set of assumptions about vaccine efficacy and the likelihood of prior-reinfection. We take a scenario-based approach to modelling potential interventions to assess relative changes rather than real-world forecasts. Specifically, we assess the effects of vaccinating those aged 16-17, those aged 12-17, and not vaccinating children at all relative to only vaccinating the adult population, addressing what might have happened had the UK began teenage vaccinations earlier. Vaccinating children in the 12-15 age group would have had a significant impact on the course of the epidemic, saving thousands of lives overall in these simulations. In the absence of such a vaccination campaign our simulations show there could still be a significant positive impact on the epidemic (fewer cases, fewer deaths) by continuing NPI strategies in schools. Our analysis suggests that the best results in terms of lives saved are likely derived from a combination of the now planned vaccination campaign and NPIs in schools.

With high levels of the Delta variant of COVID-19 circulating in England during September 2021, schools are set to reopen with few school-based non-pharmaceutical interventions (NPIs). In this paper, we present simulation results obtained from the individual-based model, June, for English school opening after a prior vaccination campaign using an optimistic set of assumptions about vaccine efficacy and the likelihood of prior-reinfection. We take a scenario-based approach to modelling potential interventions to assess relative changes rather than real-world forecasts. Specifically, we assess the effects of vaccinating those aged 16-17, those aged 12-17, and not vaccinating children at all relative to only vaccinating the adult population, addressing what might have happened had the UK began teenage vaccinations earlier. Vaccinating children in the 12-15 age group would have had a significant impact on the course of the epidemic, saving thousands of lives overall in these simulations. In the absence of such a vaccination campaign our simulations show there could still be a significant positive impact on the epidemic (fewer cases, fewer deaths) by continuing NPI strategies in schools. Our analysis suggests that the best results in terms of lives saved are likely derived from a combination of the now planned vaccination campaign and NPIs in schools.

ObjectivesGlobally, healthcare systems have been stretched to the limit by the COVID-19 pandemic. Significant changes have had to be made to the way in which non-COVID-19-related care has been delivered. Our objective was to understand, from the perspective of patients with a chronic, life-long condition (congenital heart disease, CHD) and their parents/carers, the impact of COVID-19 on the delivery of care, how changes were communicated and whether healthcare providers should do anything differently in a subsequent wave of COVID-19 infections.Design and settingQualitative study involving a series of asynchronous discussion forums set up and moderated by three patient charities via their Facebook pages.ParticipantsPatients with CHD and parents/carers of patients with CHD.Main outcome measuresQualitative responses to questions posted on the discussion forums.ResultsThe forums ran over a 6-week period and involved 109 participants. Following thematic analysis, we identified three themes and 10 subthemes related to individual condition-related factors, patient-related factors and health professional/centre factors that may have influenced how patients and parents/carers experienced changes to service delivery as a result of COVID-19. Specifically, respondents reported high levels of disruption to the delivery of care, inconsistent advice and messaging and variable communication from health professionals, with examples of both excellent and very poor experiences of care reported. Uncertainty about follow-up and factors related to the complexity and stability of their condition contributed to anxiety and stress.ConclusionsThe importance of clear, consistent communication cannot be over-estimated. Our findings, while collected in relation to patients with CHD, are not necessarily specific to this population and we believe that they reflect the experiences of many thousands of people with life-long conditions in the UK. Recommendations related to communication, service delivery and support during the pandemic may improve patients’ experience of care and, potentially, their outcomes.

BackgroundWe can improve healthcare services by better understanding current provision. One way to understand this is by linking data sets from clinical and national audits, national registries and other National Health Service (NHS) encounter data. However, getting to the point of having linked national data sets is challenging.ObjectiveWe describe our experience of the data application and linkage process for our study ‘LAUNCHES QI’, and the time, processes and resource requirements involved. To help others planning similar projects, we highlight challenges encountered and advice for applications in the current system as well as suggestions for system improvements.FindingsThe study set up for LAUNCHES QI began in March 2018, and the process through to data acquisition took 2.5 years. Several challenges were encountered, including the amount of information required (often duplicate information in different formats across applications), lack of clarity on processes, resource constraints that limit an audit’s capacity to fulfil requests and the unexpected amount of time required from the study team. It is incredibly difficult to estimate the resources needed ahead of time, and yet necessary to do so as early on as funding applications. Early decisions can have a significant impact during latter stages and be hard to change, yet it is difficult to get specific information at the beginning of the process.ConclusionsThe current system is incredibly complex, arduous and slow, stifling innovation and delaying scientific progress. NHS data can inform and improve health services and we believe there is an ethical responsibility to use it to do so. Streamlining the number of applications required for accessing data for health services research and providing clarity to data controllers could facilitate the maintenance of stringent governance, while accelerating scientific studies and progress, leading to swifter application of findings and improvements in healthcare.

Background Centralisation of paediatric intensive care units (PICUs) has the increased the need for specialist paediatric critical care transport teams (PCCT) to transport critically ill children to PICU. We investigated the impact of care provided by PCCTs for children on mortality and other clinically important outcomes. Methods We analysed linked national data from the Paediatric Intensive Care Audit Network (PICANet) from children admitted to PICUs in England and Wales (2014–2016) to assess the impact of who led the child’s transport, whether prolonged stabilisation by the PCCT was detrimental and the impact of critical incidents during transport on patient outcome. We used logistic regression models to estimate the adjusted odds and probability of mortality within 30 days of admission to PICU (primary outcome) and negative binomial models to investigate length of stay (LOS) and length of invasive ventilation (LOV). Results The study included 9112 children transported to PICU. The most common diagnosis was respiratory problems; junior doctors led the PCCT in just over half of all transports; and the 30-day mortality was 7.1%. Transports led by Advanced Nurse Practitioners and Junior Doctors had similar outcomes (adjusted mortality ANP: 0.035 versus Junior Doctor: 0.038). Prolonged stabilisation by the PCCT was possibly associated with increased mortality (0.059, 95% CI: 0.040 to 0.079 versus short stabilisation 0.044, 95% CI: 0.039 to 0.048). Critical incidents involving the child increased the adjusted odds of mortality within 30 days (odds ratio: 3.07). Conclusions Variations in team composition between PCCTs appear to have little effect on patient outcomes. We believe differences in stabilisation approaches are due to residual confounding. Our finding that critical incidents were associated with worse outcomes indicates that safety during critical care transport is an important area for future quality improvement work.

[First paragraph] Following centralisation of paediatric intensive care in England and Wales, nearly 5000 critically ill children are transported from local hospitals to paediatric intensive care units (PICUs) annually. The majority of transports are performed by ten regionally based paediatric critical care transport teams (PCCTs) [1]. As arrival of the PCCT represents the first interaction these children have with specialist paediatric critical care, a key standard set by the national Paediatric Intensive Care Society (PICS) [2] is that a PCCT should arrive at the child’s bedside within three hours of agreeing they require PICU admission (referred to as ‘time-to-bedside’).

In order of first author surname

ObjectiveGiven the paucity of long-term outcome data for complex congenital heart disease (CHD), we aimed to describe the treatment pathways and survival for patients who started interventions for functionally univentricular heart (FUH) conditions, excluding hypoplastic left heart syndrome.MethodsWe performed a retrospective cohort study using all procedure records from the National Congenital Heart Diseases Audit for children born in 2000–2018. The primary outcome was mortality, ascertained from the Office for National Statistics in 2020.ResultsOf 53 615 patients, 1557 had FUH: 55.9% were boys and 67.4% were of White ethnic groups. The largest diagnostic categories were tricuspid atresia (28.9%), double inlet left ventricle (21.0%) and unbalanced atrioventricular septal defect (AVSD) (15.2%). The ages at staged surgery were: initial palliation 11.5 (IQR 5.5–43.5) days, cavopulmonary shunt 9.2 (IQR 6.0–17.1) months and Fontan 56.2 (IQR 45.5–70.3) months. The median follow-up time was 10.8 (IQR 7.0–14.9) years and the 1, 5 and 10-year survival rates after initial palliation were 83.6% (95% CI 81.7% to 85.4%), 79.4% (95% CI 77.3% to 81.4%) and 77.2% (95% CI 75.0% to 79.2%), respectively. Higher hazards were present for unbalanced AVSD HR 2.75 (95% CI 1.82 to 4.17), atrial isomerism HR 1.75 (95% CI 1.14 to 2.70) and low weight HR 1.65 (95% CI 1.13 to 2.41), critical illness HR 2.30 (95% CI 1.67 to 3.18) or acquired comorbidities HR 2.71 (95% CI 1.82 to 4.04) at initial palliation.ConclusionAlthough treatment pathways for FUH are complex and variable, nearly 8 out of 10 children survived to 10 years. Longer-term analyses of outcome based on diagnosis (rather than procedure) can inform parents, patients and clinicians, driving practice improvements for complex CHD.

BACKGROUND A third of children admitted to paediatric intensive care units (PICUs) in the United Kingdom (UK) are transported by paediatric critical care transport services (PCCTs). Parents have described the transfer journey as particularly stressful. Critical care nurses have a key role in mitigating the impact of the journey on parents. Evaluating parents' experiences is important to inform service improvements. AIM AND OBJECTIVES Our aim was to describe the development of a new measure of parents' experiences of PCCTs, derived from data collected in the Differences in access to Emergency Paediatric Intensive Care and care during Transport (DEPICT) study. DESIGN A descriptive cross-sectional survey was used. METHODS As part of the DEPICT study, a 17-item transport experience questionnaire was developed and given to parents of children transported by PCCTs to 24 UK PICUs during a 12-month period. Analyses included exploratory factor analysis and a validation review by a PCCT stakeholder group. RESULTS Families of 1722 children (1798 journeys) completed questionnaires. Five items were excluded from further analysis as correlation coefficients were

Recovery from the pandemic will be as challenging as the pandemic itself, argue Christina Pagel and Edward Palmer

ObjectivesGlobally, health care systems have been stretched to the limit by the COVID-19 pandemic. Significant changes have had to be made to the way in which non-COVID-19 related care has been delivered. Our objective was to understand, from the perspective of patients with a chronic, life-long condition (congenital heart disease, CHD) and their parents/carers, the impact of COVID-19 on the delivery of care, how changes were communicated and whether health care providers should do anything differently in a subsequent wave of COVID-19 infections.Design and settingA series of asynchronous discussion forums set up and moderated by three patient charities via their Facebook pages.ParticipantsPatients with CHD and parents/carers of patients with CHD.Main outcome measuresQualitative responses to questions posted on the discussion forums.ResultsThe forums ran over a 6-week period and involved 111 participants. Following thematic analysis of the transcripts, we identified three themes and ten subthemes related to individual condition-related factors, patient-related factors and health professional/centre factors that may have influenced how patients and parents/carers experienced changes to service delivery as a result of COVID-19.ConclusionsOur findings, whilst collected in relation to patients with CHD, are not necessarily specific to this population and we believe reflect the experiences of many thousands of people with life-long conditions in the UK. Drawing on what participants told us in the discussion forums, we have developed recommendations related to communication, service delivery and support during the pandemic that would, we think, improve patients’ experience of care and, potentially, their outcomes. Although the data were collected specifically in relation to COVID-19, a number of these recommendations are relevant to the wider delivery of care to patients with chronic underlying health conditions and reflect principles of good communication and service delivery.