NHS Digital Data Release Register - reformatted
University Hospitals Of Derby And Burton NHS Foundation Trust
Project 1 — DARS-NIC-391959-Q3C3G
Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)
Sensitive: Non Sensitive, and Sensitive
When: 2021/01 — 2021/03.
Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'
Categories: Anonymised - ICO code compliant
- HES:Civil Registration (Deaths) bridge
- Hospital Episode Statistics Critical Care
- Civil Registration - Deaths
- Hospital Episode Statistics Admitted Patient Care
The coronavirus disease 2019 (COVID-19) pandemic has caused significant morbidity and mortality and has affected some countries disproportionately. It has become evident that SARS-CoV-2 has shown variation in its virulence with some regions, within a country, more severely affected than others. In England, London and West Midlands the NHS were overwhelmed in the early period of the pandemic with increased in hospitalizations for pneumonia with multiorgan disease. As of 31st July 2020, the number of confirmed cases for COVID-19 have exceeded 17 million world-wide and 300,000 in United Kingdom with 46,000 deaths in UK alone. In UK, the pandemic reached its peak in mid-April with confirmed cases decreasing by end of May 2020. One of the most serious complications of COVID-19 has been kidney involvement, in the form of acute kidney injury (AKI) but the incidence of this has ranged widely in reports from different centres, between 5% to 57%. In the only report from UK, the incidence of AKI in COVID-19 was 26.2% which was much higher than a comparable cohort of people admitted with non-COVID acute illnesses (12.4%). However, no data have been published regarding variation in the incidence of COVID associated AKI within the UK. The medical community rapidly learnt lessons in the first wave of the pandemic, for example regarding the use of continuous positive pressure ventilation (CPAP) in case of respiratory distress and the use of regional anticoagulation in AKI needing continuous renal replacement therapy (CRRT). There was no effective treatment available at the start of the pandemic and this resulted in death rate rising sharply in England as well as many other countries. It has now become evident that there has been considerable variation in mortality in individual hospitals and there is urgent need to understand the reasons for this unwanted variation. As the country tries to recover from the pandemic, it becomes more important to learn lessons with regards to its strategy of tackling the disease. This learning can then be applied to a possible second spike of COVID-19 to help mitigate the impact and improve outcomes. The purpose of this study is to understand if variation exists in incidence and mortality in COVID patients and its complication namely, acute kidney injury, in England. The adjusted analysis will also focus on what are the causes of this variation from routinely collected data from rich source of hospital episode statistics (HES). This will help highlight areas of improvement and learning, for example, if the mortality in AKI in COVID patient is high in a particular District General Hospital (DGH), the analysis may help the DGH to look at the provisions to detect and manage AKI and nephrology services. Another example is that University Hospital of Derby and Burton Foundation Trust (UHDB)’s mortality in COVID patients was in top quartile in England it was highest in Midlands, though, Birmingham was worse hit. Without case-mix study, it is not possible to attain any learning of what were the factors which led to high mortality. Without this learning there is a risk of high mortality in COVID patients To address this gap in knowledge, University Hospital of Derby and Burton Foundation Trust wishes to undertake a two arm, retrospective, cohort study of hospitalised patients 18 years and over on 01/03/2002 identified from national data collected during routine care in the hospital settings in England between 1st March 2020 and 31st August 2020. The University Hospital of Derby and Burton Foundation Trust (UHDB) wishes to combine national data base of Hospital Episode Statistics (HES) for Admitted Patient Care (APC) with Critical Care (CC) and Mortality data over a period of four months to determine the regional incidence and case fatality (epidemiology) of hospitalised patients with COVID-19 disease in England. The UHDB will also investigate the association between patient characteristics and patient outcomes in patients admitted with COVID-19 and Acute Kidney Failure (AKI) and explore the various determinants of mortality. The primary outcome will be to determine in-hospital mortality in patients with COVID-19 disease and AKI in COVID-19. The secondary outcomes will include all-cause mortality, need for ventilatory support, admission to Intensive Care Unit (ICU), length of stay. PLEASE NOTE: Acute renal failure (ARF) has been replaced by new terminology, acute kidney injury (AKI), but due to lack of ICD-10 codes* for AKI, the ICD10 codes for acute renal failure will be requested and will be referred to as AKI in this agreement. *What are ICD-10 codes? ICD-10 is the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD), a medical classification list by the World Health Organization (WHO). It contains codes for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases. A handy look-up tool for ICD-10 codes can be found here: https://icdcodelookup.com/icd-10/codes DATA MINIMISATION USING ICD-10 CODES N17.0 for acute renal failure with tubular necrosis, N17.1 for acute renal failure with acute cortical necrosis, N17.2 for acute renal failure with medullary necrosis, N17.8 for other acute renal failure and N17.9 for acute renal failure, unspecified. The severity of AKI requiring dialysis will be identified by additional procedure code of X40.2 for peritoneal dialysis, X40.3 for haemodialysis, or X40.4 for hemofiltration, X40.5 for automated peritoneal dialysis and X40.6 for continuous ambulatory peritoneal dialysis in any of the 25 procedure codes. These codes have established biological and clinical plausibility and are widely used in acute kidney injury research. The study will consist of two arms of study: First arm: Epidemiology of COVID-19 in England All patients who are admitted to a hospital with COVID-19 infection between 1st March 2020 and 31st August 2020 and who meet following criteria will be included: 1) Diagnostic code for COVID-19 (U07.1) in any of the 20 diagnoses codes 2) Adult patients 18 years of age and upwards [those with a birth date on or before 01/03/2002]. Exclusion criteria: 1) Paediatric patients under 18 years of age [those with a birth date after 01/03/2002]. Second arm: Epidemiology of AKI in COVID-19 in England All patients who are admitted to a hospital with acute kidney injury (AKI) between 1st March 2020 and 31st August 2020 and who meet following criteria will be included: 1) Diagnostic code for AKI (N17) in any of the 20 diagnoses codes 2) Adult patients 18 years of age and upwards [those with a birth date on or before 01/03/2002]. Exclusion criteria: 1) Paediatric patients under 18 years of age [those with a birth date after 01/03/2002]. 3) Patients on chronic maintenance haemodialysis or peritoneal dialysis The record-level pseudonymised data for both arms of the study would be in one data extract with a flag to indicate one of 3 situations: 1. Positive diagnosis of Covid-19, AND AKI 2. Positive diagnosis of Covid-19, NO AKI 3. Negative diagnosis of Covid-19, AND AKI All episodes for each cohort individual will be required to ensure there is no survival bias in the analysis. - for the first part of the study, NHS Digital will identify all cases of hospitalised individuals with COVID-19 between 1st March 2020 and 31st August 2020 by using validated International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code of U07.1(COVID-19, virus identified) in any of the diagnoses codes, in keeping with the objective of the study. This will be the COVID-19 AKI cohort. - For the second part of the study, NHS Digital will identify hospitalised individuals with following ICD-10 codes for acute kidney injury (AKI) [as identified by ICD-10 code of N17 in any of the 20 diagnostic codes] between 1st March 2020 and 31st August 2020 will be included: N17.0 for acute renal failure with tubular necrosis, N17.1 for acute renal failure with acute cortical necrosis, N17.2 for acute renal failure with medullary necrosis, N17.8 for other acute renal failure and N17.9 for acute renal failure, unspecified. AKI patients requiring dialysis will be identified by additional procedure code of X40.2 for peritoneal dialysis, X40.3 for haemodialysis, or X40.4 for hemofiltration, X40.5 for automated peritoneal dialysis and X40.6 for continuous ambulatory peritoneal dialysis in any of the 25 procedures. The AKI cohort without COVID-19 will serve as AKI control. To exclude patients with chronic kidney disease starting dialysis, NHS Digital will exclude patients who had following codes: Z99.2 – dependence on renal dialysis, L74.2 - arteriovenous fistula or L74.3 - arteriovenous shunt during the inpatient admission. This algorithm has been shown to be sensitive and specific, with a high positive and negative predictive value (all >90%). For both arms of the study, the UHDB will obtain data on patient demographics, admissions and discharge details, hospital characteristics, in-hospital mortality, disposition, length of stay (LOS), deprivation decile and up to 20 diagnosis and 25 procedure codes that are based on the ICD-10-CM and OPCS-4 from the HES database. Data for critical care admission, discharge and organ support will be obtained from the linked HES Admitted Patient Care and Critical Care data set. Patients status at 30-day will be obtained from mortality data via the Civil Registrations (Deaths) - Secondary Care Cut data set. Patients will not be contacted. Data requested will be pseudonymised and no attempt will be made to re-identify patients. LEGAL BASIS The General Data Protection Regulation Article 6 (1) (e) and Article 9 (2) (j) are the legal basis for the processing of the data. Article 6 (1) (e) states that processing is necessary for the public interest. The purpose of this application is to determine the regional incidence and case fatality (epidemiology) of hospitalised patients with COVID-19 disease in England. The understanding gained from this data analysis will help to prevent this unwanted variation in second spike of COVID-19. This data will not be used for commercial purposes, will not be provided in record level form to any third party and will not be used for direct marketing. Only patients residing in England and Wales have been included in this study.
The COVID-19 pandemic has exposed the unwanted variation in COVID-19 outcome as evidence by Public Health England’s - and later NHS England's - report on COVID-19 Daily Deaths (https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-daily-deaths/) . For example, UHDB has reported high crude mortality as compared to other trusts in the region. Unwanted variation is care or outcome that is not consistent with a patient’s preference or related to their underlying illness. The King’s Fund has done some work in variation in care but not specifically to any disease process. The variation in outcome may be because of various reasons - differing underlying health conditions in the population, deprivation, physician preference and knowledge and ethnic diversity. Many clinical decisions seem to be subtly influenced by the availability of particular services: increasing bed availability, example is intensive care beds, is known to lead to an increase in admissions. This study will help to find if there is any association between COVID-19 mortality and the various factors which are being studied – age, gender, ethnicity, deprivation. In adjusted analysis if a region seems to have greater mortality, that will need further investigation. The data needs to be analysed to find which factors are associated with mortality and that may increase the understanding. The benefits of this study is that it provides new information to people, health care workers and policymakers on the difference in incidence, mortality and complication like AKI in COVID-19 infection in different parts of England. The study will also look at various factors associated with increase mortality in COVID-19 and incidence of AKI and its associated mortality. This new found knowledge will be useful at tackling health inequalities and minimising adverse events like AKI in patients with COVID-19 and mortality in AKI patients. The benefit extends to the NHS trust or regions who can then look at process of care for patients who have died to understand what changes they should make to reduce this unwanted variation. SPECIFIC STUDY BENENFITS 1) The study will establish if there is regional variation in mortality in COVID-19. 2) The study will assess if there is any associations between patient demographics, clinical characteristics, and associated chronic illness with mortality. 3) The study will assess if there is association between AKI and mortality in COVID-19 patients. 4) The study will highlight regions with higher adjusted mortality and will help Trusts to delve deeper into reasons of mortality by looking at process of care through case-note reviews. 5) The study will also evaluate the predictors of AKI in patients with COVID-19. This will help all the regions and the NHS trust to understand the unwanted clinical variation in outcome and make efforts to learn and reduce these unwanted variations in care and minimise the variation in outcome. It is important for policy makers, stake holders, medical professionals and patient and public themselves to understand the reason for these unwanted variations to minimise patient harm and reduce morbidity and mortality. The understanding gained from this data analysis may help to prevent this unwanted variation in second spike of COVID-19. Depending on the availability of data estimated target dates for analysis are: - Data will be reviewed and prepared for statistical analysis (3 months); - Analysis of data (1 month); - The results will be reviewed by research team and patient representative and any additional analysis may be performed (1 month); - Writing of manuscript and review by all researchers and patient representative (2 months); - Peer-review publications (6 months) Patient Involvement is in the form of a patient representative who has been involved in design and methodology of the study protocol. The patient representative has reviewed the protocol and will be involved in the analysis of the results. The results will be disseminated through patient organizations like the National Kidney Foundation.
The University Hospital of Derby and Burton Foundation Trust (UHDB) hope to identify crude mortality rate and mortality rate adjusted for age, gender, ethnicity and comorbidities for each region in England for AKI and COVID-19. Determinants of mortality will be examined for trusts of the same size and population served as University Hospital of Derby and Burton Foundation Trust. The analysis will be completed within 60 days of receiving the data from NHS Digital, with the study manuscript prepared 6 months from receiving the data. The data will be processed and the results will be presented as a report to the University Hospital of Derby and Burton Foundation Trust Board. The data analysis will also be submitted to peer-reviewed journals and presented in Nephrology conferences, nationally and internationally. The results will be presented in the Renal Association annual meeting in June 2021, European Renal Association in June 2021 and American Society of Nephrology in November 2021 The data analysis will generate aggregate data with statistical inferences. All outputs will be aggregated with small numbers suppressed in line with the HES Analysis Guide. The results of the research analysis will be disseminated to stakeholders during the project and after its completion. The target of this dissemination will be NHS stake holders, like UHDB, policy makers, medical fraternity, patients and researchers. The portal of dissemination of the results will be: - Conferences (as above), - briefing document to the UHDB Trust board, - peer-reviewed journals (Open access / free journals are preferred as they are well read and are not restricted to subscription), which advertise the findings via social media such as Twitter. - oral presentations in grand rounds and teaching sessions.
DATA SUMMARY: The agreement requests one extract of record-level pseudonymised data made up from HES APC and HES CC, linked to Civil Registration (Deaths) Secondary Care Cut in order to obtain Date of Death for a cohort of individuals who were admitted to hospital between 1st March 2020 and 31st August 2020 filtered by a diagnosis of Covid-19 and/or Acute Kidney Injury (AKI). There is no flow of data into NHS Digital. METHODOLOGY: NHS Digital will create one pseudonymised data extract with the following filters: 1. All Adult patients 18 years of age and upwards [those with a birth date on or before 01/03/2002] who are admitted to the hospital with COVID-19 infection between 1st March 2020 and 31st August 2020. Including Diagnostic code for COVID-19 (U07.1) in any of the 20 diagnoses codes. This will exclude all patients under 18 years of age [those with a birth date after 01/03/2002]. 2. All Adult patients 18 years of age and upwards [those with a birth date on or before 01/03/2002] who are admitted to the hospital with acute kidney injury (AKI) between 1st March 2020 and 31st August 2020. Including Diagnostic code for AKI (N17) in any of the 20 diagnoses codes. this will exclude all patients under 18 years of age [those with a birth date after 01/03/2002] and patients on chronic maintenance haemodialysis or peritoneal dialysis and chronic kidney disease starting dialysis. 3. the data extract will have a flag applied to indicate one of 3 situations: 1. Positive diagnosis of Covid-19, AND Positive diagnosis of AKI 2. Positive diagnosis of Covid-19, NO Positive diagnosis of AKI 3. Negative diagnosis of Covid-19, AND Positive diagnosis of AKI All episodes for each cohort individual will be required to ensure there is no survival bias in the analysis. 4. The pseudonymised data extract will be disseminated in one drop via the Secure File Transfer Service (SEFT). The pseudonymised data extract will be analysed as per the study objectives stated above by the study chief investigator who is a substantive employee of UHDB. The data will be stored and processed on a UHDB Trust server with two-factor authentication on the VPN to connect to the Trust Network secure access via a Trust remote device. All hard drives are encrypted using 128-bit encryption. A username and password are required to log into the Trust remote device with a username and password, and a further unique code number required as second factor authentication for the VPN end-to-end encrypted tunnel. The VPN tunnel uses AES-256 encryption. Data will not be downloaded to the remote device. The data quality will be checked to ensure validity and the chief investigator is responsible for upholding UHDB’s information governance and data security policies. University Hospitals of Derby and Burton NHS Foundation Trust will take the responsibilities of Sponsor as defined in the UK Policy Framework for Health and Social Care Research. University Hospitals of Derby and Burton NHS Foundation Trust do not use any public cloud storage or processing services and all server backups are stored on site. IT support is in-house. Data will not be transferred outside of the UK. The data will be analysed to find any association with regional variation in COVID mortality and AKI. By signing the Data Sharing Agreement, all organisations party to this agreement must comply with the Data Sharing Framework Contract, including requirements on 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). HES DISCLOSURE CONTROL / SMALL NUMBER SUPPRESSION In order to protect patient confidentiality, when presenting results calculated from HES record level data, outputs will contain only aggregate level data with small numbers suppressed in line with HES Analysis Guide. When publishing HES data, you must make sure that: · cell values from 1 to 7 are suppressed at a local level to prevent possible identification of individuals from small counts within the table. · Zeros (0) do not need to be suppressed. · All other counts will be rounded to the nearest 5. 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.
Project 2 — DARS-NIC-11221-X6Y6N
Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)
Sensitive: Non Sensitive
When: 2016/09 — 2020/06.
Repeats: Ongoing, System Access
Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)
Categories: Anonymised - ICO code compliant
- HES Data Interrogation System
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Outpatients
- Hospital Episode Statistics Critical Care
Access is provided to the entire HES dataset (non-identifiable) for the specific purposes as listed below. The purpose of the request is to use information available in HES to study epidemiology of acute kidney injury in England. Specifically, the objectives of the research are 1) To study regional variation in dialysis requiring acute kidney injury (AKI-D) in England. 2) To evaluate factors affecting renal and patient outcome in acute kidney injury after medical conditions or procedures 3) To develop AKI risk score for community acquired AKI 4) To study long term patient and renal outcomes after dialysis requiring AKI To date there is a paucity of data on the incidence of AKI whether community or hospital-acquired. The reported prevalence of AKI from US data ranges from 1% (community-acquired) up to 7.1% (hospital-acquired) of all hospital admissions. The population incidence of AKI from UK data ranges from 172 per million population (pmp) per year from early data8 up to 486-630 pmp/year from more recent series, again depending on definition. The incidence of AKI requiring renal replacement therapy (RRT) ranges from 22 pmp/year to 203 pmp/year. An estimated 5–20% of critically ill patients experience an episode of AKI during the course of their illness and AKI receiving RRT has been reported in 4·9% of all admissions to intensive-care units (ICU)12. Data from the Intensive Care National Audit Research Centre (ICNARC) suggests that AKI accounts for nearly 10 percent of all ICU bed days. There are 4 studies from United States (S), reporting that the incidence and case-fatality of AKI has decreased, but the health care system in US is insurance based and the data used is from billing databases with their own limitations. The data will allow lay people, the medical community and healthcare policy makers to appreciate the true burden and variation of this important disease. This is important because it is the first critical step in developing strategies to reduce the incidence of AKI as well as improve outcomes. As such this study is well aligned with initiatives undertaken by NHS England to better understand the burden of AKI in England with the goal of developing national initiatives to reduce the incidence and improve survival. The research will be performed in Derby Teaching Hospital NHS Trust The data from HSCIC will provide information regarding incidence and case fatality of AKI in England and specifically in relation to high-risk cardio-vascular procedures. The data will also be used to specifically develop AKI risk scores for community acquired AKI. The research will be based in UK and there will be no element of this work performed abroad.
HDIS access allows the licensed user to carry out service evaluation for the Trust. The benefit is also in understanding yearly change in length of stay, mortality for certain group of diseases as identified by ICD 10 codes. Some example - 1) The access to HDIS has allowed the Trust to understand the impact of heart failure services on length of stay and readmission rates at University Hospitals of Derby and Burton NHS Foundation Trust. 2) The licensed user evaluated the number of AKI admissions in Queens Hospital Burton as recognised by coding and by NHS England's AKI algorithm to understand the specificity of the coding. This has led to important financial saving to the Trust by implementing "improving coding" in Queens Hospital, Burton. 3) The same audit also evaluated impact of not recognising AKI and mortality which was higher in Queens Hospital, Burton and has resulted in measures to improve AKI recognition. 4) The other service evaluation which is planned to understand the impact of influenza testing in emergency department and medical assessment unit in reducing hospital admission.
The use of HDIS mean that users and organisations have a secure access, remotely hosted software application for the analysis of HES data. The system is hosted and audited by the HSCIC meaning that large transfers of data to on-site servers is reduced and the HSCIC has the ability to audit the use and access to the data. The provision of a tool enables that rapid analysis can be performed to the latest version of the data where speedy analysis is required to react to either local public health, commissioning or research requirements. There are huge benefits with this research as mentioned below. The use of HES data for AKI epidemiology has resulted in clearer picture of the disease burden in England. As mentioned previously, the health care system is different in each country and though the mortality for AKI has decreased in US, this is not the case for England. The previously provided data has highlighted that mortality for dialysis requiring AKI (AKI-D) remains unchanged in England over last 15-years and urgent action needs to be taken to tackle this. The data shared previously was presented at the World Congress of Nephrology 2015 in Cape Town, European Renal Association meeting in London 2015 and an oral presentation in the European Renal Association meeting in London 2015. 1) The epidemiology of hospitalised acute kidney injury not requiring dialysis in England from 1998 to 2013: retrospective analysis of hospital episode statistics. Kolhe NV, Muirhead AW, Wilkes SR, Fluck RJ, Taal MW. Int J Clin Pract. 2016 Jan 22. doi: 10.1111/ijcp.12774. [Epub ahead of print] 2. National trends in acute kidney injury requiring dialysis in England between 1998 and 2013. Kolhe NV, Muirhead AW, Wilkes SR, Fluck RJ, Taal MW. Kidney Int. 2015 Nov;88(5):1161-9. doi: 10.1038/ki.2015.234. Epub 2015 Jul 29 The previous data has highlighted that the population incidence of both AKI & AKI-D has increased more than 12 folds in England. This research has led to further projects by UK Renal Registry to collect dialysis data for AKI prospectively. The NHS as a whole will benefit. As the results of the analysis are freely available, policy makers can also make use of this to decide important healthcare policies. 1) Benefits aimed are to achieved by working on research question 1 (above): England will be the first country to report accurately the incidence and case-fatality from AKI at regional level from ICD-10 coded definition of AKI. Recent evidence from England indicates that outcome of dialysis requiring AKI is poor, though there is no evidence if this is due to regional variation. This study will be provide evidence if regional evidence exists and the factors influencing the regional variation. This will be useful for service planning at national level to reduce the regional variation and improve outcomes. Target: 12-18 months 2) Benefits aimed are to achieve by working on research question 2 (above): It is unclear if AKI after bypass surgery is influenced by keeping patients on a bypass pump. This study will provide evidence and help clinicians with the knowledge gained to improve patient and renal outcome after cardiac bypass surgery. Target: 12-18 months 3) Benefits aimed to achieve by working on research question 3 (above): A better understanding of the factors associated with acute kidney injury in the form a risk score will help to prevent not only community acquired AKI, but also hospital acquired AKI by stratifying patients, who haven’t developed AKI, into low risk or high risk category. Validation in other regions will increase the robustness of the risks core. Target: 12-24 months 4) Benefits aimed are to achieve by working on research question 4 (above): Long term outcome of dialysis requiring AKI has been hampered by bias in the form of being either from specific centers or specific locations like intensive care. The national data available gives the power to investigate long-term patient and renal outcomes which can be further stratified by region. The benefit of this research questions is that it will identify best practice and set a benchmark for future improvements and will inform strategies that lead to a reduction in mortality rates. Target: 12-24 months. There is increasing evidence that AKI episodes, transient and permanent, lead to increased risk of end stage renal disease and all-cause mortality. The linked data with HES and UKRR will provide longitudinal data confirming and quantifying this relationship. Intervention studies initiated in selected locations in England can help understand the effectiveness and help prevent progression of AKI. In summary, it is expected that the benefits to include further published work in peer-reviewed medical journals, and further findings which may lead to quality improvement initiatives.
Users of HDIS are able to produce outputs from the system in a number of formats. The system has the ability to be able to produce small row count extracts for local analysis in Excel or other local analysis software. Users are also able to produce tabulations, aggregations, reports, charts, graphs and statistical outputs for viewing on screen or export to a local system. Any outputs that are produced from the systems that are to be published or shared will be small number suppressed outputs in line with the HES analysis guide. Users are not permitted to link data extracted from the system to any other data items which make the data identifiable. The results of the analysis will be presented as abstracts or posters in following meetings - Renal Association, British Renal Society, European Renal Association and American Society of Nephrology. The results will also be submitted to following reputed journals like BMJ, Plos Medicine or Lancet and Renal journals like Journal of American Society of Nephrology, Kidney International, Nephrology Dialysis and Transplantation etc It is expected that the analysis will take place in October 2016. Considering the review delays and differing resubmission process of each journals, it is difficult to predict dates. The outputs are for medical professionals in any speciality, given the importance of AKI. The output will also be useful to policy makers and commissioners Many journal articles can be published as open access. All manuscripts will be available free of charge and will be available to the public. Outputs will contain only aggregate level of data and small numbers suppressed in line with the HES analysis guide. As mentioned above the output may change as a result of findings, but the Trust expect to produce outputs in 12 months’ time. AKI in relation to cardiological procedures (cardio-pulmonary bypass graft), as mentioned earlier, will be analysed followed by risk modelling for community acquired AKI. Additional information to address DAAG comments 5th April 2016; 1) Regional variation in dialysis requiring acute kidney injury (AKI-D) in England – 6 months a. The outputs will be in the form of regional incidence of AKI-D in each region of England from 2001 to 2015. b. Regional mortality of AKI-D in each year from 2000 to 2015. c. Tables or forest plot of multivariable analysis of mortality determinants 2) Evaluate factors affecting renal and patient outcome in acute kidney injury after medical conditions or cardiac procedures – 12-18 months a. Table and forest plots of multivariable analysis of determinants of AKI-D after CABG 3) Risk score for AKI in community – 12-18 months a. Table and forest plots of multivariable analysis of determinants of AKI-D after CABG b. Table of AKI risk score and results of validation from other regions of England. 4) Long term patient and renal outcome after AKI-D – 24 months a. Kaplan-Meir survival analysis curves to demonstrate acturial survival. b. Cox-proportional hazard analysis and survival curve demonstrating adjusted hazards for patient and renal survival.
HDIS is accessed via a two-factor secure authentication method to approved users who are in receipt of an encryption token ID. Users have to attend training before the account is set up and users are only permitted to access the datasets that are agreed within this agreement. Users log onto the HDIS system and are presented with a SAS software application called Enterprise Guide which presents the users with a list of available data sets and available reference data tables so that they can return appropriate descriptions to the coded data. The access and use of the system is fully auditable and all users have to comply with the use of the data as specified in this agreement. The software tool also provides users with the ability to perform full data minimisation and filtering of the HES data as part of processing activities. Users are not permitted to upload data into the system. Licences are for named users only. Logon details are non-transferable and for use only by the named user. The data obtained will be used to calculate Charlson’s comorbidity index and will be analysed in SPSS v22, statistical software. The data will not be accessed from outside UK. Only direct employees of the Trust will have access to the data, with only the named user(s) having access to the HDIS system itself. Record-level data cannot be downloaded from the HDIS system. Linkage to other data sources is only permitted where this does not increase the risk of re-identification such as geographical databases which are in the public domain. As only aggregated data can be downloaded from HDIS, and it is not possible to upload data into HDIS, any linkage is only carried out on aggregated data. For subsequent linkage with UK renal registry (UKRR) for renal outcome of AKI-D, HSCIC will be requested to perform linkage and anonymise the data before processing for analysis. Any request for linkage to the UKRR would be subject to an application to the HSCIC. Only aggregated data will be downloaded from HDIS. However the applicant will receive separately an extract in relation to a patient cohort recognised as having AKI (by ICD 10 code of N17) and requiring dialysis (by X403 & X404), excluding patients with Chronic Kidney Disease (CKD) stage 5. The additional procedure codes which will be investigated will be K40-K44 for cardiac bypass surgery and other code for On-Pump bypass (Y73.1). Under this agreement, record level data will be provided by HSCIC in relation to the above cohort established within HDIS. This record level data will be an extract once agreed with the applicant, and will subsequently be analyzed to study long term outcome – Renal as well as patient outcome (survival) over a period of 15 years. The applicant will calculate the time on survival (days/months) and use statistical analysis (cox proportional hazard analysis and Kaplan Meir survival analysis) to plot and compare survival in different age groups and region. The Trust also anticipates a request to HSCIC in future to perform anonymised linkage to other dataset such as UKRR (UK Renal Registry) dataset to study the progression of AKI into CKD - such linkage is not part of this agreement. No patient identifiable data will be used for analysis and publishing. For detailed statistical analysis, the Trust may need to obtain statistical advice from Trust statistician.