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Background: Over 5000 paediatric cardiac surgeries are performed in the UK each year and early survival has improved to > 98%. Objectives: We aimed to identify the surgical morbidities that present the greatest burden for patients and health services and to develop and pilot routine monitoring and feedback. Design and setting: Our multidisciplinary mixed-methods study took place over 52 months across five UK paediatric cardiac surgery centres. Participants: The participants were children aged

Objectives Given the current excellent early mortality rates for paediatric cardiac surgery, stakeholders believe that this important safety outcome should be supplemented by a wider range of measures. Our objectives were to prospectively measure the incidence of morbidities following paediatric cardiac surgery and to evaluate their clinical and health-economic impact over 6 months.Design The design was a prospective, multicentre, multidisciplinary mixed methods study.Setting The setting was 5 of the 10 paediatric cardiac surgery centres in the UK with 21 months recruitment.Participants Included were 3090 paediatric cardiac surgeries, of which 666 patients were recruited to an impact substudy.Results Families and clinicians prioritised:Acute neurological event, unplanned re-intervention, feeding problems, renal replacement therapy, major adverse events, extracorporeal life support, necrotising enterocolitis, postsurgical infection and prolonged pleural effusion or chylothorax.Among 3090 consecutive surgeries, there were 675 (21.8%) with at least one of these morbidities. Independent risk factors for morbidity included neonatal age, complex heart disease and prolonged cardiopulmonary bypass (p

Background: In 2011, we developed a risk model for 30-day mortality after children’s heart surgery. The PRAiS (Partial Risk Adjustment in Surgery) model uses data on the procedure performed, diagnosis, age, weight and comorbidity. Our treatment of comorbidity was simplistic because of data quality. Software that implements PRAiS is used by the National Congenital Heart Disease Audit (NCHDA) in its audit work. The use of PRAiS triggered the temporary suspension of surgery at one unit in 2013. The public anger that surrounded this illustrated the need for public resources around outcomes monitoring. Objectives: (1) To improve the PRAiS risk model by incorporating more information about comorbidities. (2) To develop online resources for the public to help them to understand published mortality data. Design: Objective 1 The outcome measure was death within 30 days of the start of each surgical episode of care. The analysts worked with an expert panel of clinical and data management representatives. Model development followed an iterative process of clinical discussion of risk factors, development of regression models and assessment of model performance under cross-validation. Performance was measured using the area under the receiving operator characteristic (AUROC) curve and calibration in the cross-validation test sets. The final model was further assessed in a 2014–15 validation data set. Objective 2 We developed draft website material that we iteratively tested through four sets of two workshops (one workshop for parents of children who had undergone heart surgery and one workshop for other interested users). Each workshop recruited new participants. The academic psychologists ran two sets of three experiments to explore further understanding of the web content. Data: We used pseudonymised NCHDA data from April 2009 to April 2014. We later unexpectedly received a further year of data (2014–15), which became a prospective validation set. Results: Objective 1 The cleaned 2009–14 data comprised 21,838 30-day surgical episodes, with 539 deaths. The 2014–15 data contained 4207 episodes, with 97 deaths. The final regression model included four new comorbidity groupings. Under cross-validation, the model had a median AUROC curve of 0.83 (total range 0.82 to 0.83), a median calibration slope of 0.92 (total range 0.64 to 1.25) and a median intercept of –0.23 (range –1.08 to 0.85). In the validation set, the AUROC curve was 0.86 [95% confidence interval (CI) 0.83 to 0.89], and its calibration slope and intercept were 1.01 (95% CI 0.83 to 1.18) and 0.11 (95% CI –0.45 to 0.67), respectively. We recalibrated the final model on 2009–15 data and updated the PRAiS software. Objective 2 We coproduced a website (http://childrensheartsurgery.info/) that provides interactive exploration of the data, two animations and background information. It was launched in June 2016 and was very well received. Limitations: We needed to use discharge status as a proxy for 30-day life status for the 14% of overseas patients without a NHS number. We did not have sufficient time or resources to extensively test the usability and take-up of the website following its launch. Conclusions: The project successfully achieved its stated aims. A key theme throughout has been the importance of collaboration and coproduction. In particular for aim 2, we generated a great deal of generalisable learning about how to communicate complex clinical and mathematical information. Further work: Extending our codevelopment approach to cover many other aspects of quality measurement across congenital heart disease and other specialised NHS services. Funding: The National Institute for Health Research Health Services and Delivery Research programme.

BackgroundImprovements in hospital‐based care have reduced early mortality in congenital heart disease. Later adverse outcomes may be reducible by focusing on care at or after discharge. We aimed to identify risk factors for such events within 1 year of discharge after intervention in infancy and, separately, to identify subgroups that might benefit from different forms of intervention. Methods and ResultsCardiac procedures performed in infants between 2005 and 2010 in England and Wales from the UK National Congenital Heart Disease Audit were linked to intensive care records. Among 7976 infants, 333 (4.2%) died before discharge. Of 7643 infants discharged alive, 246 (3.2%) died outside the hospital or after an unplanned readmission to intensive care (risk factors were age, weight‐for‐age, cardiac procedure, cardiac diagnosis, congenital anomaly, preprocedural clinical deterioration, prematurity, ethnicity, and duration of initial admission; c‐statistic 0.78 [0.75–0.82]). Of the 7643, 514 (6.7%) died outside the hospital or had an unplanned intensive care readmission (same risk factors but with neurodevelopmental condition and acquired cardiac diagnosis and without preprocedural deterioration; c‐statistic 0.78 [0.75–0.80]). Classification and regression tree analysis were used to identify 6 subgroups stratified by the level (3–24%) and nature of risk for death outside the hospital or unplanned intensive care readmission based on neurodevelopmental condition, cardiac diagnosis, congenital anomaly, and duration of initial admission. An additional 115 patients died after planned intensive care admission (typically following elective surgery). ConclusionsAdverse outcomes in the year after discharge are of similar magnitude to in‐hospital mortality, warrant service improvements, and are not confined to diagnostic groups currently targeted with enhanced monitoring.

Background: While early outcomes of paediatric cardiac surgery have improved, less attention has been given to later outcomes including post-discharge mortality and emergency readmissions. Objectives: Our objectives were to use a mixed-methods approach to build an evidenced-based guideline for postdischarge management of infants undergoing interventions for congenital heart disease (CHD). Methods: Systematic reviews of the literature – databases used: MEDLINE (1980 to 1 February 2013), EMBASE (1980 to 1 February 2013), Cumulative Index to Nursing and Allied Health Literature (CINAHL; 1981 to 1 February 2013), The Cochrane Library (1999 to 1 February 2013), Web of Knowledge (1980 to 1 February 2013) and PsycINFO (1980 to 1 February 2013). Analysis of audit data from the National Congenital Heart Disease Audit and Paediatric Intensive Care Audit Network databases pertaining to records of infants undergoing interventions for CHD between 1 January 2005 and 31 December 2010. Qualitative analyses of online discussion posted by 73 parents, interviews with 10 helpline staff based at user groups, interviews with 20 families whose infant either died after discharge or was readmitted urgently to intensive care, and interviews with 25 professionals from tertiary care and 13 professionals from primary and secondary care. Iterative multidisciplinary review and discussion of evidence incorporating the views of parents on suggestions for improvement. Results: Despite a wide search strategy, the studies identified for inclusion in reviews related only to patients with complex CHD, for whom adverse outcome was linked to non-white ethnicity, lower socioeconomic status, comorbidity, age, complexity and feeding difficulties. There was evidence to suggest that home monitoring programmes (HMPs) are beneficial. Of 7976 included infants, 333 (4.2%) died postoperatively, leaving 7634 infants, of whom 246 (3.2%) experienced outcome 1 (postdischarge death) and 514 (6.7%) experienced outcome 2 (postdischarge death plus emergency intensive care readmissions). Multiple logistic regression models for risk of outcomes 1 and 2 had areas under the receiver operator curve of 0.78 [95% confidence interval (CI) 0.75 to 0.82] and 0.78 (95% CI 0.75 to 0.80), respectively. Six patient groups were identified using classification and regression tree analysis to stratify by outcome 2 (range 3–24%), which were defined in terms of neurodevelopmental conditions, high-risk cardiac diagnosis (hypoplastic left heart, single ventricle or pulmonary atresia), congenital anomalies and length of stay (LOS) > 1 month. Deficiencies and national variability were noted for predischarge training and information, the process of discharge to non-specialist services including documentation, paediatric cardiology follow-up including HMP, psychosocial support post discharge and the processes for accessing help when an infant becomes unwell. Conclusions: National standardisation may improve discharge documents, training and guidance on ‘what is normal’ and ‘signs and symptoms to look for’, including how to respond. Infants with high-risk cardiac diagnoses, neurodevelopmental conditions or LOS > 1 month may benefit from discharge via their local hospital. HMP is suggested for infants with hypoplastic left heart, single ventricle or pulmonary atresia. Discussion of postdischarge deaths for infant CHD should occur at a network-based multidisciplinary meeting. Audit is required of outcomes for this stage of the patient journey. Future work: Further research may determine the optimal protocol for HMPs, evaluate the use of traffic light tools for monitoring infants post discharge and develop the analytical steps and processes required for audit of postdischarge metrics. Study registration: This study is registered as PROSPERO CRD42013003483 and CRD42013003484. Funding: The National Institute for Health Research Health Services and Delivery Research programme. The National Congenital Heart Diseases Audit (NCHDA) and Paediatric Intensive Care Audit Network (PICANet) are funded by the National Clinical Audit and Patient Outcomes Programme, administered by the Healthcare Quality Improvement Partnership (HQIP). PICAnet is also funded by Welsh Health Specialised Services Committee; NHS Lothian/National Service Division NHS Scotland, the Royal Belfast Hospital for Sick Children, National Office of Clinical Audit Ireland, and HCA International. The study was supported by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. Sonya Crowe was supported by the Health Foundation, an independent charity working to continuously improve the quality of health care in the UK.