NHS Digital Data Release Register - reformatted

University of Leicester

Project 1 — DARS-NIC-370641-K0J0T

Opt outs honoured: Y

Sensitive: Non Sensitive, and Sensitive

When: 2017/03 — 2017/05.

Repeats: One-Off

Legal basis: Section 251 approval is in place for the flow of identifiable data

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Outpatients
  • Office for National Statistics Mortality Data

Objectives:

Community screening for Abdominal Aortic Aneurysm (AAA) by ultrasound has been proven to reduce AAA related deaths and has recently been adopted by the NHS with national coverage established in 2013 and from this year onwards, over 300,000 men will be screened for AAA every year with approximately 4000 AAA detected. Community screening for AAA in England is carried out by the NHS AAA Screening Programme (NAAASP), part of Public Health England (PHE). NAAASP invites all men for AAA screening in the year of their 65th birthday. Screening is carried out by ultrasound and is both clinically effective and cost effective. NAAASP records the infra-renal aortic diameter for all men who attend for screening. Men found to have an AAA (aortic diameter >30mm) are either entered into a surveillance programme that is also run by NAAASP (AAA 30mm to 54mm) or referred to a vascular surgeon for consideration of surgical repair (AAA >54mm). In order to ensure cost-efficiency. The incidence of AAA is falling in western populations and this raises the question of whether AAA screening will remain effective in the long-term. In addition, the NHS AAA Screening Programme (NAAASP), who has become part of Public Health England (PHE), will detect a large number of patients with small AAA that will require regular surveillance imaging. The University of Leicester propose to determine the outcomes of men being invited for screening by the NAAASP and investigate clinical factors associated with outcomes by linking a single-year cohort of men invited for AAA screening by NAAASP with multiple years of Hospital Episode Statistics (HES) data via the Health and Social Care Information Centre (HSCIC). In this project NAAASP will control all personal data and process this into a dataset that contains both pseudonymised and study identifiers. The University of Leicester will receive a dataset from NAAASP detailing the outcomes of screening. NAAASP will send HSCIC dataset comprising a list of NHS numbers and the study identifiers. HSCIC will use this dataset to identify the HES/HES-ONS records for the men in the dataset and provide this data to the University of Leicester with only the study identifiers. The University of Leicester will link the NAAASP data and the HES/HES-ONS data and perform analysis. The outcomes of patients attending the NAAASP are partially unknown. Patients with AAA are followed up by NAAASP through AAA surveillance and the outcomes of patients referred for surgery are recorded. The cause of death in patients with AAA who die whilst under surveillance is not automatically made available to NAAASP. In addition, those screened and found not to have AAA are discharged from NAAASP follow-up and some patients do not attend for screening. There is some evidence that patients with a normal aortic diameter at age 65 may develop an AAA later in life and therefore be at risk of AAA related death. Also, NAAASP utilises a technique for the assessment of aortic diameter that results in a smaller measurement when compared to other methods and discharges patients if their aorta is below a 3.0cm threshold. This technique may therefore result in some patients being discharged by NAAASP who may be entered into surveillance in other screening programmes. It is not known whether this puts discharged patients at risk of aortic rupture. The University of Leicester propose to link all patients invited for screening by NAAASP in 2013/2014 with the HSCIC to obtain HES data as outcomes, with yearly updates.

Expected Benefits:

In 2013/14 the NHS completed its first year of national screening for AAA. In the NAAASP men in the year of their 65th birthday are invited to have an ultrasound scan of their abdomen to screen for AAA. Screening men for AAA by ultrasound has proven to be clinically and cost-effective. If an AAA is detected there are well established pathways for treatment of large AAA, which are at risk of bursting (surgery), and clinical monitoring of small AAA, which are at low risk of causing harm. All men with AAA are followed-up by NAAASP. Only around 1.5% of men screened for AAA are found to have an AAA however. NAAASP screens over 300,000 men every year and measures the diameter of their abdominal aorta. It has been well established that aortic diameter is an indicator for the risk of dying from cardiovascular disease, with the highest risk in those with very small or very large aortic diameters. Whilst NAAASP measures and records aortic diameter in the men it screens for AAA it does not follow these men up. Furthermore, attendance rates for AAA screening are in the region of 80% and nothing is known about the long-term risk of AAA-related morbidity/mortality in the men who do not attend for screening. In this project the University of Leicester wish to determine whether there are opportunities to improve the health of men attending for AAA screening beyond simply the detection and treatment of AAA. Since NAAASP has already been set up and is measuring aortic diameters in all men attending for screening, if the University of Leicester can identify those men at high risk of cardiovascular events and flag these men for the institution of secondary prevention in primary care, the University of Leicester can add significant value to the process of AAA screening. Secondarily, the University of Leicester wish to identify whether screening non-attenders are at high-risk or low-risk of AAA-related or cardiovascular events to determine whether additional effort in re-inviting these non-attenders would be worthwhile or not.

Outputs:

The University of Leicester will use this data for research purposes and to feedback to NAAASP outcomes for service evaluation. Only de-identified data will be supplied to the University of Leicester. Due to the long-term nature of AAA related outcomes after screening the University of Leicester expect that the research outputs will not occur for at least 5 years and will continue to be produced at such intervals for at least 15 years. The service evaluation aspects of this work will be produced on a yearly basis. The University of Leicester will produce an annual report for the NHS AAA Screening Programme based on the linked cohort. The University of Leicester will produce research publications from the data. The NAAASP annual report will be sent directly to NAAASP. NAAASP will include summary data in their publically available national programme reports. The University of Leicester’s data table suppression rules are adhered to in the report they send to NAAASP. Research publications will be open-access and available to the public. The University of Leicester will again ensure that the University’s table suppression rules are adhered to in the preparation of these publications. These suppression rules are aligned with the HES analysis guide and where they differ the University’s rules are more robust.

Processing:

1. NAAASP will identify all men invited for screening in the 2013/2014 English screening cohort and all men with small AAA already under NAAASP surveillance. NAAASP holds this personal information for these men for the purposes of their clinical care. NAAASP will provide screening outcome data for the cohort to the University of Leicester. This data will contain a study ID for each individual. No personal data will be transferred to the University of Leicester. NAAASP will provide the NHS numbers of these men to the HSCIC, together with a study ID. 2. HSCIC will link the patients identified by NAAASP with HES/HES-ONS data using the NHS numbers and provide this linked data to the research team at the University of Leicester, using the same study ID as those used by NAAASP to transfer data to the University of Leicester. HSCIC will then supply the University of Leicester with HES/HES-ONS data stripped of identifiers other than the study ID supplied by NAAASP. The University of Leicester will apply for updated linkage reports on a yearly basis. 3. The University of Leicester will receive data from both NAAASP and HSCIC. This data will be linked using the study ID and analysed. The University of Leicester will provide NAAASP with annual reports based upon the data, the content of which will be determined by NAAASP but will primarily consist of all-cause and aneurysm-specific mortality and aneurysm-related morbidity. The University of Leicester will also analyse the data for the purposes of producing research papers focussed on the description of mid- to long-term outcomes of contemporary AAA screening. No personal data will be held or processed by the University of Leicester.


Project 2 — DARS-NIC-347200-H9G0Q

Opt outs honoured: N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2016/08.

Repeats: Ongoing

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Categories: Identifiable

Datasets:

  • MRIS - Cause of Death Report
  • MRIS - Flagging Current Status Report

Objectives:

Researchers from the National Institute for Health Research (NIHR) Diet, Lifestyle and Physical Activity Biomedical Research Unit are investigating the association of objectively measured levels of physical activity and sedentary behaviour with the risk of all-cause and disease-specific mortality. University of Leicester is requesting ONS-mortality data for its ‘Walking Away from Type 2 Diabetes Study’ to be used to answer this question. The ‘Walking Away from Type 2 Diabetes’ was conducted by the Diabetes Research Centre, University of Leicester. In total 833 participants were recruited to the study from January 2010 to January 2011. Of these, 719 gave consent for their future health status to be accessed. University of Leicester is seeking ONS-mortality linkage for these 719 individuals. Data will not be shared with a third party and will be stored on secure servers controlled by the University of Leicester

Expected Benefits:

Over recent years sedentary behavior, conceptualised as any non-exercise sitting, has gained increasing interest as a distinct health behaviour that acts as an important determinant of mortality and mortality independently to MVPA. This has initiated research activity and public health attention on the possible benefits of displacing time in sedentary behaviour for time in light-intensity physical activity as an additional target to traditional lifestyle interventions focused on the promotion of MVPA. However, further research is needed with morbidity and mortality outcomes and objective measures of sedentary behaviour to adequately quantify the distinctive association of sedentary behaviour with health. Data generated by this study will help establish the strength of the association between sedentary behaviour and mortality risk and whether this relationship is fully independent of habitual physical activity levels. The research has been commissioned by the NIHR Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit and the results will be feed back to NIHR through the process of annual reporting. This analysis will also inform NICE guidance and guidance from other national/international health care organisations in the future. NICE have already held a Topic Advisory Workshop on sedentary behaviour and are likely to require robust evidence with which to form guidance specific to sedentary behaviour in the near future. Once this research is in progress, University of Leicester will contact the Chairperson of all relevant NICE committees (related to physical activity, sedentary behaviour or diabetes prevention) to make them aware of this project. University of Leicester will also seek to present any finding as expert testimony. This research will also inform lifestyle interventionists of the importance of targeting sedentary behaviour within the context of lifestyle intervention.”

Outputs:

The results of the analyses highlighted above will be disseminated through presentations at international topic-relevant conferences and publication in peer-reviewed academic medical journals. University of Leicester anticipate that results will be ready for dissemination by December 2016. Findings will be presented at the meetings organised by the “International Society for Behavioral Nutrition and Physical Activity (annual)” or the “International Congress on Physical Activity and Public Health (every two years)”. Results will be published in a peer-reviewed medical journal. In the first instance University of Leicester will target a high impact journal such the Lancet or Journal of the America Medical Association. The exact journal will be dependant on the peer-review process and journal acceptance. The level of output data will be statistical in nature, i.e. the risk of all-cause mortality was reduced by XX% per every 30 minute difference in moderate-intensity physical activity. Individual record level data will not be published or shared with a third party.

Processing:

University of Leicester want to test the hypothesis that objectively measured daily sedentary time and time in moderate-to-vigorous physical activity (MVPA) are both independently associated with all-cause and cardiovascular mortality. The ‘Walking Away from Type 2 Diabetes’ dataset for which linkage to ONS-mortality linkage is being requested includes levels of objectively measured average daily time spent sedentary (i.e. sitting) and in MVPA. Objective measurements were obtained through accelerometer technology. The ‘Walking Away from Type 2 Diabetes’ study received a favourable NHS ethical review and patients were given the option of consenting to having their future health status accessed. Only those that explicitly provided this consent will be included in the dataset sent for linkage. Cox proportional hazard models will assess the independent associations of baseline sedentary time and MVPA time with all-cause and cardiovascular mortality that occurred from baseline to follow-up (most current ONS-mortality data). Assumptions of linearity will be assessed. Areas of non-linearity likely at the extremes of sedentary behaviour will be analysed using spline techniques. Data will be adjusted for accelerometer wear time and measured/clinical/anthropometric/demographic confounders. The hazard ratios obtained from the above analysis will be combined with those generated from other studies from which the outputs are accessible to University of Leicester using standard meta-analytic methods in order to increase the power and generalizability of this project’s findings. However, University of Leicester will not merge or link this data with other datasets or allow access to third parties. All analysis will be conducted within the Diabetes Research Centre, University of Leicester.


Project 3 — DARS-NIC-262908-X5F4Q

Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)

Sensitive: Non Sensitive, and Sensitive

When: 2020/12 — 2020/12.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Critical Care
  • HES:Civil Registration (Deaths) bridge
  • Hospital Episode Statistics Outpatients
  • Hospital Episode Statistics Admitted Patient Care
  • Civil Registration - Deaths
  • Hospital Episode Statistics Accident and Emergency
  • Diagnostic Imaging Dataset
  • Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset

Objectives:

This study will be undertaken by the Leicester Cardiac Surgery Research Group at Department of Cardiovascular Sciences based in the University of Leicester. This study is to establish a database of patients with cardiovascular diagnosis in England using routinely collected clinical and mortality data obtained from NHS Digital. This database will be used to model trials of surgical interventions in silico and devise a set of pragmatic trial proposals to address the priority research questions in cardiac surgery. HES DATA The gold standard for the evaluation of medical treatment is through randomised controlled trials. However, the successful delivery of clinical trials are often limited by the many assumptions that are required for design and planning. Assumptions are often made with respect to recruitment, eligibility, event rates, effect estimates, safety and attrition in real world populations. Hospital Episode Statistics (HES) data contains a wealth of real-world data including demographics, diagnoses, procedures and other clinical information collected prospectively from all NHS hospitals. This routinely collected clinical data enables the University of Leicester to explore the effect of interventions (e.g. open heart vs minimally invasive heart surgery) in a population and across different patient subgroups (e.g. elderly patients, or patients with other medical conditions), and obtain the necessary parameters required for designing a clinical trial. The University of Leicester may also optimize the trial design through sensitivity analyses of the inclusion/exclusion criteria of patient populations and definition of clinical outcomes. Applications of electronic health records to estimate trial outcomes and assess trial feasibility have been reported (Longo 2003, Doods 2014, Mc Cord 2018). In this project, the University of Leicester propose to use HES data to obtain the granular data required for designing clinical trials assessing trial feasibility, thus minimizing the assumptions imputed and making the process quicker, simpler and more reliable. The University of Leicester will model pragmatic trials of surgical interventions in silico that will, in turn, be used to inform commissioning and funding applications for randomised clinical trials in NHS hospitals. James Lind Alliance (JLA) Priority Setting Partnership (PSP) in Adult Heart Surgery The Heart Surgery Priority Setting Partnership (PSP) is a collaboration between the Department of Cardiovascular Sciences at the University of Leicester and the James Lind Alliance (JLA). The JLA is a National Institute for Health Research (NIHR) initiative that aims to bring patients, carers and healthcare professionals together to identify and prioritise top unanswered health research questions. The University of Leicester propose to use HES data to design clinical trials in silico, assess trial feasibility, and devise a set of trial proposals to address the priority research questions identified in the JLA Heart Surgery PSP. The PSP has identified over 40 research questions covering different aspects of cardiac surgery, and the Top 10 research questions identified are: 1. How does a patient’s quality of life (QOL) change (e.g. disability-free survival) following heart surgery and what factors are associated with this? 2. How can we address frailty and improve the management of frail patients in heart surgery? 3. How can we improve the outcomes of heart surgery patients with chronic conditions (obesity, diabetes, hypertension, renal failure, autoimmune diseases etc.)? 4. Does prehabilitation (a programme of nutritional, exercise and psychological interventions before surgery) benefit heart surgery patients? 5. When should heart valve intervention occur for patients without symptoms? 6. How does minimally invasive heart surgery compare to traditional open surgery? 7. How do we minimise damage to organs from the heart-lung machine/heart surgery (heart, kidney, lung, brain and gut)? 8. Can we use 3D bio printing or stem cell technology to create living tissues (heart valves/heart) and repair failing hearts (myocardial regeneration)? 9. What are the most effective ways of preventing and treating postoperative atrial fibrillation? 10.How do we reduce and manage infections after heart surgery including surgical site/sternal wound infection and pneumonia? Please note: these questions are official wording sources from JLA Heart Surgery PSP. STUDY OBJECTIVES The primary objective of this project is to use routinely collected HES and the linked mortality data to model trials of surgical interventions in silico and devise a set of pragmatic trial proposals to address the national priority research priorities in cardiac surgery. The secondary objectives are: • To evaluate the extent to which in silico trials can be conducted using HES data to design new trials. • To establish methodologies and a systematic framework to carry out trials in silico with HES data so that trial feasibility can be conducted quickly and cost-effectively for a range of research questions. • To develop capacity in processing and analyzing real-world clinical data using statistical and machine learning methods. • To gain insights into how we might use HES data sets to support data collection and undertake future pragmatic trials. REQUESTED DATA Adult patients (18 years and above) with a cardiovascular diagnosis (ICD10 I00-I99, whether primary or secondary diagnoses) in HES Admitted Patient Care (APC) will form the reference cohort. Request for all HES and Civil Registrations - Deaths data sets are confined to patients identified in the reference cohort. Cumulative reference cohort will be used for annual update. The University of Leicester are requesting the data sets for the past 10 years plus an annual update for the next 3 years. An addition of two earlier years is also requested for HES APC for the purpose of new case ascertainment and defining patients’ co-morbidities and frailty score. 1) HES Admitted Patient Care (APC) AR 2007/08 to AR 2018/19 plus annual update to 2021/22 2) HES Critical care (CC) AR 2009/10 to AR 2018/19 plus annual update to 2021/22 3) HES Accident and Emergency (AE) AR 2009/10 to 2019/20 M12 4) ECDS AR 2020/21 to AR 2021/22. 5) HES Outpatient (OP) AR 2009/10 to AR 2018/19 plus annual update to 2021/22 6) Civil Registrations - Deaths data 2007/08 to 2018/19 plus annual update to 2021/22 7) Diagnostic imaging data sets (DID) 2007/08 to 2018/19 plus annual update to 2021/22 COHORT The estimated size of the reference cohort is roughly 1.5 million admissions a year. The University of Leicester project team recognises that this is a large cohort size but will use the requested data to model trial in-silico and address the priority research questions in cardiac surgery identified by the James Lind Alliance process. It is important to recognise that the James Lind Alliance process provides a set of priorities for research agenda which could be translated into future clinical trials. These research questions represent the areas that are important to those affected by cardiac surgery but are not precisely-worded that can be shared immediately with research funders. Further work is required to translate the research priorities into specific potential researchable questions for research funders to work with. For example, priority 3 ‘How can we improve the outcomes of heart surgery patients with chronic conditions?’, this question can potentially lead to specific research questions like (a) does pre-surgery optimisation of chronic conditions reduce post-operative lung and kidney injury or infection? (b) does minimally invasive approach improve outcomes in patients with chronic diseases? (c) are there specific pre-surgery interventions that can be targeted to patients with specific chronic diseases (e.g. weight loss programme for obese patients, glucose control for diabetic patients, iron supplement for anaemic patients)? Also, some specific question can address more than one research priority, for example, the question “does minimally invasive approach improve outcomes in patients with chronic conditions?” addresses two research priorities in relation to improving outcomes in patients with chronic conditions (priority 3) and minimally invasive cardiac approach (priority 6). As well as strategic partnership with research groups to facilitate question formulation, the University of Leicester, in collaboration with Cochrane Heart, will commission a series of systematic reviews of the priority research questions to identify the knowledge gaps that can be addressed by clinical trials. In addition, the University of Leicester is organising a one-day Clinical Research Priorities Workshop to pump prime potential research teams who can come together to develop high quality research proposals for research funders. The workshop will bring together patients, carers, and a critical mass of expertise including clinicians, methodologists and scientists from across the UK to form interdisciplinary working groups and identify important trial questions from the research priorities. This Workshop was initially scheduled for July 2020 but has been postponed to early next year due to the Coronavirus pandemic. In this project, the population of interests are adult patients with cardiovascular diseases who require or potentially require cardiac surgery. Cardiac surgery is performed to fix problems in the heart. It is used to treat a wide variety of cardiovascular diseases including aortic disease, arrhythmia, heart failure, coronary heart disease, cardiomyopathy, valvular heart disease, etc. Sometimes these problems can be addressed with medications or non-surgical procedures. For example, coronary angioplasty is a minimally invasive procedure in which a stent is inserted into a narrowed or blocked coronary artery. There are many types of heart surgery, some of the most common ones include coronary valvular surgery, aortic surgery, arrhythmia surgery, coronary artery bypass graft (CABG) surgery. The identified research questions cover all types of cardiac surgery and encompass all aspects of surgery from pre-operative assessment and risk stratification, to intraoperative management and post-operative outcomes. The University of Leicester requests hospital admissions (HES APC) from adult patients with cardiovascular diagnoses. The requested data will be used to model a variety of cardiac surgery trials, and the analyses involved are board ranging. The analyses will not be limited to cardiac surgery patients, as it is also imperative to examine the effectiveness of surgical treatment by comparing the outcomes of cardiovascular patients with surgical and non-surgical interventions. For example, the research team is interested in developing trials examining the risks and benefits of CABG bypass surgery vs non-surgical angioplasty in heart failure patients. By limiting the patient cohort to patients who had cardiac surgery would limit the usefulness of the data. It is also not feasible to produce an exhaustive list of diagnosis codes that the cardiac surgery is used for. Therefore, although the focus of this study is cardiac surgery, the study requires a boarder cardiovascular cohort to define the patient population. It is important to note that although the HES APC data is termed the reference cohort, it will be used not only to define the patient populations but also to identify post-operative outcomes which include a wide range of cardiovascular conditions such as stroke, myocardial infarction, atrial fibrillation, in the trial modelling. In addition, the exact research questions for cardiac surgery are still being developed through the Cochrane review and the Clinical Research Priorities Workshop, it is necessary to ensure the requested hospital data covers all cardiovascular conditions so that the design of trials would not be limited by a predefined set of diagnoses. The University of Leicester also requests hospital admissions within two years prior to the cardiovascular admissions, this data is required to check for patients’ frailty score and co-morbid conditions. These prior hospital episodes need to include ICD codes beyond the cardiovascular codes because the derivation of comorbidity and frailty scores such as Hospital Frailty Risk Score (Gilbert 2018) and Charlson Comorbidity Index (Li 2008) require a board range of diagnoses including both cardiovascular and non-cardiovascular codes. In addition, two of the research priorities identified are related to frailty (priority 2) and patients with chronic conditions (priority 3). Frail patients are often elderly patients with multiple medical conditions. Frailty is currently poorly defined for cardiac surgery. It would be desirable to examine if specific set of ICD codes could be identified to define frailty for cardiac surgery. By limiting our study to only pre-specified comorbid conditions, it would limit the usefulness and ability of the study to inform future cardiac surgery trials. This project requires adult data defined by patients aged 18 and above, in line with the scope of the James Lind Alliance Priority Setting Partnership for Heart Surgery. Children data are not needed. The University of Leicester requests national data as this project targets at designing multi-centre pragmatic trials to evaluate clinical effectiveness in a real-world setting. Access to and outcomes of cardiac surgery vary across geographical regions. Such variations may reflect difference in patient case-mix, centralisation of care into specialist hospitals, variation in practices, and other factors. By limiting the analysis to specific geographical regions would affect the generalisable of the findings in multiple settings. It is also important to recognise that certain heart operations such as the Ross procedure, Transcatheter aortic valve implantation (TAVI) are only practised by limited heart centres in the UK. In addition, an important part of the analysis is to enable a detailed understanding of the characteristics of patient populations and the estimation of treatment effects across patient groups stratified by age, comorbid conditions or frailty thus enabling the identification of targeted populations for specific interventions. Large volume national level data is therefore needed to ensure sufficient patient size to carry out sub-group analysis. The University of Leicester requests various HES datasets and Civil Registrations – Deaths data to evaluate short (in hospital, within 1 month), medium (3-6 months) and long term (1 to 5 years) outcomes of cardiac surgery patients. Cardiac surgery is a complex operation with all heart surgery patients requiring intensive care support immediately after the surgery. It is necessary to include organ support data in critical care (HES CC) and post-op complications and in-hospital mortality in the index episodes (HES APC) to evaluate the short-term outcomes of patients after surgery. Also, HES APC datasets will be longitudinally linked to track short to medium term outcomes including readmission due to cardiovascular causes and repeat of heart operation. Together with the HES A&E data, unplanned readmissions could be identified which could serve as an indicator of adverse outcomes post surgery. The request of Civil registration mortality data will enable the project team to undertake survival analysis and evaluate patients’ survival in short, medium and long term basis. The project team is planning to track the outcomes within 5 years after surgery as long term outcomes. Most of the existing clinical trials have focused on reporting short terms outcomes. Data on long term outcomes are lacking, although this is important to determine the comparative effectiveness of different surgical and non-surgical interventions. The University of Leicester requests 10 years of patient data in the initial cohort, and this will provide 5 years of data with long term outcome measures. In addition to clinical outcomes, this study will include analysis to evaluate healthcare resource use following an intervention. As well as the extraction of resources use data during the index admission, post-discharge healthcare use data will be obtained on hospital readmissions, visits to Accident and Emergency, outpatient attendances, and imaging tests. Resources including length of hospital stay and various levels of care after surgery will be obtained with HES APC. As all heart surgery patients need to be followed up in outpatient clinics post discharge and cardiac imaging such as echocardiography and cardiovascular magnetic resonance are used to assess cardiovascular function after cardiac surgery, it is necessary to include HES outpatient (OP) and imaging (DID) data sets as part of the outcome analysis. Also, HES A&E data is needed to identify unplanned medical visits as indication of healthcare resource use resulting from post surgery complications. In summary, patient population, identified by the index episodes receiving the relevant surgical /procedural interventions, along with their baseline patient characteristics (demographics, co-morbid conditions, frailty scores, etc) will first be defined using HES APC. Short term outcomes including post-operative complications and in-hospital mortality would be tracked using HES CC and APC. Medium term healthcare resource use following the surgical intervention will be tracked with HES AE, OP and DID data sets. Long term outcomes including 1-year and 5-year survival will be tracked using Civil Registrations - Deaths data. The University of Leicester has considered data minimisation to ensure the data requested is justified and limited to the study objectives. The requested HES data sets will be individual records and pseudonymised with unique identifiers generated by NHS Digital. No identifiable data (name, address, NHS number, etc) will be included in the data sets. Civil Registrations - Deaths, and DIDs data sets are linked to the HES data sets through bridging files. HES data set will be longitudinally linked through the pseudo identifiers. All the analyses will be carried out within the data sets requested in this application. There will be no linking of these data sets to any external data sets. The University of Leicester is the sole data controller and will process the data for this project. No data processing will be carried out by other organisations. The project team will share and discuss the results in form of summary statistics with the collaborators. No data processing would be undertaken by them and all decisions about the data analysis would remain with the university. James Lind Alliance is not involved in this project. However, the University will feedback to James Lind Alliance for any successfully funded trials resulting from the work of this project. PATIENT AND PUBLIC INVOLVEMENT (PPI) The University of Leicester will engage with patients and the public for dissemination and communication of the main findings. This will be facilitated through the established Patient and Public Involvement (PPI) networks with the Leicester Cardiac Surgery Research Group and the Heart Surgery Priority Setting Partnership Steering Committee. Through the involvement and recommendations regarding the dissemination of findings by the PPI groups, this will ensure the outputs are interpret-able to the wider patient and public community. LEGAL BASIS This project is managed by the University of Leicester and will be conducted in accordance with all applicable regulatory guidelines. The University of Leicester will lawfully be processing personal data on the basis of GDPR Article 6.1(e) - the processing is necessary for the performance of a task in the public interest. Research is a task that the University of Leicester performs in the public interest, as part of the core functions as a university. This project will involve processing data related to patients’ ethnicity (there are marked ethnic differences in risk of cardiovascular diseases). The University will lawfully be processing special categories of personal data on the basis of GDPR Article 9.2(j) - the processing is necessary for research purposes or statistical purposes. We will be processing pseudonymised data and the data sets will be stored and processed in accordance with the University Information Security Policy, College of Life Sciences Information Governance Policy, General Data Protection Regulation (GDPR) (EU) 2016/679 and the UK Data Protection Act (2018). REFERENCES 1/ Longo et al. Can randomised trials rely on existing electronic data? A feasibility study to explore the value of routine data in health technology assessment. Health Technol Assess. 2003;7(26):iii, v-x, 1-117. 2/ Doods et al. A European inventory of common electronic health record data elements for clinical trial feasibility. Trials. 2014 Jan 10; 15:18. 3/ Mc Cord et al. Routinely collected data for randomized trials: promises, barriers, and implications. Trials. 2018 Jan 11;19(1):29. 4/ Gilbert et al. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet. 2018 May 5;391(10132):1775-1782. 5/ Li et al. Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Serv Res. 2008 Jan 14;8:12.

Expected Benefits:

Approximately 35,000 adult cardiac procedures are carried out in the UK each year. The national research priorities for cardiac surgery have been identified through a vigorous and transparent James Lind Alliance (JLA) process and collectively agreed by patients, carers and healthcare professionals. The University of Leicester propose to use HES routinely collected clinical data to model trial in-silico and assess trial feasibility. The outcomes will lead to the production of a portfolio of cardiac surgery trial proposals to address those important research questions. It is anticipated that these trial proposals will attract research funding from UK National Institute for Health Research (NIHR) and British Heart Foundation (BHF) to the University of Leicester. More importantly, the eventual implementation of these trials could lead to improved clinical care and outcomes for heart surgery patients. One of the key outputs of this project is a master protocol/methodological paper that will describe the methods, strengths and limitations of conducting in-silico trials using HES data. The in-silico approach could potentially shorten the research cycle from proof of concept to implementation of the trial, and set as a new benchmark in clinical trial design. By using HES data to obtain the granular data required for designing a trial and assess its feasibility, it can make the design of clinical trials quicker, simpler and more reliable. In addition, the in-silico approach can inform the subsequent data analysis plan of the trials designed on this basis. Concerns as to the event distributions over time, length of follow-up and so on can be addressed at the trial design phase. Also, it is anticipated that the in-silico approach developed using cardiac surgery will be adaptable across surgical disciplines. The University of Leicester will engage with key research funders to promote the initiative of in-silico trial as a key element for the rationale and justification of trial funding. The University of Leicester will share the methodology and promote the initiative with researchers of interests via workshop and academic channels (publications, academic conferences). There is an increased emphasis on using routinely collected data to answer clinical and research questions. The in-silico trial initiative aligns with the research strategies of NIHR, the BHF Health Data Science Centre and the NHS DigiTrial - The Health Data Research Hub for Clinical Trials to increase the use of routinely collected HES data in supporting planning and delivery of pragmatic clinical trials. The dissemination of the in-silico methods will be undertaken in collaboration with the following professional bodies and research partnerships: 1. The Society for cardiothoracic Surgery in Great Britain and Ireland 2. The UK Clinical Research Collaboration (UKCRC) Clinical Trials Network 3. The British Heart Foundation (BHF) Health Data Science Centre 4. The UK National Institute for Health Research (NIHR) BHF Cardiovascular Partnership 5. The Royal College of Surgeons of England Clinical Trials Initiative. In addition to the output of trial parameters using HES, this work will provide a platform to identify unmet needs and areas for further research and development. An example is the use of linked electronic health records and other routinely collected primary and secondary care data in pragmatic clinical trials. This is one of the strategic aims of the new BHF Health Data Science Centre of which the Chief Investigator is a member of the steering committee. Throughout the analysis, the project team will identify the outcome measures that are unable to be obtained from the NHS Digital HES data and propose how these might be addressed using remote data capture of electronic health records, smart phone data capture or other data capture methods. The proposed digital tool for designing trials of cardiovascular diseases, intended to be put in a public domain, will enable any researchers interested in surgical research to plan for their cardiac surgery trials. This project has also an additional benefit of educational training - the research team has a member of staff who is doing a part-time PhD, and will be trained in biostatistics, machine learning and clinical trial design using the data.

Outputs:

The University of Leicester will use the data for the research purposes specified in the application. This project will set out a methodological framework for conducting in silico trials using routinely collected HES and the linked death data. The work will provide granular data required for designing surgical trials and lead to the production of a portfolio of pragmatic trial proposals addressing the top priorities research questions in heart surgery. The project team will first work on two candidate trials, which have been selected so that the strengths and the weaknesses of the in-silico trials approach can be identified. The two trials are: 1. Benefits of re-vascularisation (bypass surgery vs minimally invasive angioplasty) in heart failure patients – this work will model the comparative effectiveness of bypass surgery vs angioplasty in people with heart failure (a chronic condition) and coronary artery disease. The trial will address research priorities including improving outcomes in patients with chronic conditions (priority 3) and comparative effectiveness of minimally invasive vs open surgery (priority 6). 2. Benefits of stratification of re-vascularisation decisions based on objective measures of frailty - this work will model a trial to test the hypothesis that treatment decisions stratified by frailty are likely to result in improved long-term benefits. The trial will address improving outcomes of heart surgery patients in relation to long-term quality of life outcome (priority 1), frailty (priority 2) and minimally invasive vs open surgery (priority 6). As well as the outputs for these two trials, this work will facilitate the development of the in-silico methodological framework and contribute to the production of a master protocol that will describe the methods, strengths and limitations of conducting in-silico trials using HES data. The project team will work on modelling other trials in-silico when the exact research questions are formulated after the Cochrane review and the Clinical Research Priorities Workshop. Trial proposals, funding applications and all research reports and presentations resulting from this project will contain only summary aggregated data with small numbers suppressed in line with the NHS Digital HES Analysis Guide. Research presentations may consist of oral presentations, poster and published abstract. Scientific findings will be disseminated by usual academic channels, i.e. presentation at academic conferences and publication in peer-reviewed journals. No identifiable information will be presented. The James Lind Alliance Priority Setting Partnership in Heart Surgery identified over 40 research questions covering different aspects of cardiac surgery. The priority will be given to address the top 10 questions, but it is important to recognise that some of the remaining questions are also important research questions. These include geographical variation in outcomes of heart surgery. The project team will use an observational study design to examine the short and long term outcomes of heart surgery patients by geographical regions and the factors associating with the variations. Peer reviewed scientific publications will be produced from analysing the data. Proposed digital tool for designing trials of cardiovascular diseases The University of Leicester Cardiac Surgery Research Group is planning to develop a web-based digital tool to support the planning of clinical trials in cardiac surgery. The tool is to be a web-based interactive tool to display the data summary and analyses that the University of Leicester Cardiac Surgery Research Group do for the research questions. The tool would keep multidimensional databases (in the same vein as an online analytical processing (OLAP) cube. An OLAP cube is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional data set) for important trial parameters like patient numbers, outcome events stratified by dimensions including surgery/intervention, patient age and sex, frailty score, geographical region, etc that the users are able to be specified. Users will be asked to select/enter the targeted patient population (based on age, diagnosis, medical conditions etc), geographical region, the intervention, the comparator, trial design, primary outcome. The digital tool will then output the trial parameters including the occurrence of the primary outcome, expected treatment effect, sample size required, availability of patient populations by hospital etc. The tool will also help users to explore the trial parameters for different patient groups. The tool is intended to be put in a public domain, to be used by UK healthcare professionals and researchers inside and outside the University of Leicester. The tool is a web application accessible via a web address. The data will sit on a secure server owned by the University of Leicester. With respect to access control, users need to register and login to gain access to the tool. The tool will make no attempt to link NHS Digital data with any other data sets. All outputs are aggregated statistics with small number suppressed as per the HES guide. Target dates for outputs: Short term (1 - 2 year) - a methodological paper or a master protocol that will describe the methods, strengths and limitations of an in-silico trial approach; Medium term (2 - 5 years) - a series of pragmatic trial proposals, including the two candidate trials, that answer the priority research questions identified by JLA Priority Setting Partnership in Heart Surgery.

Processing:

NHS Digital will extract: 1. HES APC: hospital admissions with cardiovascular diagnoses (primary or secondary) ICD10 I00-I99 (cardiovascular episodes), and this will form the basis of reference cohort. 2. HES APC: all hospital admissions including those with and without cardiovascular diagnoses in the two years preceding for each admission identified in (1) 3. HES Critical care (CC): ICU admissions linked to the cardiovascular episodes identified in (1) 4. HES Accident and Emergency (AE): all AE records of patients in the reference cohort 5. ECDS : all AE records of patients in the reference cohort 6. HES Outpatient (OP): all Outpatient records of patients in the reference cohort 7. Diagnostic imaging data sets (DID): all imaging records of patients in the reference cohort 8. Civil Registrations - Deaths data: mortality records of patients in the reference cohort In the first extraction for 2009/10 – 2018/19, Data set (1), which includes all cardiovascular episodes during the extraction period, will form the reference cohort for extraction of other data sets. In subsequent annual updates, the cumulative data set (1) will form the reference cohort for data extraction. For Data set (2), the University of Leicester would like to know all cardiovascular and non-cardiovascular diagnoses during the 2 years prior to the cardiovascular episodes. Say a patient has a cardiovascular episode identified in June 2008, the University of Leicester would like to have all his/her cardiovascular and non-cardiovascular diagnoses from June 2006 to June 2008. Also, data set (2) will be needed not only for first time diagnosis, but for all cardiovascular episodes. For example, if a patient had undergone angioplasty in May 2008 and a heart bypass surgery in Dec 2018. A study on minimally invasive technique may use the angioplasty episode in May 2008 to form the study cohort, and the patient’s co-morbidity and frailty score will be determined based on the all his/her admission records in May 2006 to May 2008. But for another study on, for example, the quality of life of open heart bypass surgery, the study cohort will include this patient’s admission in Dec 2018 and his/her co-morbidity and frailty score will be determined based on the his/her admission records in Dec 2016 to Dec 2018. A data flow diagram with illustration of the logic of data extraction is provided in the supporting documentation. All data sets (1) to (7) will be extracted annually. NHS Digital will supply the University of Leicester with pseudonymised HES data and linked Civil Registration- Deaths data. No identifiable information will be included in the data sets. The University of Leicester will analyse the data for the purposes of producing clinical trial proposals and research papers. For each of the priority research questions in Heart Surgery, the general steps of data analysis are outlined as follows. a. Data preparation and phenotyping – to define patient groups based on demographic information and diagnosis codes; define specific surgical interventions using OPCS-4 codes; and prepare HES data sets that are longitudinally linked. In-hospital outcomes will be tracked using HES APC and CC data, and mid to long term outcomes will be identified using HES APC, OP, AE, ECDS, DIDs and Civil Registrations - Deaths data bases. b. In-silico trials – For a given research question, define the study hypothesis, patient populations, intervention, and primary and secondary outcomes, – Propose an overall trial design and carry out statistical analysis to obtain the parameters required for designing clinical trials including outcomes rates and treatment effects – Conduct subgroup analysis and model treatment heterogeneity across patient groups – Estimate sample size required and assess trial feasibility (in terms of availability of patient population and resources), and – Carry out sensitivity analyses varying the trial designs, definition of trial outcomes and reassess the sample size requirement and trial feasibility. c. Output - output trial parameters and produce trial proposals. The University of Leicester will comply with the Data Sharing Framework Contract requirements. DATA STORAGE The data will be exclusively stored and processed at the University of Leicester and not shared with any third parties. The University of Leicester has no access to the files that can link the pseudo identifiers back to the patients. The research team will not carry out any analysis attempting to re-identify patients. The requested data will not be linked with any external data sets. All outputs shared with the project collaborators will be aggregated with small numbers suppressed in line with the HES Analysis Guide. All data will be stored on the secure dedicated research data storage service known as the Research File Store (RFS) at the University of Leicester. The server is based in University’s main campus, and is not cloud based. The RFS is a secure and resilient server that adheres to current information governance standards and is centrally managed by the University of Leicester to ensure it is updated to meet future changes in data security standards. Security of the system is be governed by the corporate security policy of The University of Leicester. The RFS is built on an enterprise-class storage facility which is replicated between two secure, access-controlled data centres for recovery purposes. Nightly backups are also taken to an enterprise-class storage facility in the Secondary data centre. Backups are retained for 28 days. Both data centre facilities are owned by University of Leicester and managed by the University of Leicester internal IT Services. DATA ACCESS The Leicester Cardiac Surgery Research Group, University of Leicester will control the access of the requested HES and Civil Registration - Deaths data. Only designated researchers employed by the University of Leicester will be granted the access right to process and analyse the data supplied by NHS Digital. Project collaborators will have no access to the raw patient data, and only aggregated outputs with small numbers suppressed in accordance with the HES Analysis guide will be shared with them. All data processing and analyses will be carried out within the University of Leicester. DATA PROCESSING All individuals processing the data are substantive employees of the University of Leicester. The student referenced in this research team is doing a PhD on a part-time basis and is also a substantive member of staff of the University of Leicester. Data Processing will take place physically at University of Leicester’s Cardiovascular Biomedical Research Unit located in Glenfield Hospital, Groby Road, Leicester, LE3 9QP via secure remote access to the RFS.


Project 4 — DARS-NIC-148437-C9YSC

Opt outs honoured: N

Sensitive: Sensitive, and Non Sensitive

When: 2016/04 (or before) — 2017/02.

Repeats: Ongoing

Legal basis: Informed Patient consent to permit the receipt, processing and release of data by the HSCIC

Categories: Identifiable

Datasets:

  • MRIS - Cause of Death Report
  • MRIS - Cohort Event Notification Report

Objectives:

This study aims to find out more about abdominal aortic aneurysms (AAA). This is a condition where the main artery in the body swells up and there is a risk of it bursting as a result. This kills approximately 10,000 people in England and Wales per year. These AAA can be found when they are small but it they get bigger there is no treatment for them other than high-risk surgery. Recently, a national screening programme has been started for AAA and through this programme, patients with AAA and those found not to have AAA will be recruited into this study. Study participants will have blood and urine samples taken at several time points as well being asked to fill in questionnaires about how they feel and their general health. Long-term follow up of the participants through the data retrieved from the MRIS will be used to determine mortality rates and causes in the study participants.


Project 5 — DARS-NIC-120105-F0K2L

Opt outs honoured: No - data flow is not identifiable (Section 251, Does not include the flow of confidential data)

Sensitive: Non Sensitive, and Sensitive

When: 2019/01 — 2019/11.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Accident and Emergency
  • HES:Civil Registration (Deaths) bridge
  • Civil Registration - Deaths

Objectives:

Critically ill children who are admitted to district general hospitals can require specialist transport to a paediatric intensive care unit (PICU). There is considerable variation in the care provided to critically ill children prior to admission to paediatric intensive care. It is unclear whether the differences in timeliness of access to paediatric intensive care, and care delivered during stabilisation and transport by specialist transport teams, matter in terms of clinical outcomes and patient experience. This lack of scientific evidence has led over the years to the evolution of different models of paediatric transport provision, the development of national standards based on expert opinion rather than scientific evidence and has contributed to the lack of progress in improving care at the crucial interface between secondary and tertiary paediatric care. The objective of the DEPICT (Differences in access to Emergency Paediatric Intensive Care and care during Transport) study is to study the association between timeliness of access to paediatric intensive care and 30-day mortality. The University of Leicester requires pseudonymised linked data for use in the quantitative analysis work stream of the DEPICT Study (IRAS ID: 218569). The DEPICT Study was instigated and is led by the Chief Investigator based at Great Ormond Street Hospital. Great Ormond Street Hospital hold the contract with the Department of Health for the NIHR funding for the DEPICT study. The study has four workstreams (quantitative analysis, qualitative and questionnaires study, health economic evaluation and mathematical modelling). Great Ormond Street Hospital have a collaboration agreement in place with all the various work stream lead centres including the University of Leicester (who lead Work Stream A -data linkage study), under the lead professor's leadership. This agreement relates only to the quantitative analysis workstream, which is led by the lead professor based at the University of Leicester. For this agreement Great Ormond Street and the University of Leicester are joint data controllers. Great Ormond Street Hospital in their role as lead for their study, and the University of Leicester in their role as lead for Workstream A. As Sponsor of the study, Great Ormond Street Hospital, through the Chief Investigator, have a responsibility for the conduct of the entire DEPICT study including Work stream A. The University of Leicester are essentially carrying out the data analysis of the linked data set, therefore will decide how the data is analysed. They will receive the study data and store it. Great Ormond Street Hospital will not receive or have access any data that has been received from NHS Digital. To undertake the analysis specified in the quantitative workstream, the University of Leicester will have access to pseudonymised linked data. The sources of data are: 1) Paediatric Intensive Care Audit Network (PICANet) audit data from the University of Leeds. This audit is commissioned by the Healthcare Quality Improvement Partnership (HQIP) and University of Leeds is a data processor for the audit data. There has and will not be any involvement from University of Leeds or HQIP in the design or performance of the DEPICT study, in the study itself or this agreement. 2) Case Mix Programme (CMP) audit data from Intensive Care National Audit and Research Centre (ICNARC). There has and will not be any involvement from ICNARC in the design of the DEPICT study, in the study itself or this agreement. 3) Hospital Episode Statistics from NHS Digital. 4) Office of National Statistics mortality data from NHS Digital. 5) Patient Episode Database for Wales (PEDW) data from NHS Wales Informatics Service (NWIS). For both the audit datasets (PICANet and CMP), the University of Leicester approached HQIP and ICNARC to access and process their audit data for the purpose of Workstream A of this study, and this access has been agreed. Neither HQIP, ICNARC nor the University of Leeds have had or will have any further involvement in this study and, therefore, play no role in the design or performance of the project, and do not have access to any of the data to be disseminated by NHS Digital under this agreement. They will, however, receive study IDs only from the University of Leicester. The legal basis for dissemination: is: - Mortality data: Statistics & Registration Service Act S42(4A)(A) - Dissemination of data: Health and Social Care Act - 261(1) 261 (2)(b)(ii). The University of Leicester want NHS Digital to identify common records in the two audit datasets (PICANet and CMP) and link PICANet identifiers to HES and mortality datasets. Where common CMP records have been identified, the CMP unique identifier will be added to that record also. The University of Leicester will be the only organisation to access the record level data supplied from NHS Digital, as this is where the statistical team for the DEPICT Workstream A study are based. No other organisations will have access to the data received from NHS Digital. The University of Leicester is part of the DEPICT study collaboration and is leading the quantitative data analysis workstream. The DEPICT study is funded by the NIHR HS&DR programme (ref: 15/136/45). The DEPICT Study has three main aims: 1) Understand whether and how a) clinical outcomes and b) experience of critically ill children (and families) transported to PICU are affected by national variations in timeliness of access to care and care provided by transport teams before PICU admission. 2) Study the relative cost effectiveness of the current transport team and evaluate alternative methods of service delivery. 3) Provide evidence for the development of future clinical standards. The objective of the DEPICT study (see Aim 1a) is to investigate how the clinical outcomes of critically ill children who are transported to paediatric intensive care are affected by national variations in timeliness of access to intensive care. The primary outcome of interest is 30-day mortality and the secondary outcomes are: mortality in intensive care, at 90 days and within a year of admission; length of stay; resource use; number of hospital admissions and days in hospital in the 12 months following admission. In order to achieve these outcomes, the University of Leicester require linkage of PICANet audit data to HES and mortality data and the common records between PICANet and CMP to be flagged; this is so the outcomes of paediatric patients seen in both a PICU and other specialist intensive care units as part of their care can be analysed and a fuller picture of the cohort obtained. Under this agreement, the only organisation permitted to access and process the data provided by NHS Digital is University of Leicester.

Yielded Benefits:

To date there has been no yielded benefits from this study. University of Leicester are currently undertaking the statistical analysis as outlined in the original application and they anticipate completing the initial statistical analysis in Autumn 2019.

Expected Benefits:

The DEPICT Study addresses an important clinical problem related to the care of acutely ill children in the NHS. The study will provide important information about the differences which may exist between the different paediatric transport services and the outcomes experienced by children. This is particularly important since current national standards from the Paediatric Intensive Care Society (PICS) are expert consensus derived rather than being evidence based. The main areas of uncertainty addressed by the DEPICT study are: 1. Provision of early, high-quality acute care has been shown to improve clinical outcomes in specific diseases such as paediatric sepsis and head trauma but it is unclear how these findings apply to the vast majority of critically ill children who require stabilisation and transport to a PICU. We will examine whether and how timeliness of access to paediatric intensive care and care delivered during acute stabilisation and transport affect clinical outcomes of critically ill or injured children with a range of diagnoses and pre-existing medical conditions, so that findings can be generalised to all critically ill children. 2. Centralisation of specialist acute care has occurred in several NHS services such as stroke, trauma, and specialist paediatrics. The findings from our research can provide evidence that can be generalised to evaluate other such centralisations. This is especially relevant to questions related to the trade-off between timeliness of access to acute care and provision of high quality cost effective specialist care. 3. Evidence is urgently required to understand whether and how delays in access to paediatric intensive care and variations in the quality of care provided during acute stabilisation and transport affect clinical outcomes. This study will provide definitive outcome information about critically ill children who receive specialist transport to paediatric intensive care. Development of the transport services and their related PICS standards of care have been driven by expert opinion but these have lacked scientific evidence. It will allow different transport services to compare their service with other services in the country, whilst accounting for the differences in populations and sickness of the children they transport, and will identify inequalities in access and timing of care. The DEPICT study will generate the high-quality evidence necessary to guide the development of future standards of care for the transport of critically ill children and inform decisions about the associated national policy. This work will be completed by the conclusion of the study in 2022.

Outputs:

The results of the study will be disseminated actively and extensively. The research team has strong links with (a) the PICU community via the Paediatric Intensive Care Society (PICS), PICS Study Group (PICS-SG), and the NIHR CRN: Children Clinical Studies Group (CSG) in Anaesthesia, Intensive Care and Cardiology; (b) the PICU Transport community through the PICS Acute Transport Group; (c) the Healthcare Quality Improvement Partnership national audit programme through the Paediatric Intensive Care Audit Network (PICANet) and Intensive Care National Audit and Research Centre (ICNARC) Case Mix Programme; and (d) NHS England. The DEPICT Study team plan to write six peer-reviewed publications related to the study aims. A recent paper describing the background to the DEPICT study was published in Paediatric Critical Care Medicine (Feb 2018). An peer-reviewed publication describing the DEPICT study’s initial findings will be submitted within 12 to 18 months of beginning the work. The intention is to publish the findings in high-impact journals and these will be made open-access. A final report overviewing the entire project will be published in the National Institute for Health Research (NIHR) Health Services and Delivery Research journal (funders of this research) by the end of the study (May 2020). CLINICIANS AND ACADEMICS: Clinicians in the study steering group will be drawn from all transport services in the UK, and will ensure wide dissemination of the results to frontline clinicians. The findings from the work will be presented at national and international conferences, potentially including the Annual Conference of the Royal College of Paediatrics and Child Health, the World Congress of Paediatric Intensive Care, the PICANet Annual Meeting, the Society of Critical Care Medicine Annual Congress, PICS Annual Scientific Meeting, American Association of Paediatrics Conference, the European Society of Paediatric and Neonatal Intensive Care, and British Association of Critical Care Nurses (BACCN). Dissemination at conferences will occur throughout the course of the DEPICT study (2019-2022). POLICY MAKERS: Recommendations for clinical guidelines arising out of the research will be published and disseminated to professional societies concerned with the care of children presenting with acute illness, including PICS and the Royal College of Paediatrics and Child Health. Our strong links with service managers and NHS commissioners will allow our findings to be disseminated to national policy makers, especially through the PIC Clinical Reference Group. Presentation slides will be prepared for use by the study team or others in disseminating the research findings. The timescale for this will also be throughout the course of the DEPICT study (2019-2022). PUBLIC: The results of the study will be disseminated to patients and their families, facilitated by the co-applicants, members of the research team who have links with PICS and the NIHR CSG, and via The PICANet Families Group who we have liaised with already. Findings will be made available via the DEPICT Study website (https://depict-study.org.uk/) which will make all results publicly available. These will also be promoted via social media (Twitter @DEPICT_Study). We will ensure that lay summaries are provided (reviewed in collaboration with parents involved in this research). Where appropriate, results will be promoted as press releases. (2019-2022). Outputs will contain only aggregate level data with small numbers suppressed in line with HES analysis guide

Processing:

The data flows are as follows: 1) Data flows to NHS Digital University of Leeds (PICANet) and ICNARC (CMP) will each securely transfer a file to the NHS Digital Data Access Request Service (DARS). These files will contain person-identifiable information (NHS Number, sex, post code, date of birth) and unique study identifiers (PICANet: DEPICT Study Number; CMP: CMP identifier) required to perform the data linkage. 2) NHS Digital will identify common records between PICANet data and CMP data 3) Data flows from NHS Digital - NHS Digital will supply a list of the study identifiers common to PICANet and CMP to University of Leicester - NHS Digital will provide HES data for all individuals in the PICANet cohort to the University of Leicester. The unique study identifiers (DEPICT study number and CMP identifier, where applicable) will be appended to the end of every episode record provided to the University of Leicester. - Mortality data for all individuals in the PICANet cohort will be provided to the University of Leicester. The unique study identifiers (DEPICT study number and CMP identifier, where applicable) will be appended to the end of every episode record provided to the University of Leicester. 4) Data flow from University of Leicester University of Leicester will securely transfer DEPICT study numbers and the unique CMP study identifiers for the records that were identified as been in common by NHS Digital to University of Leeds and ICNARC respectively. No HES or mortality data or any other personal identifiable data will be transferred. This information is shared so that clinical data for the records in common can be securely transferred from both PICANet and ICNARC to the University of Leicester for inclusion in their analysis. 5) Data flow from University of Leeds (PICANet) and ICNARC (CMP) University of Leeds (PICANet) and ICNARC will provide clinical data from their respective audits for the specific DEPICT and CMP records in common identified by NHS Digital to the University of Leicester by means of secure transfer. No personal identifiers will be transferred. All statistical analyses will be undertaken at the University of Leicester. The complete study dataset will only be accessed by two individuals employed by the University of Leicester for the statistical analyses. All organisations party to this agreement must comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data). The datasets required by the DEPICT Study team from NHS Digital are mortality and HES data. Data will be required from 2012/13 to 2017/18 to allow investigation of mortality and details about re-admission to A&E or hospital up to one year after the initial admission to paediatric intensive care. Data is only required on individuals aged <19 years to follow up children who required paediatric intensive care. There will be no requirement nor attempt to re-identify individuals from the data. National data is required to allow comparison of the different specialist transport services across the country. The results of all analyses will be published in aggregate form, with small numbers suppressed in line with HES guidance. No identifiable data will be held by the University of Leicester; therefore, no identifiable data will be released. Linked study data provided by NHS Digital will be used by the Workstream A team at the University of Leicester to achieve the primary and secondary study aims, i.e. investigate if differences exist in PICU mortality, or at 30 days, 90 days or one-year post-admission or if differences exist in re-admission to hospital and subsequent care in hospital following discharge. The DEPICT Study has the relevant Research Ethics and Section 251 approvals. Under this agreement, the only organisation permitted to access and process the data provided by NHS Digital is University of Leicester’. There will be no data linkage undertaken with NHS Digital data provided under this agreement other than that which is specified.