NHS Digital Data Release Register - reformatted

University of Surrey

Project 1 — DARS-NIC-21083-B6C5J

Opt outs honoured: Yes - patient objections upheld (Statutory exemption to flow confidential data without consent)

Sensitive: Non Sensitive, and Sensitive

When: 2020/05 — 2020/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Categories: Identifiable

Datasets:

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

Objectives:

Public Health England (PHE) holds a contract with the Royal Collage of Practitioners (RCGP) who in turn hold a contract with the University of Surrey to deliver information to support surveillance and monitoring of vaccine efficacy on Influenza. PHE, RCGP and University of Surrey are Joint Data Controllers for this request. They require HES and Civil Registration Data (CRD) to look at the outcomes of care, including death to support surveillance and monitoring of vaccine efficacy on Influenza. Most important health outcomes happen in hospital, hospital is where the bulk of health care costs are incurred. The focus of the work will be the impact of influenza and other infections on health the benefit-risk of influenza and other vaccinations. The Royal College of General Practitioners (RCGP)Research Surveillance Centre (RSC), is based at the University of Surrey. The University of Surrey will have access to the record level data supplied by NHS Digital under this agreement. The University of Surrey will be the only organisation who accesses and processes the data disseminated under this agreement. The GDPR Lawful basis for processing the requested data under this agreement are; Public Health England; Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller) and Article 9(2)(h) (processing is necessary for the purposes of preventive or occupational medicine, for the assessment of the working capacity of the employee, medical diagnosis, the provision of health or social care or treatment or the management of health or social care systems and services) and Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices) PHE exist to protect and improve the nation's health and wellbeing, and reduce health inequalities. RCGP; Article 6(1)(f) processing is necessary for the purposes of the legitimate interests pursued by a controller, except where such interests are overridden by the interests or fundamental rights and freedoms of the data subject which require protection of personal data, in particular where the data subject is a child. This shall not apply to processing carried out by public authorities in the performance of their tasks. 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices) University of Surrey; Article 6(1)(e) (Public Task processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller) and Article 9(2)(i) (processing is necessary for reasons of public interest in the area of public health, such as protecting against serious cross-border threats to health or ensuring high standards of quality and safety of health care and of medicinal products or medical devices). Additionally the request for data is supported by PHE as they have an emanation of the Secretary of State for health and social care, to both self-approve the use of Regulation 3 and to grant this approval to third parties processing confidential patient information without consent for purposes that fall under the scope of Regulation 3. This authority to has been in existence since PHE was established in 2013 although the large majority of the Regulation 3 approvals granted since that date have been internal to PHE; only a very small number have been granted by PHE to third parties. Specifically the work being undertaken under Reg 3 in this application is limited to Communicable Disease surveillance and other risks to public health’. This secondary care data being requested will be linked at individual level to the Royal College of General Practitioners (RCGP) Research and Surveillance Centre's (RSC) primary care sentinel data for the purposes of infectious and respiratory diseases surveillance in England’. These include feeding back to member practices about their quality of care through a practice dashboard. The key objectives of the work are to: (1) Monitor influenza; (2) Analyse influenza vaccine effectiveness; (3) Understand and predict the impact of influenza and other winter infections on health service utilisation (e.g. older people with co morbid illness may be more likely admitted to hospital. Primary care/general practice data (which is already held) is rich in terms of diagnosis and information about the process of care. However, HES and CRD data provides key information about the outcomes of care (A&E use, hospitalisation and death data) The University of Surrey have an established sentinel GP influenza surveillance scheme in over 270 practices across England that monitors Influenza-like-illness and a subset who take virology swabs with the purpose of virologically confirming infection. The University of Surrey have a great deal of experience in using health related data to monitor infectious illnesses. Accessing HES and CRD data will allow the University of Surrey to expand their knowledge about the impact of infectious diseases further; this will both be at the individual patient risk level as well as looking how the University of Surrey could better predict winter pressures on the NHS to support PHE and RCGP. Public Health England (PHE) is involved in this programme of surveillance and quality improvement. PHE is a large organisation whose main aim is to protect and improve the nation’s health and reduce inequalities. The RCGP RSC and PHE have worked together for over 50 years to monitor the progression of infectious illnesses in order to put any action plans in place if needed. PHE are funding this surveillance and quality improvement being undertaken through this agreement. Individual patient level data is required because this allows much more precise statistical analyses to be made, compared with just comparing aggregate data. The main aim of this project is to build a robust database and reporting system using up-to-date primary and secondary care data at the individual patient level, which can be easily queried; and has the likely variables required for PHE reports outlined in the specific outputs section. The database will contain the following variables for each patient (where present): • Influenza-like-illness appointments: including information on whether or not a virology swab was taken and the outcome of the swab • Data for the other 32 conditions monitored by University of Surrey as contracted by RCGP RSC on behalf of PHE • To provide national surveillance data about an outbreak or pandemic that was not predicted • Vaccination status: date of vaccination, type of vaccination • Co morbid conditions • Medication which may be associated with better or adverse outcomes. • A & E visits • Inpatient appointments, including critical care • Outpatient appointments • Mortality data (if applicable). The database will be used to answer the many associated questions exclusively related to surveillance and monitoring of vaccine efficacy on Influenza. For example, gaining access to HES and CRD data means that the University of Surrey can clearly see the rates of patients who access health care because of influenza related conditions. This will enable the University of Surrey to assess the pressure that is put on the healthcare system during influenza seasons, and devise and test measures to prevent this. Another example relates to comorbidities of disease, reducing the rates of influenza nationwide is of public health interest as influenza can be particularly dangerous for those in high risk groups. HES and CRD data will be used to identify the incidence of flu in those with certain conditions, such as pregnancy or diabetes. This will enable the University of Surrey to identify whether certain conditions are associated with an increased risk of catching influenza, and may lead to individuals with certain conditions being offered vaccinations in future influenza seasons. A further example relates to vaccine effectiveness. The RCGP RSC system is also used to monitor the effectiveness of influenza vaccine on behalf of PHE each season. PHE make decisions about England’s vaccination programme, and the data the RCGP RSC provides to PHE informs their decisions on future influenza vaccinations. The data provided under this agreement will be used to see whether anyone with certain conditions, who are vaccinated, are less likely to use hospital services than those who have not been vaccinated. This will provide further information on vaccine effectiveness in individuals with certain conditions. The data will be used to support University of Surrey, RCGP and PHE in understanding more about the primary and secondary care data at a patient level for the following conditions; URTI – Upper respiratory infections LRTI – Lower respiratory infections (pneumonia and acute bronchitis) Asthma and COPD These peak as flu circulates and not all flu is diagnosed as flu therefor looking at these conditions will support the influenza overall programme. Both CRD and HES data will be required: • HES: Critical Care • HES: Outpatients • HES: A&E • HES: Admitted patient care • CRD (mortality) data Since the outbreak of COVID-19 in Wuhan, China, the surveillance programme have been working closely with and under instruction from Public Health England (PHE) and other national bodies to closely monitor and make plans to deal with any situation that may develop in the UK. A vital part of that will be to monitor the number of suspected COVID-19 cases in the community in a timely way. PHE has commissioned the RCGP Research Surveillance Centre to incorporate monitoring of COVID-19 into its virology surveillance scheme. RCGP RSC and PHE will be extending the surveillance to include COVID-19. 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 ie: employees, agents and contractors of the Data Recipient who may have access to that data).

Expected Benefits:

The surveillance work conducted by the RCGP RSC on behalf of the Data Controllers is used by Department of Health, NHS England and PHE to monitor trends in a number of infectious conditions. Specifically for influenza, seasonal epidemics are carefully followed, in order to deploy necessary measures as needed to limit the impact on the population. The trends in other conditions inform the development of vaccination programmes or other public health measures. Linking with HES and CRD data can help assess the severity and mortality of a given condition, thereby alerting PHE on whether larger measures should be implemented. This could lead to improved healthcare and reduced mortality of certain conditions. Additionally, the link with the HES and CRD data allows The University of Surrey to identify whether a particular flu season is putting additional pressures which means that plans can be out in place in order to prevent or deal with these pressures next season. Specific benefits The benefits include improved knowledge of the pressures of certain conditions during the winter period, reduced mortality from influenza, improved vaccine effectiveness and a health system that is more prepared in the event of an influenza outbreak. Magnitude of benefits It is expected that these benefits will be nationwide across England, to both patients and staff working in the health care system. Sequence of events needed to take place in order for benefits to be achieved: 1. Pseudonymised matching and then HES and CRD mortality data are linked with the data the University of Surrey hold at the RSC 2. The University of Surrey analyse the data and identify trends in rates of illnesses, hospital use and mortality in certain groups (i.e. pregnant women, older people, and people with co morbid conditions) 3. The University of Surrey alert PHE and the Chief Medical Officer of the findings who will then evaluate the evidence and make health care plans that are in the best interest of the nation’s health. For example, from the data provided by HES and CRD, PHE might identify that certain conditions are associated with higher influenza rates, and therefore the possibility of extending the vaccination programme to this condition might be examined. The RSC and PHE have been working together for many years, to improve the nation’s health. University of Surrey has become important in the process from March 2015 the secure network was established at University of Surrey. The work is funded by PHE and the University of Surrey's work has previously been used to influence practice. For example, if high rates of influenza are circulating the University of Surrey will inform the Chief Medical Officer who will then make a decision about whether or not to dispense anti-viral medications at hospitals and general practices.

Outputs:

The purpose of linking HES, CRD, and primary care data is to implement a wider and more accurate sentinel surveillance of infectious diseases in England. The main outputs of the RCGP RSC’s surveillance work, which is funded by Public Health England (PHE) are as follows: • The RCGP RSC weekly report is circulated to a selected list of recipients on Wednesdays and it is publicly available on Thursdays at 2 pm at the RCGP RSC website (http://www.rcgp.org.uk/clinical-and-research/our-programmes/research-and-surveillance-centre.aspx). This report currently covers incidence rates of 37 infectious and respiratory conditions in England. It is expected that, in future, hospitalisation trends will be included. This is incorporated into the syndromic surveillance carried out by PHE on a daily basis, which allow them to determine any urgent priorities for local health protection teams. • Similar to this, an annual report is published covering the annual trends of the 37 conditions. Each year, this report has a new theme which is explored in a paper submitted to a peer-reviewed journal (usually British Journal of General Practice). Themes explored include demographic disparities in disease presentation, higher rates of consultations for lower respiratory infections for boys, and urban/rural disparities of presentation. • In January of every year, the University of Surrey provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. This data extract contains details of influenza swabbing, chronic conditions, and vaccination status for each patient. It is hoped to be able to include details of emergency attendances or admission around influenza, pneumonia, or lower respiratory tract infection events. At the end of the flu season (varies from March to May), a second extract is provided updating the first, with data recorded after December. • The data from both of these extracts is used to estimate seasonal influenza vaccine effectiveness, stratified by comorbidities and demographics. HES data will allow the University of Surrey/PHE and RCGP to include the impact of any changes in effectiveness, assessed through changes in hospital admissions/emergencies due to respiratory conditions. The results are published at the mid-season and at the end of season stage, on the peer-reviewed journal Eurosurveillance. • Important results from either of these will be further analysed and presented at the RCGP annual conference, the PHE annual conference, and the PHE annual epidemiology conference. All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.

Processing:

Flows of data: • Data are extracted from practices that are members of the Royal College of General Practitioners (RCGP RSC) Research and Surveillance Network by Apollo. The University of Surrey subcontracts with Apollo to do this as part its contractual responsibilities. • The University of Surrey, on behalf of RCGP RSC, will provide NHS digital with a list of pseudonymised NHS numbers and date of birth for the cohort each quarter. • NHS digital will provide HES Critical Care, Outpatients, A&E, Admitted patient care and CRD data for the cohort to the University of Surrey each quarter for it to link these information to RCGP RSC data. • University of Surrey will store the data on the secure network. • University of Surrey will process and aggregate pseudonymised data to produce approved reports for surveillance (as part of the National surveillance process); and quality improvement. Detailed explanation of flows of data: a) Data flow from RCGP RSC network member practices to University of Surrey: Apollo extract the data from the practices. Patients who have opted out of data sharing do not have their data extracted, unless they have consented to a specific surveillance programme or study. This extract provides the study with information about patient’s visits to general practices including the date of the appointment, the reason for the visit and any relevant vaccination information. The University of Surrey also receive patient’s NHS numbers and date of births which are pseudonymised using SHA-512 algorithm. Detailed information about this algorithm is held in a separate location by IT services at the University of Surrey. This extract provides University of Surrey with a cohort of participants whose data will then requested from NHS digital. b) University of Surrey to NHS Digital: The University of Surrey securely transfers a file of identifiers (Pseudonymised NHS Number, date of birth, and Unique Study ID) to NHS Digital for all non-opt-out patients who are registered with RCGP RSC general practices. c) NHS Digital to University of Surrey: NHS Digital returns linked HES and CRD mortality data including the Unique Study ID and pseudonymised NHS numbers or date of birth to University of Surrey. d) University of Surrey Storage and processing of data: The data about patients registered with RCGP RSC general practices is stored on the secure server at the University of Surrey which can only be accessed from the University of Surrey. The data will be processed within secure network and dedicated analysis server of the Surveillance Group. The secure network is located behind a firewall within the University’s network, all in-bounded connections are blocked, but out-bounded connections are allowed. Patient level data are held in the database server within the RSC Group’s secure network. Pseudonymised data will be stored on the database server within the RSC’s secure network. The pseudonymisation algorithm is held in a separate location by IT services at the University of Surrey. e) University of Surrey process and aggregate pseudonymised data to produce reports. For example, University of Surrey on behalf of RCGP RSC provide a mid-season flu cohort to PHE with data up to the end of December. This is a fully pseudonymised patient-level extract collected by a PHE statistician using a secure drive. The University of Surrey also produce an end of season report, an annual report and weekly reports that are available to the public and use aggregated data on rates of infectious and allergic conditions. The RCGP RSC data is controlled and processed by a group of staff who are all based at the University of Surrey; all are mandated to complete information governance training. The group is made up of analysts, academic fellows, Structure Language Query (SQL) developers, RCGP RSC practice liaison officers, a project manager and a head of department. The team work from secure workstations or secure laptops with encrypted drives within the group’s secure network. Data will only be accessed by individuals within the RSC who have authorisation that are substantive employees of University of Surrey. The authorisation process includes: (1) Contractual requirement to follow IG principles; (2) Using the email registered with Human Resources to complete IG training and to return the certificate; (3) Staff’s email is authorised by the IT department for one year to access the secure network and staff’s computers are configured to allow this; (4) At any point the project managers or Head can have access to the secure network turned off. There is special authorisation to have access to the main database. Only three SQL developers and one senior project manager can access the main database. Surveillance databases are created for approved analyses once they have been agreed by the RCGP RSC approval committee. This agreed protocol includes the list of variables required for the database. The SQL developers create separate databases for individual projects only including the required variables, for the required time interval. The HES and CRD data will be linked with the data that the University of Surrey already receives from the RCGP RSC network practices and PHE reference laboratories. The linkage between secondary and primary care data would happen via linking pseudonymised NHS numbers in both sets of data. The University of Surrey have used this process for previous projects linking different sets of data, and the linkage has been successful, provided both parties use the same pseudonymisation algorithm (SHA-512). There will be no requirement nor attempt to re-identify individuals from the data. The data will not be made available to any third parties other than those specified except in the form of aggregated outputs with small numbers suppressed in line with the HES Analysis Guide. Historic data are needed because longitudinal data better enable the RSC to predict what might happen in the future; even a small increase in the ability to understand flu and its associated morbidity and mortality would offer benefits for patients and the NHS. Both historical and future data are needed in order to build a robust database and reporting system using up-to-date primary and secondary care data at the individual patient level, which can be easily queried. This will enable the study group to answer a wide range of questions which will have an impact on the provision of health care in England. For example, the data will be used to answer questions posed by PHE, who make many decisions about healthcare, such as the vaccination programme, or preventative measures. The use of national data is needed as the University of Surrey are a national surveillance centre and the cohort are from across England. Practices are recruited to be nationally representative. Due to the potentially wide variety of adverse events that influenza can cause, it is not seen as appropriate to limit the data to specific health conditions/diagnostic codes or data types. For example, unexpected rise in scarlet fever and winter outbreaks of scabies are examples of unexpected increased incidence of diseases that has been followed. The use of pseudonymised NHS numbers are essential as the request to link HES and CRD data to the data that the University of Surrey already receives from the RCGP RSC network general practices and PHE reference laboratories.


Project 2 — DARS-NIC-203503-X7K8K

Opt outs honoured: N

Sensitive: Non Sensitive, and Sensitive

When: 2017/03 — 2017/05.

Repeats: One-Off

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

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

The Imperial College study team have recorded baseline characterisation of approximately 30,000 Indian Asian men and women aged 35-74 years and free from clinically manifest cardiovascular disease (CVD), in the London Life Sciences Prospective Population (LOLIPOP) study. LOLIPOP aims to precisely calculate the increased vascular risk for British Asians. Health economic analysis of the introduction of the CVD risk prediction calculator for use in Indian Asians will be performed as well as a qualitative study to evaluate the utility and acceptability to general practitioners and individuals of implementing the CVD risk prediction model in general practice. In parallel University of Surrey will develop models and conduct an economic evaluation to examine the cost-effectiveness of using the new risk estimator to detect the number of Asian men at risk. This includes the costs of identifying the cohort using the new risk estimator and putting them in a preventative scheme, and the benefit, both in terms of improved health outcomes and associated reduced health care costs

Expected Benefits:

The high CVD morbidity and mortality amongst the Asian population compared to Europeans represents a significant health inequality which needs to be explored, explained and addressed. Currently the precise risk is not known, so the costs effectiveness of a possible greater intensity of cholesterol, blood pressure and other interventions can’t be defined. Inclusion of enhanced treatment in national and international guidelines generally requires demonstration of cost effectiveness. By precisely calculating risk the University of Surrey will enable cost-effectiveness of any enhanced intervention to be determined. The current recommended method for risk prediction is NOT adequate for this group and uncertainty of risk leads generally to standard guidelines being applied and the consequent under-treatment widens the inequalities in CVD outcomes for this population. Some patients may also be inappropriately over treated where individual clinician approximate additional risk. This study has received a large investment from the NIHR, through a competitive, peer reviewed application process, to produce results of the highest standards to ensure this issue is addressed. The results will be used to derive a new model for CVD prediction for British Asians and this will be disseminated into routine clinical care. This research will result in clinicians being able to make informed decisions on how aggressively to treat this group as a whole, or specific subgroups (e.g. people with diabetes). Preventative treatment will benefit health care both in terms of improved health outcomes and associated reduced health care costs.

Outputs:

All outputs will be aggregate with small numbers suppressed in line with the HES Analysis guide. The outputs from this research will be published in major scientific journals. Target journals include the Lancet and New England Journal of Medicine. It is anticipated that the outputs will directly impact national guidelines in the preventative management regimes implemented for public health as well as in primary and secondary care. This is likely to be in place within two years of publication. Outputs will also directly impact the treatment of the study participants as well as the needs of the west London community for education and service development. There have already been many publications from the LOLIPOP study team including; 1. Coronary heart disease in Indian Asians. Tan ST, Scott W, Panoulas V, Sehmi J, Zhang W, Scott J, Elliott P, Chambers J, Kooner JS. Glob Cardiol Sci Pract. 2014 Jan 29;2014(1):13-23. doi: 10.5339/gcsp.2014.4. Collection 2014. PMID: 25054115 2. 6. Prevalence of coronary artery calcium scores and silent myocardial ischaemia was similar in Indian Asians and European whites in a cross-sectional study of asymptomatic subjects from a U.K. population (LOLIPOP-IPC). Jain P, Kooner JS, Raval U, Lahiri A. J Nucl Cardiol. 2011 May;18(3):435-42. doi: 10.1007/s12350-011-9371-2. Epub 2011 Apr 9. PMID: 21479755 3. 9. Ethnicity-related differences in left ventricular function, structure and geometry: a population study of UK Indian Asian and European white subjects. Chahal NS, Lim TK, Jain P, Chambers JC, Kooner JS, Senior R. 4. A replication study of GWAS-derived lipid genes in Asian Indians: the chromosomal region 11q23.3 harbors loci contributing to triglycerides. Braun TR, Been LF, Singhal A, Worsham J, Ralhan S, Wander GS, Chambers JC, Kooner JS, Aston CE, Sanghera DK. PLoS One. 2012;7(5):e37056. doi: 10.1371/journal.pone.0037056. Epub 2012 May 18. PMID: 22623978

Processing:

The University of Surrey are conducting a first full follow up of the participants in the LOLIPOP study and therefore need access to data from all the patients from the cohort that have been in the study for the past 10 years. Both HES and ONS data will be linked to cohort data to maximize the identification of their CVD outcomes (stroke, advanced coronary artery disease and myocardial infarction) to allow a more rigorous evaluation. Particularly as many people may have moved away from northwest London. NHS Digital will use the consented cohort already flagged under MR1143 to link to the requested data. The University of Surrey would receive a pseudonymised output from the HSCIC, which will be encrypted so re-identification cannot take place. No record level data will be provided to third parties and none of the data will be used within any commercial tool or product or for commercial gain. Only substantive employees of the University of Surrey will have access to the data and only for the purposes described in this document.


Project 3 — DARS-NIC-195793-R5Y3H

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

Sensitive: Non Sensitive, and Sensitive

When: 2020/03 — 2020/03.

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
  • Civil Registration - Deaths
  • HES:Civil Registration (Deaths) bridge

Objectives:

The University of Surrey and the Royal College of General Practitioners (RCGP) are working together as joint data controllers to look at preventing Venous thromboembolism. The Royal College of General Practitioners legitimate purpose through the use of the data is to provide information and analysis on general practice data – both disease and workload Project specific: To understand the impact of mandatory venous thromboembolism (VTE) risk assessment on the incidence and outcomes of VTE after surgery. The benefits to patients is to improve the understand the impact of mandatory venous thromboembolism (VTE) risk assessment on the incidence and outcomes of VTE after surgery (Patient Care) There are benefits to national bodies through the • Provision of national surveillance information for Public Health England • Provision of workload and workforce breakdown (influence policy) for NHS England • Project specific: To understand the impact of mandatory venous thromboembolism (VTE) risk assessment on the incidence and outcomes of VTE after surgery (Policy implications) The processing of the data will help the study to provide surveillance services based on general practice electronic healthcare records. Project specific: data from general practice is required to fill in the gaps in the current understanding of the incidence and outcomes of mandatory VTE risk assessment after surgery as currently much of the existing information is from secondary care. RSC data is required to identify where VTE has occurred once a patient has left hospital. No additional processing outside of what is required is approved by the RSC and all amendments have been made to ensure that data is processed in the least intrusive way possible while still enabling the purpose of the RCGP RSC Data is pseudonymised as close to the source as possible, the RCGP RSC does not hold or process any identifiable personal data. There are no existing relationships that can be identified with the individuals whose data is processed. All data is pseudonymised, In this application, the University of Surrey will be studying a comparable-sized population of about 3 million individuals from the Royal College of General Practitioners Research & Surveillance Centre (RCGP RSC) database. Over seven years they expect to see about 450 VTE events from approximately 78,000 surgical procedures (ie prior to mandatory screening). With 61,506 surgeries before, and 61,506 surgeries after the introduction of VTE guidelines, there is 80% power to detect a 10% reduction in VTE events from 23.7/1000 years to 21.3/1000 years. The concept to use preventive measures to prevent Venous thromboembolism (VTE, also known as 'blood clots') for specific at-risk groups is well established (Haut et al, 2013). There are significant risks to medications that reduce clotting of the blood and so determining the risk-to-benefit ratio is essential to ensure that prevention is targeted appropriately. The National VTE prevention programme was launched in 2010 with the introduction of mandatory VTE risk assessment of all adults on admission to hospital. This was supported by NICE guidelines. Where patients are at increased risk of VTE (ie the risk is NOT outweighed by risk factors for bleeding), then NICE recommend mobilisation of the patient as soon as possible, medicines to limit clotting and compression stockings. Patients are also given information of the risk of blood clots and discharge planning includes relaying this information to other care-givers. The risk of VTE persists for up to 12 months after surgery, and is particularly high in the first three months (Kearon, 2003; Sweetland et al, 2009). This risk was estimated before the era of Enhanced Recovery After Surgery (ERAS) which may change the natural history of the disease. ERAS is a package of care that mean patients stay in hospital is much shorter than it once was. In the modern era, in the UK the length of stay for bariatric surgery is less than three days (Awad et al, 2014) and for thyroidectomy is just two days (Perera et al, 2014), for example. Studies evaluating HES have estimated postoperative VTE rates in varicose vein (Sutton et al, 2012), urological (Dyer et al, 2013) and orthopaedic surgery (Jameson et al, 2010). However, data from hospitals (Hospital Episode Statistics, HES) by itself is limited to capturing in-hospital adverse events and those recorded during readmission. It is evident that the risk of VTE persists well beyond discharge from hospital. For instance, a study by Bouras and colleagues showed that a large proportion of postoperative VTE was detected in primary care (2015). Linkage to primary care electronic health records and mortality data will allow for a more accurate perspective of a patients’ entire postoperative course. Mortality is obviously a key clinical outcome after surgery and would be recorded in hospital-derived data but if it occurs in the community, has been shown to be not well recorded through clinical coding in primary care. Linkage between NHS Digital data and the primary care record will be made via a pseudonymised NHS number. No patient identifiable information will be seen or used by Apollo Medical Software Solutions (the company that facilitate data extraction at the GP surgeries) or anyone at University of Surrey and the RCGP. The aim of this study is to examine the impact of mandatory VTE risk assessment (introduced in 2010) on the incidence of VTE after general surgery and major orthopaedic surgery. Patients undergoing one of twelve general surgical procedures will be chosen. Limiting to twelve operations allows the study to standardise for operative duration, likelihood of postoperative immobilisation etc. These procedures represent the majority of emergency and elective general surgical operations in UK hospitals. In terms of the number of years of data required, it is necessary to have data over such a long period because in the paper by Bouras et al (PLoS ONE 2015) there were 981 VTE events captured within 90 days of surgery, in 168005 procedures, from a background population of ~2.9 million people over 15 years (23.7/1000 patient-years). The period of time that the Bouras study relates to was 1997 to 2012. Importantly, this crosses the introduction of mandatory VTE risk assessment and so the paper cannot describe the effect of mandatory screening. Orthopaedic sub study It is hypothesized that an individual’s VTE risk after hip or knee surgery can be modelled with the use of a mathematical prediction model. Study Objectives: To develop a model that predicts the risk of VTE in patients who undergo total hip arthoplasty (THA, 'hip replacement') or total knee arthroplasty (TKA, 'knee replacement') surgery. This will be based upon data of the clinical characteristics of the individual as well as data of the operation itself and routinely collected hospital biochemical (laboratory) data. The Research question is therefore: What is the optimal prediction model for VTE risk following THA and TKA surgery? Expected results and influence in society: Current strategies to prevent blood clots are a one-size fits all -ie for all patients who undergo THA and TKA - these are not optimal because patients vary hugely in their ability to form blood clots. Therefore a new strategy, i.e., advice on an individual basis, is necessary to reduce VTE, bleeding complications and costs. A prediction model should be able to reach a discriminative value (area under the curve) of at least 0.7 with a sensitivity of 75% (in other words, detects at least 75% of those with blood clots) and specificity of 50% (in other words, detect at least half of people who do not have blood clots). Ideally, three risk groups could be identified according to the prediction model; a low- (60% of the total), intermediate-(30%) and high-risk (10%) group. These risk groups could consequently be used to optimize strategies to prevent blood clots (thromboprophylaxis). For patients in the low-risk group (VTE risk <0.5%), thromboprophylaxis could be limited to in-hospital preventative treatment only, resulting in less costs and less bleeding events. For patients in the intermediate group (0.5-1.0%), current thromboprophylaxis policies (lasing for 2 to 4 weeks) may be sufficient; while patients in the high risk group (>1.0%) could potentially benefit from an extended period (or higher dosage) of thromboprophylaxis. However, before such a tailored strategy can be implemented in clinical practice, an additional impact-analysis has to be performed that measures the validity of the prediction model, and the usefulness in clinical practice. This current study will form the basis for this approach. For the orthopaedic sub study in this application, the two most common elective major orthopaedic surgeries (hip and knee replacement) have been chosen. In England and Wales (population 58 million) there are approximately 160,000 total hip and knee replacement procedures performed each year. From the population of 3 million in the RCGP RSC database, it would be expected that about 8300 surgeries occur per year ( in other words, about 17,000 over the two years requested). In patients who undergo total hip arthroplasty (THA) or total knee arthroplasty (TKA), 3.7% and 2.7% of patients will develop symptomatic VTE, respectively, despite use of preventative low-molecular-weight heparin (a drug used to thin the blood). This is considered the minimal data necessary upon which to build a predictive algorithm for postoperative VTE. Sanofi provide a research grant for this study and have no obligation to provide any other support for the study. University of Surrey is responsible for the initiation, management and conduct of the study. The Parties acknowledge that nothing in the funding agreement is provided as or intended to be an inducement to prescribe, purchase, recommend, use, or dispense any of Sanofi’s or its Affiliates’ products. University of Surrey is performing the study independently of Sanofi. Sanofi will have no control of nor in any way contribute to the conduct of the Study.

Expected Benefits:

The results are expected to inform the evaluation of the NHS policy on VTE risk assessment and thromboprophylaxis in the surgical populations studied. Understanding the impact of the VTE prevention programme and consequent VTE rates following surgical procedures will identify areas with scope for further improvement. Expected benefits will include length of stay, costs, complication rate after surgery and patient satisfaction. As an example, the orthopaedic substudy will enable VTE risk stratification of patients undergoing joint replacement (currently all are considered high risk). This will enable delivery of thromboprophylaxis only to those at very high risk (anticipated to be 50% of patients). Avoiding thromboprophylaxis in those at low risk will minimise adverse effects such as surgical site bleeding/ooze which predisposes to infection, which can adversely impact patient quality of life immediately post operatively and in the long term. Additionally, this represents a significant cost saving to the NHS. This will help inform best practice and guideline development in the continuum of care for joint replacement, as well as in general surgery. The data will be made immediately available to the National VTE Programme Board at NHS England (via a co-applicant of this study) - who is also a Director of the National VTE Exemplar Centres Network.

Outputs:

There are four key audiences for this research, these are: A. patients, the public, and health care practitioners B. commissioning organisations (such as Clinical Commissioning Groups and NHS England) C. external statutory organisations (such as Department of Health, NHS Information Centre, NICE) D. academia The outputs will be in the form of aggregate data tables, graphs, reports and papers for publication, with any small numbers suppressed (in line with the HES Analysis Guide). • The university of Surrey will work with the local Academic Health Science Network, who will advise and support routes for dissemination to the public. • Outputs to the public will be made via University of Surrey, University of Leiden and King’s College Hospital twitter feeds, Facebook and the media offices. Results of the study will be posted on www.clininfo.eu and University of Surrey webpages. • Publications including Full, Executive Summary and Plain English summary reports of the research will be made in peer review journals and local NHS newsletters. Journals may include, but not limited to: JAMA surgery, BMJ, British Journal of Haematology, Journal of Thrombosis and Haemostasis, Thrombosis research. • Wherever possible, publication will be made using a Creative Commons Licence. This will allow downloading the report, free of charge. Publications are made available on the University of Surrey library page, academics webpage and Researchgate.net. • Presentations at national and international haemostasis and perioperative conferences. • A Report of the study will be written for Sanofi (funding body) • There is a website for the National VTE prevention programme: vteengland.org.uk where the study will promote the findings. • Outcomes from the research will be included in future iterations of the guide to achieving CQUIN targets by King’s Thrombosis Centre, in conjunction with VTE Exemplar Centres. http://www.kingsthrombosiscentre.org.uk/kings/Delivering%20the%20CQUIN%20Goal_2ndEdition_LR.pdf • A co-applicant is the Director of the King's Thrombosis Centre and a Senior Medical Advisor to the National VTE Prevention Programme in England. Through this channel, the research outcomes will influence Department of Health, NICE guidance for thrmboprophylaxis. Expected Output of Research/Impact OUTPUTS 1. An understanding of the effect of mandatory VTE risk assessment, introduced in 2010 2. A risk prediction tool for VTE after orthopaedic surgery. IMPACT The approach to research and dissemination will: • Potentially reduce NHS costs through better assessment of VTE risk and through more accurate understanding of thrombosis risk after hospitalisation. • Provide findings to enhance the current evidence base for quality indicators and commissioning practices enabling commissioners and providers to make evidence based decisions to ensure maximum benefit to patients and the NHS • Contribute to national debates on the role of VTE thrombo-prophylaxis in driving forward improvements in patient care. Submission of manuscripts will be targeted for the end of 2019 / Spring 2020.

Processing:

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 ie: employees, agents and contractors of the Data Recipient who may have access to that data)” The study will only use and store pseudonymised information extracted by an approved third party provider, Apollo Medical Software Solutions. Each unique patient will be de-identified using a computer generated patient ID which could only be retraced by staff of the participating GP practices. The research team at University of Surrey will not view patient identifiable information in any form. Linkage between NHS Digital and the primary care data will be made via the pseudonymised NHS number. Apollo generates the hash key which then de-identifies all the patients in the server. This is passed onto the University of Surrey. University of Surrey will transfer the ‘hash’ algorithm to NHS Digital via Secure Electronic File Transfer (SEFT). The Hash algorithm is a one way encryption and can not be reversed so there is o ability for the pseudo data to be re-identified by University of Surrey. Record level HES data pseudonymised at source using ‘hash’ algorithm downloaded to the Research Group at the University of Surrey for linkage via SEFT. Pseudonomised record-level HES data will be processed and stored by the Research Group at the University of Surrey. Patient level databases are held in the database server within the Research Group’s secure network. The Research Group is made up of staff substantially employed by University of Surrey. The Research Group’s dedicated secure network is sited behind a firewall within the University’s network. It is a standalone – independent network, all in-bounded connections are block, but out-bounded connections are allowed. All staff members of the research group working within the team base work from secure workstations or secure laptops with encrypted drive. All staff members of the Research Group working within the team base work from secure workstations or secure laptops with encrypted drive within the Research Group’s secure network. The secure network is located behind a firewall within the University’s network, all in-bounded connections are blocked, but out-bounded connections are allowed. The Research Group has conducted a risk assessment of the physical security of the offices and servers where patient level data is kept, a copy of the risk assessment can be accessed: https://clininf.eu/wp-content/uploads/2017/02/Risk-Assessment-of-physical-security-V3.1-2016_18-signed.pdf A more recent review was carried out on the 2nd May 2019 which will soon be published. The hashed data provided by NHS Digital for this study will be downloaded by the Research Group. The Research Group will not have access to the identifiable data or the SALT key used for encryption. The University of Surrey will make no attempt to re-identify the data extract provided by NHS Digital under this agreement. The GDPR legal basis for the data processing is 'public interest', as medical research. There will be no additional data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the purpose. Data will only be accessed and processed by substantive employees of the University of Surrey and will not be accessed or processed by any other third parties.