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Overcrowding affects hospital emergency departments (ED) worldwide. Most OR studies addressing overcrowding develop bespoke models to explore potential improvements but ignore the organisational context in which they would be implemented, and few influence practice. There is interest in whether reusable models, for ED crowding and in healthcare generally, could have more impact. We developed a configurable approach for tackling ED overcrowding. A reusable queuing model for exploring drivers of ED performance was augmented by a qualitative approach for exploring the implementation context and a generic framework for assessing the likely compatibility of interventions with a given organisation. At the hospital where the approach was developed it directly informed strategy. We describe reuse of the approach at three hospitals. One project was completed and well-received by hospital management, two were terminated partway when data problems surfaced. The primary contribution of this work is its novelty in considering, alongside quantitative modelling, evidence-based interventions to overcrowding and qualitative assessment of a hospital’s aptitude and capability to adopt different interventions. A secondary contribution is to further the debate on model reuse, particularly by introducing more complex, modelling-centred approaches that acknowledge how models must relate to tangible interventions with reasonable prospects of being adopted locally.

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.

Large-scale immunisation programmes against seasonal influenza are characterised by logistical challenges related to the need for vaccinating large cohorts of people in a short amount of time. Careful operational planning of resources is essential for a successful implementation of such programmes. We focused on the process of child vaccination in schools and analysed the staffing and workflow aspects of a school-aged children vaccination programme in England. Our objectives were to document vaccination processes and analyse times and costs associated with different models deployed across England. We collected data through direct non-participatory observations. Statistical data analysis enabled us to identify potential factors influencing vaccine delivery time and informed the development of a tool to simulate vaccination sessions. Using this tool, we carried out scenario analyses and explored trade-offs between session times and costs in different settings. Our work ultimately supported the local implementation of school-based vaccination.

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.

Little consideration is given to the operational reality of implementing national policy at local scale. Using a case study from Norway, we examine how simple mathematical models may offer powerful insights to policy makers when planning policies. Our case study refers to a national initiative requiring Norwegian municipalities to establish acute community beds (municipal acute units or MAUs) to avoid hospital admissions. We use Erlang loss queueing models to estimate the total number of MAU beds required nationally to achieve the original policy aim. We demonstrate the effect of unit size and patient demand on anticipated utilisation. The results of our model imply that both the average demand for beds and the current number of MAU beds would have to be increased by 34% to achieve the original policy goal of transferring 240 000 patient days to MAUs. Increasing average demand or bed capacity alone would be insufficient to reach the policy goal. Day-to-day variation and uncertainty in the numbers of patients arriving or leaving the system can profoundly affect health service delivery at the local level. Health policy makers need to account for these effects when estimating capacity implications of policy. We demonstrate how a simple, easily reproducible, mathematical model could assist policy makers in understanding the impact of national policy implemented at the local level.

Background In the UK, the childhood immunisation programme is given in the first 5 years of life and protects against 12 vaccine-preventable diseases. Recently, this programme has undergone changes with addition of vaccination against Meningitis B from September 2015 and the removal of the primary dose of protection against Meningitis C from July 2016. These hanges have direct impact on the associated diseases but in addition may induce indirect effects on the vaccines that are given simultaneously or later in the programme. In this work, we developed a novel formal method to evaluate the impact of vaccination changes to one aspect of the programme across an entire vaccine programme. Methods Firstly, we combined transmission modelling (for four diseases) and historic data synthesis (for eight diseases) to project, for each disease, the disease burden at different levels of effective coverage against the associated disease. Secondly, we used a simulation model to determine the vector of effective coverage against each disease under three variations of the current childhood schedule. Combining these, we calculated the vector of disease burden across the programme under different scenarios, and assessed the direct and indirect effects of the schedule changes. Results Through illustrative application of our novel framework to three scenarios of the current childhood immunisation programme in the UK, we demonstrated the feasibility of this unifying approach. For each disease in the programme, we successfully quantified the residual disease burden due to the change. For some diseases, the change was indirectly beneficial and reduced the burden, whereas for others the effect was adverse and the change increased the disease burden. Conclusions Our results demonstrate the potential benefit of considering the programme-wide impact of changes to an immunisation schedule, and our framework is an important step in the development of a means for systematically doing so.

The concept of knowledge co-production is used in health services research to describe partnerships (which can involve researchers, practitioners, managers, commissioners or service users) with the purpose of creating, sharing and negotiating different knowledge types used to make improvements in health services. Several knowledge co-production models have been proposed to date, some involving intermediary roles. This paper explores one such model, researchers-in-residence (also known as ‘embedded researchers’).In this model, researchers work inside healthcare organisations, operating as staff members while also maintaining an affiliation with academic institutions. As part of the local team, researchers negotiate the meaning and use of research-based knowledge to co-produce knowledge, which is sensitive to the local context. Even though this model is spreading and appears to have potential for using co-produced knowledge to make changes in practice, a number of challenges with its use are emerging. These include challenges experienced by the researchers in embedding themselves within the practice environment, preserving a clear focus within their host organisations and maintaining academic professional identity.In this paper, we provide an exploration of these challenges by examining three independent case studies implemented in the UK, each of which attempted to co-produce relevant research projects to improve the quality of care. We explore how these played out in practice and the strategies used by the researchers-in-residence to address them. In describing and analysing these strategies, we hope that participatory approaches to knowledge co-production can be used more effectively in the future.

Accidents involving release of chemical, biological, radiological or nuclear substances may prompt the need to decontaminate exposed casualties prior to further medical treatment. Health service workers who carry out decontamination procedures wear protective suits to avoid direct contact with contaminants. We developed an analytical framework based on queueing theory to inform UK Department of Health’s decisions on the stock of protective suits that ambulance services and hospitals with emergency departments in England should hold. Our aim was to ensure that such allocation gave an accepted degree of resilience to locally identified hazards. Here we give an overview of our work and describe how we incorporated information in the public domain about local hazards with expert opinion about the patterns of demand for decontamination associated with different types of incident. We also give an account of how we worked with decision makers to inform national guidance on this topic.

ObjectiveTo describe the long-term outcomes, treatment pathways and risk factors for patients diagnosed with hypoplastic left heart syndrome (HLHS) in England and Wales.MethodsThe UK’s national audit database captures every procedure undertaken for congenital heart disease and updated life status for resident patients in England and Wales. Patients with HLHS born between 2000 and 2015 were identified using codes from the International Paediatric and Congenital Cardiac Code.ResultsThere were 976 patients with HLHS. Of these, 9.6% had a prepathway intervention, 89.5% underwent a traditional pathway of staged palliation and 6.4% of infants underwent a hybrid pathway. Patients undergoing prepathway procedures or the hybrid pathway were more complex, exhibiting higher rates of prematurity and acquired comorbidity. Prepathway intervention was associated with the highest in-hospital mortality (34.0%).44.6% of patients had an off-pathway procedure after their primary procedure, most frequently stenting or dilation of residual or recoarctation and most commonly occurring between stage 1 and stage 2.The survival rate at 1 year and 5 years was 60.7% (95% CI 57.5 to 63.7) and 56.3% (95% CI 53.0 to 59.5), respectively. Patients with an antenatal diagnosis (multivariable HR (MHR) 1.63 (95% CI 1.12 to 2.38)), low weight (ConclusionTreatment pathways among patients with HLHS are complex and variable. It is essential that the long-term outcomes of conditions like HLHS that require serial interventions are studied to provide a fuller picture and to inform quality assurance and improvement.

Existing modelling work on preparedness to pandemic influenza has focused on evaluating specific countermeasures for pandemics with specific characteristics (typically based on historical instances). The aim of this study was to inform policy on preparedness planning for pandemic influenza based on the assessment of a wide range of scenarios and free from restrictive assumptions about timing and features of the next pandemic.We carried out epidemiological modelling and health economic analysis of an extensive set of scenarios, each comprising a combination of pandemic, vaccine and immunisation programme characteristics in presence or absence of access to effective antivirals. Preparedness policies that incorporate mass immunisation were evaluated on the basis of there being a given chance of a pandemic each year. To support understanding and exploration of model output, an interactive visualisation tool was devised and made available online.We evaluated over 29 million combinations of pandemic and policy characteristics. Preparedness plans incorporating mass immunisation show positive net present value for a wide range of pandemic scenarios, predominantly in the absence of effective antivirals. Plans based on the responsive purchase of vaccine have greater benefit than plans reliant on the purchase and maintenance of a stockpile if immunisation can start without extensive delays. This finding is not dependent on responsively purchased vaccine being more effective than stockpiled vaccine, but rather is driven by avoiding the costs of storing and replenishing a stockpile.While emerging technologies for rapid vaccine development and production increase the prospects for mass immunisation to be an effective countermeasure, policies based on the responsive purchase of vaccine not tailored to the pandemic should be explored. Focus is also required on the pandemic intelligence, decision, contractual and logistical processes on which timely commencement of immunisation in a pandemic is reliant.

Variability in demand for staffed beds from existing patients and new referrals in intensive care units presents a substantial problem to managers. Short term fluctuations in the number of patients requiring a bed can result in demand for beds exceeding capacity, or alternatively, seemingly inefficient use of an expensive resource. While operational research methods can help in capacity planning, there are many barriers to implementing such methods in practice. In this paper we describe an entire operational research project cycle. This included: deriving exact expressions for the probability distribution for the time-varying bed demand on an intensive care unit taking account of occupancy at the point of forecast and future planned and emergency admissions; applying these expressions to a specific hospital’s intensive care unit using historical data; building software that the hospital staff can use daily to produce forecasts of short term bed demand; implementing the software within the hospital; and an evaluation of this implementation from both a technical and non-technical perspective. The main contribution of this paper is in describing the process of implementing an abstract mathematical model in a busy intensive care unit and the independent qualitative evaluation of the work about how potential barriers to implementation were addressed as part of a “modellers in residence” programme that led to us building a software tool that is still being used by the hospital more than 4 years after initial implementation. In particular, we draw together lessons from our work that we think will benefit other operational researchers wanting to work effectively with health care organisations on similar problems.

Highlights • This as a unifying method to calculate the net-benefit of different preparedness policies against different pandemic influeunza strains. • We adaptated of an existing transmission model for seasonal influenza to project the impact of different interventions against different influenza strains • In collaboration with colleagues at the UK Department of Health and Social Care, we developed a corresponding economic model. • We can combine the results from 1 to 2 to showcase the net-benefit projections across a large number of scenarios., • Our work presents a unifying method to calculate the net-benefit of different preparedness policies against different pandemic influeunza strains. Unlike previous methods, which have focused on evaluating specific strategies against specific pandemics, our method allows assessment of mass immunisation strategies in presence and absence of antiviral drugs for a large range of pandemic influenza strain characteristics and programme features. Overall, the model described here combines two parts to evaluate different preparedness planning policies against pandemic influenza. • The first part is adaptation of an existing transmission model for seasonal influenza to include generalisation across large number of pandemic influenza scenarios. • The second part is development of a tailor-made health economic model devised in collaboration with colleagues at the UK Department of Health and Social Care., Graphical abstract Image, graphical abstract

BackgroundMorbidity is defined as a state of being unhealthy or of experiencing an aspect of health that is “generally bad for you”, and postoperative morbidity linked to paediatric cardiac surgery encompasses a range of conditions that may impact the patient and are potential targets for quality assurance.MethodsAs part of a wider study, a multi-disciplinary group of professionals aimed to define a list of morbidities linked to paediatric cardiac surgery that was prioritised by a panel reflecting the views of both professionals from a range of disciplines and settings as well as parents and patients.ResultsWe present a set of definitions of morbidity for use in routine audit after paediatric cardiac surgery. These morbidities are ranked in priority order as acute neurological event, unplanned re-operation, feeding problems, the need for renal support, major adverse cardiac events or never events, extracorporeal life support, necrotising enterocolitis, surgical site of blood stream infection, and prolonged pleural effusion or chylothorax. It is recognised that more than one such morbidity may arise in the same patient and these are referred to as multiple morbidities, except in the case of extracorporeal life support, which is a stand-alone constellation of morbidity.ConclusionsIt is feasible to define a range of paediatric cardiac surgical morbidities for use in routine audit that reflects the priorities of both professionals and parents. The impact of these morbidities on the patient and family will be explored prospectively as part of a wider ongoing, multi-centre study.

Among congenital heart diseases, none has undergone a more drastic change in diagnostic approach, management, and outcomes over the last 30 years than hypoplastic left heart syndrome (HLHS), with comfort care replaced as the predominant form of management by a palliative surgical treatment pathway.1 The outcomes of palliative procedures for HLHS have been well documented, but the longer-term picture is less clear. The UK National Congenital Heart Diseases Audit (NCHDA) captures every procedure undertaken for congenital heart disease and updated life status for patients resident in England and Wales from death certifications. From this data set, we identified patients born between 2000 and 2015 who fulfilled the criteria for HLHS: a small left ventricle, stenosis or atresia of the left-sided heart valves, normally aligned great arteries, and no common atrioventricular junction.2 All patients with HLHS require surgical palliation with a traditional Norwood or hybrid pathway or heart transplantation to survive. Hence, we were able to use procedure information in combination with diagnostic information to identify patients with HLHS within the NCHDA data set using the International Paediatric and Congenital Cardiac Codes. Because the NCHDA is a procedure-based data set, patients with HLHS who did not undergo any interventional treatment are not included. Because the hybrid procedure was introduced in the United Kingdom in 2006, we considered 2 eras for …

In the event of a novel influenza strain that is markedly different to the current strains circulating in humans, the population have little/no immunity and infection spreads quickly causing a global pandemic. Over the past century, there have been four major influenza pandemics: the 1918 pandemic ("Spanish Flu"), the 1957-58 pandemic (the "Asian Flu"), the 1967-68 pandemic (the "Hong Kong Flu") and the 2009 pandemic (the "Swine flu"). To inform planning against future pandemics, this paper investigates how different is the net-present value of employing pre-purchase and responsive- purchased vaccine programmes in presence and absence of anti-viral drugs to scenarios that resemble these historic influenza pandemics. Using the existing literature and in discussions with policy decision makers in the UK, we first characterised the four past influenza pandemics by their transmissibility and infection-severity. For these combinations of parameters, we then projected the net-present value of employing pre-purchase vaccine (PPV) and responsive-purchase vaccine (RPV) programmes in presence and absence of anti-viral drugs. To differentiate between PPV and RPV policies, we changed the vaccine effectiveness value and the time to when the vaccine is first available. Our results are "heat-map" graphs displaying the benefits of different strategies in pandemic scenarios that resemble historic influenza pandemics. Our results suggest that immunisation with either PPV or RPV in presence of a stockpile of effective antiviral drugs, does not have positive net-present value for all of the pandemic scenarios considered. In contrast, in the absence of effective antivirals, both PPV and RPV policies have positive net-present value across all the pandemic scenarios. Moreover, in all considered circumstances, vaccination was most beneficial if started sufficiently early and covered sufficiently large number of people. When comparing the two vaccine programmes, the RPV policy allowed a longer timeframe and lower coverage to attain the same benefit as the PPV policy. Our findings suggest that responsive-purchase vaccination policy has a bigger window of positive net-present value when employed against each of the historic influenza pandemic strains but needs to be rapidly available to maximise benefit. This is important for future planning as it suggests that future preparedness policies may wish to consider utilising timely (i.e. responsive-purchased) vaccines against emerging influenza pandemics.

Given excellent 30-day survival for pediatric cardiac surgery, other outcome measures are important. We aimed to study important early postoperative morbidities selected by stakeholders following a rigorous and evidenced-based process, with a view to identifying potential risk factors.The incidence of selected morbidities was prospectively measured for 3090 consecutive pediatric cardiac surgical admissions in 5 UK centers between October 2015 and June 2017. The relationship between the candidate risk factors and the incidence of morbidities was explored using multiple regressions. Patient survival, a secondary outcome, was checked at 6 months.A total of 675 (21.8%) procedure episodes led to at least 1 of the following: acute neurologic event, unplanned reoperation, feeding problems, renal replacement therapy, major adverse events, extracorporeal life support, necrotizing enterocolitis, surgical infection, or prolonged pleural effusion. The highest adjusted odds ratio of morbidity was in neonates compared with children, 5.26 (95% confidence interval, 3.90-7.06), and complex heart diseases (eg, hypoplastic left heart), 2.14 (95% confidence interval, 1.41-3.24) compared with low complexity (eg, atrial septal defect, P .001 for all). Patients with any selected morbidity had a 6-month survival of 88.2% (95% confidence interval, 85.4-90.6) compared with 99.3% (95% confidence interval, 98.9-99.6) with no defined morbidity (P .001).Evaluation of postoperative morbidity provides important information over and above 30-day survival and should become a focus for audit and quality improvement. Our results have been used to initiate UK-based audit for 5 of these 9 morbidities, co-develop software for local monitoring of these morbidities, and parent information about these morbidities.

The development and implementation of innovation by health care providers is widely understood as a multi-determinant and multi-level process. Theories at different analytical levels (i.e. both micro and organisational) are needed in order to capture the processes that influence innovation by health care providers. This paper combines a micro theory of innovation, actor-network theory, with organisational level processes using the “resource based view of the firm”, to examine the influence of, and interplay between, innovation-seeking teams (micro) and underlying organisational capabilities (meso) during the development and implementation of service innovation. The study is based on two examples of service innovation in relation to ophthalmology services run by a specialist English NHS Trust at multiple locations in a large city. We conducted interviews (28) with stakeholders within and outside the Trust and non-participant observation (40.5 hours) of outpatient clinics and service and board level meetings. Operational Research techniques were used to map the care process in the clinics and establish the theoretical improvement possible through service redesign. In practice, innovation at the micro service level was constrained by the complexity of and strain on existing outpatient clinics. Deficiencies in organisational capabilities for supporting innovation were identified, including the nature of manager-clinician relations and organisation-wide resources. The study concludes that actor-network theory can be combined with the resource-based view to highlight the influence of organisational capabilities on the management of innovation. Equally, actor-network theory helps to address the lack of theory in the resource-based view on the micro practices of implementing change.

The purpose of this study was to gain an in-depth understanding of parents' experience and views of vaccinating their four to six-year-old child against influenza at school and at the general practice (GP). A cross-sectional qualitative study was conducted between March-June 2016 with parents of children in Reception and Year 1 in four randomly selected schools in Bury, Leicestershire, and Surrey, England. Twenty-five outreach forms were completed and returned, and seven interviews were conducted. Interview transcripts were coded by theme in NVivo (version 11, QSR International Pty Ltd., Melbourne, Australia). The primary reason parents gave for vaccinating their child was to prevent their child from contracting influenza. Parents' perceived benefits of vaccinating in schools were to avoid the inconvenience of having to take their child to the GP, and that their child would behave better at school. Parents viewed that accompanying their child for the vaccination at school would undermine the convenience and peer-pressure advantages of the school as a venue. No parents expressed concern about their child being too young to be vaccinated in school. This research suggests that the school is a desirable venue for childhood influenza vaccination, both from the parents' view and given that influenza vaccination coverage is higher when delivered through schools than GPs.

BackgroundIn 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.DesignObjective 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.DataWe 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.ResultsObjective 1The 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 2We 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.LimitationsWe 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.ConclusionsThe 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 workExtending our codevelopment approach to cover many other aspects of quality measurement across congenital heart disease and other specialised NHS services.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

Objective With survival following paediatric cardiac surgery improving, the attention of quality assurance and improvement initiatives is shifting to long-term outcomes and early surgical morbidities. We wanted to involve family representatives and a range of clinicians in selecting the morbidities to be measured in a major UK study. Setting Paediatric cardiac surgery services in the UK. Participants We convened a panel comprising family representatives, paediatricians from referring centres, and surgeons and other clinicians from surgical centres. Primary and secondary outcome measures Using the nominal group technique augmented by a robust voting process to identify group preferences, suggestions for candidate morbidities were elicited, discussed, ranked and then shortlisted. The shortlist was passed to a clinical group that provided a view on the feasibility of monitoring each shortlisted morbidity in routine practice. The panel then met again to select a prioritised list of morbidities for further study, with the list finalised by the clinical group and chief investigators. Results At the first panel meeting, 66 initial suggestions were made, with this reduced to a shortlist of 24 after two rounds of discussion, consolidation and voting. At the second meeting, this shortlist was reduced to 10 candidate morbidities. Two were dropped on grounds of feasibility and replaced by another the panel considered important. The final list of nine morbidities included indicators of organ damage, acute events and feeding problems. Family representatives and clinicians from outside tertiary centres brought some issues to greater prominence than if the panel had consisted solely of tertiary clinicians or study investigators. Conclusion The inclusion of patient and family perspectives in identifying metrics for use in monitoring a specialised clinical service is challenging but feasible and can broaden notions of quality and how to measure it.

Since the identification of variant Creutzfeldt–Jacob Disease in the late 1980s, the possibility that this disease might be passed on via blood transfusion has presented challenging policy questions for Government and blood services in the UK. This paper discusses the use of mathematical modelling to inform policy in this area of health protection. We focus on the use of a relatively simple analytical model to explore how many such infections might eventually be expected to result in clinical cases under a range of alternative scenarios of interest to policy, and on the potential impact of possible additional counter measures. We comment on the value of triangulating between findings generated using distinct modelling approaches and observational data.

Objective The study objective was to develop a risk model incorporating diagnostic information to adjust for case-mix severity during routine monitoring of outcomes for pediatric cardiac surgery. Methods Data from the Central Cardiac Audit Database for all pediatric cardiac surgery procedures performed in the United Kingdom between 2000 and 2010 were included: 70% for model development and 30% for validation. Units of analysis were 30-day episodes after the first surgical procedure. We used logistic regression for 30-day mortality. Risk factors considered included procedural information based on Central Cardiac Audit Database "specific procedures," diagnostic information defined by 24 "primary" cardiac diagnoses and "univentricular" status, and other patient characteristics. Results Of the 27,140 30-day episodes in the development set, 25,613 were survivals, 834 were deaths, and 693 were of unknown status (mortality, 3.2%). The risk model includes procedure, cardiac diagnosis, univentricular status, age band (neonate, infant, child), continuous age, continuous weight, presence of non–Down syndrome comorbidity, bypass, and year of operation 2007 or later (because of decreasing mortality). A risk score was calculated for 95% of cases in the validation set (weight missing in 5%). The model discriminated well; the C-index for validation set was 0.77 (0.81 for post-2007 data). Removal of all but procedural information gave a reduced C-index of 0.72. The model performed well across the spectrum of predicted risk, but there was evidence of underestimation of mortality risk in neonates undergoing operation from 2007. Conclusions The risk model performs well. Diagnostic information added useful discriminatory power. A future application is risk adjustment during routine monitoring of outcomes in the United Kingdom to assist quality assurance.

Objective To implement routine in-house monitoring of risk-adjusted 30-day mortality following paediatric cardiac surgery. Design Collaborative monitoring software development and implementation in three specialist centres. Patients and methods Analyses incorporated 2 years of data routinely audited by the National Institute of Cardiac Outcomes Research (NICOR). Exclusion criteria were patients over 16 or undergoing non-cardiac or only catheter procedures. We applied the partial risk adjustment in surgery (PRAiS) risk model for death within 30 days following surgery and generated variable life-adjusted display (VLAD) charts for each centre. These were shared with each clinical team and feedback was sought. Results Participating centres were Great Ormond Street Hospital, Evelina Children9s Hospital and The Royal Hospital for Sick Children in Glasgow. Data captured all procedures performed between 1 January 2010 and 31 December 2011. This incorporated 2490 30-day episodes of care, 66 of which were associated with a death within 30 days.The VLAD charts generated for each centre displayed trends in outcomes benchmarked to recent national outcomes. All centres ended the 2-year period within four deaths from what would be expected. The VLAD charts were shared in multidisciplinary meetings and clinical teams reported that they were a useful addition to existing quality assurance initiatives. Each centre is continuing to use the prototype software to monitor their in-house surgical outcomes. Conclusions Timely and routine monitoring of risk-adjusted mortality following paediatric cardiac surgery is feasible. Close liaison with hospital data managers as well as clinicians was crucial to the success of the project.