Imperial College London Dr Foster Unit (ICL DFU) - Research to identify measures of quality and safety of healthcare

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

The Imperial College London Dr Foster Unit (ICL DFU) no longer receives funding, collaborates or liaises with Dr Foster Ltd and the commercial entity Dr Foster Ltd (A wholly owned subsidiary of Telstra Health UK). As a consequence, there are four main amendments to Imperial College London's (ICL) previous Data Sharing Agreement, DARS-NIC-12828-M0K2D-v7.2. The Imperial College London Dr Foster Unit (ICL DFU) requires access to NHS England data for the purpose of the following research project: 'Research to identify measures of quality and safety of healthcare.' 1. Removal of identifiable field, local patient identifier from HES APC. The following is a summary of the aims of the research project provided by the Imperial College London Dr Foster Unit (ICL DFU): 2. Imperial College London becomes the sole data controller and sole processor, and no longer needs to forward an extract to Dr Foster Ltd/Telstra Health UK Quality and safety in healthcare: ICL DFU uses Hospital Episode Statistics (HES) data and Civil Registration (death) data to identify measures of quality and safety in healthcare. ICL DFU’s research themes are around developing and validating indicators of quality and safety of healthcare to examine variation in both primary and secondary care. This research finds variations in healthcare performance by unit, patient risk subgroups and develops risk prediction, risk adjustment and outlier detection for such indicators and variations, and any other methodological aspects as they arise. 3. Data storage and processing locations now limited to Imperial College London Mortality Alerts: 4. Funding for research has changed from Dr Foster Ltd/Telstra Health UK to NIHR Imperial BRC. The research purpose has not changed. The rest of the Data Sharing Agreement with the ICL DFU remains the same. The research component remains focussed on quality and safety in healthcare , and the unit will continue to share its research findings with individual acute trusts (e.g. through mortality alert letters) and the NHS/academic community more widely through publication. Research projects related to the quality and safety of healthcare during the COVID19 pandemic, have been updated in this Data Sharing Agreement to include outputs and impact. Identifiable fields have been removed and destroyed in accordance with the conditions of Section 251, to review on an annual basis the requirement “to continue processing confidential patient information without consent” and after consultation with Dr Foster Ltd, Imperial College London have concluded that there is no longer a need to provide an NHS number re-dentification system. ICL have notified the Confidentiality Advisory Group that this service was withdrawn on the 31st August 2021 and securely deleted all identifiable fields, in all relevant tables and databases, and Local Patient Identifier (LOPATID) is no longer required. As Dr Foster Ltd (a wholly owned subsidiary of Telstra Health UK) have secured access to a de-identified HES feed under a separate Data Sharing Agreement, Imperial College London Dr Foster Unit are no longer required to provide an extract to Dr Foster Ltd for their tools and analysis/NHS management function. Dr Foster Ltd will no longer play a role under this Data Sharing Agreement. Imperial College London is now the Sole Data Controller and data Processor for this Data Sharing Agreement. The research will continue and the unit’s primary source of funding is now the NIHR Imperial Biomedical Research Centre. Processing and storage locations As a consequence of removing Dr Foster Ltd/Telstra Health UK from the agreement, the number of data storage and processing locations have been reduced. Data are now stored and processed in only two locations. Data are stored and processed at The Imperial College London - Data Centre which is based at Virtus SDC Limited in Slough. Imperial College has its own dedicated space within Virtus which provides a physical environment and power, to house ICL's own computing racks. No racks are shared with other organisations and ICL's racks have their own access controls that are restricted to approved ICL substantive staff. No network infrastructure is shared with any other organisation, and all network devices are owned and managed by Imperial College London. Virtus SDC Limited store data only and any access to this data by Virtus SDC Limited would be a breach of this data Sharing Agreement. The ICL DFU no longer use Iron Mountain for backup storage. A dedicated fibre communication between Imperial College and the Data Centre is used to backup data which is stored at Imperial College London. All data is encrypted at rest and in transit. Funding The unit’s primary source of funding is the NIHR Imperial Biomedical Research Centre. Aim and purpose of this application Quality and safety in healthcare Imperial College London Doctor Foster Unit (ICL DFU) uses Hospital Episode Statistics (HES) data and Civil Registration (death) data to identify measures of quality and safety in healthcare. ICL DFU’s research themes are around developing and validating indicators of quality and safety of healthcare to examine variation in both primary and secondary care. This research finds variations in healthcare performance by unit, patient risk subgroups and develops risk prediction, risk adjustment and outlier detection for such indicators and variations, and any other methodological aspects as they arise. Mortality alerts [1 paragraph unchanged] Imperial College London is processing the data being accessed under this Agreement as the performance of a task in the public interest under Article 6(1)(e) and 9(2)(j) of the General Data Protection Regulation. • The data are processed to provide a service to NHS Provider Trusts to support: administration and direct care of Trust patients, responding to mortality alerts for the purpose of case note audits and mortality reviews. • NHS Provider Trusts benefit from the data processed for this service to improve quality and safety of healthcare. • NHS Provider Trusts would lose the support for investigating issues raised in the performance tools at a patient level without this service. • The minimum amount of data are processed to make running this service possible. This Agreement permits ICL DFU to: • Continue research into quality and safety in healthcare • Support tools and analysis for the NHS • Provide mortality alerts How the data will support the aims and purposes of this applications ICL DFU develop and calculate a wide range of healthcare indicators (over 100) and as such require continued access to HES data to provide a wide array of relevant indicators to give end users as complete a picture of hospital performance as possible to allow UK healthcare and Social care organisations to effectively: • Monitor quality of services provided • Identify efficiency opportunities • Identify pathways where services can be improved for the benefit of patients Example longitudinal study using pseudonymised HES data: Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients This study evaluated patients who had a stroke for the first time and investigated each patient’s medical history for five years after the stroke. Historical HES data held by ICL DFU was used to track patients for 10 years and follow up for 5 years from the time of the first stroke event. Previous studies had been criticised for including patients with recurrent stroke, but ICL DFU was able to ascertain whether a patient’s stroke event was the first or recurrent. ICL DFU also evaluated important cardiovascular co-morbidities by looking at the patient’s hospital diagnosis made in previous years. The study also identified stroke patients that were initially stable but later became high users of health care resources. The Care Quality Commission (CQC) ICL DFU contributes to the CQC’s surveillance remit by providing the CQC with monthly mortality alerts since 2007. ICL DFU mortality outlier alerts are used by CQC within the CQC’s Hospital Inspection framework. Number of years requested Historical data is essential to enable ICL DFU to: 1. Obtain longitudinal data on prior admissions for patients, for example to identify a patient’s first admission for a particular diagnosis. Risk modelling will also require access to variables on prior admissions including previously recorded co-morbidities. 2. Create, update and maintain statistical risk models to enable the regular production of risk adjusted measures of mortality, quality and efficiency (including mortality and cumulative sum alerts as used by NHS organisations and regulators). Datasets requested The datasets required from NHS Digital are: • Admitted Patient Care (APC) • Accident and Emergency (A&E) • Emergency Care Dataset (ECDS) • Critical Care (CC) • Outpatients (OP) . Civil Registration (Deaths) - Secondary Care Cut ECDS has been added as a required dataset to prepare for the transition from HES A&E to ECDS, access to ECDS will allow the unit's research work to continue. ECDS with mental health data included as part of ECDS will enable the unit to develop new risk predictors and improve risk prediction models. Diagnosis information is captured in different ways in HES A&E and ECDS. ICL DFU are currently undertaking a type of trends analysis (“interrupted time series analysis”) of A&E visits and outcomes to assess the impact of COVID and the lockdown. To estimate pre-lockdown trends, ICL DFU are using five years of HES A&E records and forecasting forwards to compare with the actual number of A&E visits both overall and by diagnosis, which requires consistency of terms and data recording. To continue this work by using the ECDS dataset without disruption ICL DFU need two years of historical ECDS as they also wish to look at the impact on regular A&E attenders, defined as those making three or more visits within a 12-month period. Having overlapping data will support the technical requirements for data validation and testing of existing processing routines. The full HES datasets are required to increase the power of predictive models for rare diseases, procedures and events (e.g. ICL DFU builds standard case mix adjustment models for 259 diagnosis groups and 200 procedure groups which include some rarer conditions). [13 paragraphs unchanged] • Practice Performance Monitoring [3 paragraphs unchanged] • Overall data quality assessment Level of data requested The following NHS England Data will be accessed: A bespoke extract with fewer fields, lesser frequency, and smaller geographical area will not suffice given that ICL DFU require the most up-to-date information to inform Trusts of potential issues around quality. A National Institute for Health Research (NIHR) funded review (published 2018, https://doi.org/10.3310/hsdr06070) of a subset of mortality alerts sent between 2011 and 2013 (and subsequently followed up by Care Quality Commission), found that Trusts reported areas of care that could be improved in 70% (108/154) of the alerts and that all were implementing action plans to address these issues. ICL DFU research has found on average, an associated reduction in mortality of 55% in the 12 months following a notified alert, suggesting timeliness of data may be key to saving lives. • Hospital Episode Statistics Sensitive fields • Admitted Patient Care (APC) Sensitive fields will only be available at a record level to NHS Provider Trusts (or approved regulatory bodies with express authority to demand such data, e.g. the CQC) and are specifically required for the purpose of conducting root cause analysis where there is a legitimate relationship with the patient. Where a legitimate relationship does not exist, data will be available at an aggregate level in line with the HES Analysis Guide and NHS Digital Small Numbers Procedure, with any sensitive fields suppressed. • Accident and Emergency (A&E) Consultant Code • Emergency Care Dataset (ECDS) Consultant code is also used in ICL DFU research, e.g. analysing volume and outcome relations for elective surgery. • Critical Care (CC) Patient’s general medical practitioner • Outpatients (OP) Patient’s general medical practice is used to enable mapping to practice-level data such as the Quality and Outcomes Framework (QOF) and practice staffing data etc. This is useful to understand variation in hospital activity and outcomes which may reflect issues of community and primary care. • Civil Registration (Deaths) - Secondary Care Cut ICL DFU is funded by a grant from the NIHR Imperial BRC Diagnosis information is captured in different ways in HES A&E and ECDS. ICL DFU are currently undertaking a type of trends analysis (“interrupted time series analysis”) of A&E visits and outcomes to assess the impact of COVID, associated lockdowns, and the post-COVID recovery. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data contributes to the research output of ICL DFU for the broader improvement of health and social care for the public. This is particularly important during the COVID-19 era, when data that are as up to date as possible are needed to inform policy. The full HES datasets are required to increase the power of predictive models for rare diseases, procedures and events (e.g. ICL DFU builds standard case mix adjustment models for 259 diagnosis groups and 200 procedure groups which include some rarer conditions). Civil Registration (Deaths) - Secondary Care Cut data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research. It is essential for performing survival analyses and so represents a very valuable source of data. [3 paragraphs unchanged] • Calculate total post-operative mortality rates, e.g. when comparing operative techniques such as laparoscopy joint fixation and open approaches revision [2 paragraphs unchanged] • Show variations in performance by unit and socio demographic socio-demographic stratum [2 paragraphs unchanged] • Supports Support organisations in delivering the learning required by the Learning from Deaths Framework and timely mortality reviews [1 paragraph unchanged] 30 day 30-day mortality (both in and out of hospital) is a well published and [24 words unchanged] will improve engagement with clinicians and allow comparisons with other published analyses. The level of the Data will be: · Pseudonymised - A bespoke extract with fewer fields, lesser frequency, and smaller geographical area will not suffice given that ICL DFU require the most up-to-date information to inform Trusts of potential issues around quality. A National Institute for Health Research (NIHR) funded review (published 2018, https://doi.org/10.3310/hsdr06070) of a subset of mortality alerts sent between 2011 and 2013 (and subsequently followed up by Care Quality Commission), found that Trusts reported areas of care that could be improved in 70% (108/154) of the alerts and that all were implementing action plans to address these issues. ICL DFU research has found on average, an associated reduction in mortality of 55% in the 12 months following a notified alert, suggesting timeliness of data may be key to saving lives. · Sensitive fields - Sensitive fields will only be available at a record level to NHS Provider Trusts (or approved regulatory bodies with express authority to demand such data, e.g. the CQC) and are specifically required for the purpose of conducting root cause analysis where there is a legitimate relationship with the patient. Where a legitimate relationship does not exist, data will be available at an aggregate level in line with the HES Analysis Guide and NHS England Small Numbers Procedure, with any sensitive fields suppressed. Consultant Code: Consultant code is also used in ICL DFU research, e.g. analysing volume and outcome relations for elective surgery. Patient’s general medical practitioner: Patient’s general medical practice is used to enable mapping to practice-level data such as the Quality and Outcomes Framework (QOF) and practice staffing data etc. This is useful to understand variation in hospital activity and outcomes that may reflect issues of community and primary care. The Data will be minimised to number of years requested as follows: Historical data is essential to enable ICL DFU to: 1. Obtain longitudinal data on prior admissions and other hospital contacts for patients, for example to identify a patient’s first admission for a particular diagnosis. Risk modelling will also require access to variables on prior admissions including previously recorded co-morbidities. 2. Create, update and maintain statistical risk models to enable the regular production of risk adjusted measures of mortality, quality and efficiency (including mortality and cumulative sum alerts as used by NHS organisations and regulators). ICL DFU develop and calculate a wide range of healthcare indicators and as such require continued access to HES, ECDS and CRD data to provide a wide array of relevant indicators to give end users as complete a picture of hospital performance as possible to allow UK healthcare and social care organisations to effectively: • Monitor quality of services provided • Identify efficiency opportunities • Identify pathways where services can be improved for the benefit of patients Example longitudinal study using pseudonymised HES data: Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients This study evaluated patients who had a stroke for the first time and investigated each patient’s medical history for five years after the stroke. Historical HES data held by ICL DFU was used to track patients for 10 years and follow up for 5 years from the time of the first stroke event. Previous studies had been criticised for including patients with recurrent stroke, but ICL DFU was able to ascertain whether a patient’s stroke event was the first or recurrent. ICL DFU also evaluated important cardiovascular co-morbidities by looking at the patient’s hospital diagnosis made in previous years. The study also identified stroke patients that were initially stable but later became high users of health care resources. The Care Quality Commission (CQC): ICL DFU contributes to the CQC’s surveillance remit by providing the CQC with monthly mortality alerts since 2007. ICL DFU mortality outlier alerts are used by CQC within the CQC’s Hospital Inspection framework. This Agreement permits ICL DFU to: • Continue research into quality and safety in healthcare • Support tools and analysis for the NHS • Provide mortality alerts The research component remains focussed on quality and safety in healthcare, and the unit will continue to share its research findings with individual acute trusts (e.g. through mortality alert letters) and the NHS/academic community more widely through publication. Research projects related to the quality and safety of healthcare during the COVID19 pandemic have been updated in this Data Sharing Agreement to include outputs and impact. ICL is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. The lawful basis for processing personal data under the UK GDPR is: Article 6(1)(e) - 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. ICL DFU has determined the processing is necessary for its legitimate interests in being able to provide tools and services that will benefit healthcare organisations. The lawful basis for processing special category data under the UK GDPR is: Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. • The data are processed to provide a service to NHS Provider Trusts to support administration and direct care of Trust patients, responding to mortality alerts for the purpose of case note audits and mortality reviews. • NHS Provider Trusts benefit from the data processed for this service to improve quality and safety of healthcare. • NHS Provider Trusts would lose the support for investigating issues raised in the performance tools at a patient level without this service. • The minimum amount of data are processed to make running this service possible. The funding is provided by NIHR Imperial Biomedical Research Centre. The funding is specifically for the study described.

Processing activities

[1 paragraph unchanged] • NHS Digital England [1 paragraph unchanged] NHS Digital England release pseudonymised HES and ECDS data linked to Civil Registration data. ICL DFU processes the HES/Civil Registration [6 words unchanged] research and to alert NHS Trusts around issues of quality of care. The pseudonymised HES extracts (including sensitive fields) are stored in the research [5 words unchanged] the data for analyses. The research database is hosted in an Imperial College managed College-managed ISO27001-certified secure environment (“secure enclave”) within the Imperial College London Data Centre . Patient level data remains in this environment for storage and processing analysis purposes, so researchers only have a remote view of the data. Registered users can only access the environment using registered terminals and two-factor authentication. Centre. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data contributes to the research output of ICL DFU for the broader improvement of health and social care for the public. This is particularly important during the COVID-19 era, when data that are as up to date as possible are needed to inform policy. Patient-level data remains in this environment for storage and processing analysis purposes, so researchers only have a remote view of the data. Registered users can only access the environment using registered terminals and two-factor authentication. Users accessing the data must have an are substantive employees of Imperial College London contract and have completed the their mandatory training: training. • Data Protection Awareness The HES/Civil Registration Deaths extracts (including sensitive fields) are loaded into the research database. • Information Security Awareness Data are stored and processed at The Imperial College London - Data Centre, which is based at Virtus SDC Limited in Slough. Imperial College has its own dedicated space within Virtus that provides a physical environment and power to house ICL's own computing racks. No racks are shared with other organisations, and ICL's racks have their own access controls that are restricted to approved ICL substantive staff. No network infrastructure is shared with any other organisation, and all network devices are owned and managed by Imperial College London. Virtus SDC Limited only store data, and any access to this data by Virtus SDC Limited would be a breach of this Data Sharing Agreement. • NHS Digital Data Security Awareness Level 1 A dedicated fibre communication between Imperial College and the Data Centre is used to back-up data, which is stored at Imperial College London. All data is encrypted at rest and in transit. The HES/Civil Registration Deaths extracts (including sensitive fields) are loaded on to the Research database. There is no requirement by ICL DFU to identify individuals using the HES and Civil Registrations of Death data and no attempt will be made to identify individuals. There is no requirement by ICL DFU to identify individuals using the HES data and no attempt will be made to identify individuals. The Data will not leave England or Wales at any time., No record level data will be transferred outside of England and Wales under this Agreement. There will be no data linkage undertaken with NHS Digital data provided under this Agreement that is not already noted in this Agreement. The data will not be made available to any third parties not stated in this Agreement. 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 output

[1 paragraph unchanged] Imperial College London Dr Foster Unit (ICL DFU) work programme is designed [7 words unchanged] and safety of healthcare, show variations in performance by unit and socio-demographic stratum stratum, and develop methods for risk prediction, risk adjustment and unit outlier detection. The unit’s work focuses on quality of care and patient safety, including healthcare-acquired infections (e.g., surgical wound infections and urinary tract infections) infections), readmissions and safety indicators. Collaborative projects with clinical colleagues have helped develop and validate healthcare quality indicators other than mortality, including bariatric surgery, primary angioplasty rates, indicators for stroke care, scans, obstetric care, orthopaedic redo rates revisions, and unplanned returns to theatre. [1 paragraph unchanged] ICL DFU are investigating the impact of the coronavirus pandemic on the [5 words unchanged] healthcare use (A&E attendances, emergency and elective hospital admissions, outpatient appointments) in young people and adults with non-COVID-19 conditions (e.g. heart attack, heart failure, stroke, hip fracture, [38 words unchanged] of the pandemic on secondary healthcare use including the recovery phase. (Ongoing 2022) 2024) An investigation into the impact COVID-19 has had on non-COVID-19 related A&E presentations and subsequent inpatient admissions in children with chronic or acute conditions such as asthma, epilepsy, type 1 diabetes, infections, injuries and poisonings (codes to be decided) both on first-time and subsequent presentations: this work has been funded by NIHR until mid-2022. ICL DFU will also investigate any temporal changes by patient characteristics such as age, ethnicity and socioeconomic position to understand better whom COVID-19 has impacted the most. Lastly, ICL DFU aims to follow-up the longer-term impacts that COVID-19 has had on hospital service use, such as A&E attendance and emergency admissions, after COVID-19. (Ongoing 2022) An investigation into the impact COVID-19 has had on non-COVID-19 related A&E presentations and subsequent inpatient admissions in children and young people: An investigation into risk factors and variation in hospital mortality rates for COVID19 inpatients: as part of ICL DFU’s ongoing research into variations in healthcare performance by unit, patient risk subgroups and risk prediction, risk adjustment and outlier detection, ICL DFU needs to understand and quantify the impact that COVID19 has had on ICL DFU’s established risk models. ICL DFU needs to develop new risk models for this group of patients, which will allow them to describe and consider important patient characteristics predictive of poor outcomes (including death). ICL DFU will then be able to compare outcomes in different hospitals and ask further explore explanations for variations in outcomes by Trust, whether these are unaccounted for confounders or differences in care delivery. The first paper for COVID19 inpatients was published earlier this year, a second paper tracking the second wave is in in preparation. (Ongoing 2022) This work covers patients with chronic or acute conditions such as appendicitis, epilepsy and tooth decay both on first-time and subsequent presentations: this work was funded by NIHR until mid-2022; papers have been submitted to journals. ICL DFU will also investigate any temporal changes by patient characteristics such as age, ethnicity and socioeconomic position to understand better whom COVID-19 has impacted the most. Lastly, ICL DFU aims to follow-up the longer-term impacts that COVID-19 has had on hospital service use, such as A&E attendance and emergency admissions, after COVID-19. (Ongoing 2025) Treatment pathways for chronic diseases. By mapping out NHS hospital contacts and modelling the variation across units, the unit will determine the elements (e.g. readmissions, missed outpatient appointments, surgery that could have been done as a day case) with the most potential for improvement. The use of practice level data to identify potential primary care factors as explanatory variables will support this. ”This forms part of the unit’s work with Imperial’s NIHR funded Patient Safety Translational Research Centre on the use of information for service improvement. (Ongoing 2022) Treatment pathways for chronic diseases: Drivers of unscheduled return to theatre (or reoperation) and readmission in elective hip and knee replacements: correlation between Return to Theatre (RTT) and revision rates by surgeon; volume-outcome relation for RTT; risk of RTT following revision rates. The objective is to better understand these key metrics for the specialty: revision and readmission rates are of major interest to surgeons and are on the NHS website. The unit established that there is greater non-random variation in RTT rates between surgeons than between hospitals. (Ongoing 2022) By mapping out NHS hospital contacts and modelling the variation across units, the unit will determine the elements (e.g. readmissions, missed outpatient appointments, surgery that could have been done as a day case) with the most potential for improvement. The use of practice level data to identify potential primary care factors as explanatory variables will support this. This forms part of the unit’s work with Imperial’s NIHR-funded Patient Safety Translational Research Centre on the use of information for service improvement and for Imperial’s NIHR Biomedical Research Centre’s digital health theme. (Ongoing 2025) Publications Management and outcomes for patients with periprosthetic femoral fractures: A selection of some recent publications: This NIHR-funded work will look at how these patients are managed in terms of operative approach (e.g. conservative, fixation or revision), pathway (particularly referral to larger centres) and outcomes (hospital use, length of stay and mortality) and variations by hospital site and Trust. It builds on the team's 2020 HES analysis that showed a steady rise in the numbers of admissions for these fractures. (Ongoing 2026) Bottle A, Faitna P, Aylin PP. Patient-level and hospital-level variation and related time trends in COVID-19 case fatality rates during the first pandemic wave in England: multilevel modelling analysis of routine dataBMJ Quality & Safety Published Online First: 07 July 2021. doi: 10.1136/bmjqs-2021-012990 An investigation into risk factors and variation in hospital mortality rates for COVID19 inpatients: M Deputy, C Rao, G Worley, V Balinskaite, A Bottle, P Aylin, E M Burns, O Faiz, Effect of the SARS-CoV-2 pandemic on mortality related to high-risk emergency and major elective surgery, British Journal of Surgery, Volume 108, Issue 7, July 2021, Pages 754–759, https://doi.org/10.1093/bjs/znab029 As part of ICL DFU’s ongoing research into variations in healthcare performance by unit, ICL DFU needs to develop new risk-adjustment models for this group of patients, which will allow ICL DFU to describe and consider important patient characteristics predictive of poor outcomes (including death). ICL DFU will then be able to compare outcomes in different hospitals and further explore explanations for variations in outcomes by hospital Trust, whether these are unaccounted-for confounders or differences in care delivery. The first paper for COVID19 inpatients was first published in 2021, and a second paper tracking the second wave came out in 2022. (Ongoing 2024) Bottle A, Griffiths R, White S, Wynn-Jones H, Aylin P, Moppett I, Chowdhury E, Wilson H, Davies BM. Periprosthetic fractures: the next fragility fracture epidemic? A national observational study. BMJ Open 2020;10(12):e042371. Ali AM, Loeffler MD, Aylin P, Bottle A. Timing of Readmissions After Elective Total Hip and Knee Arthroplasty: Does a 30-Day All-Cause Rate Capture Surgically Relevant Readmissions? J Arthroplasty 2021;36(2):728-733. Giuliani S, Honeyford, K, Chang C-Y, Bottle, A, Aylin P. Outcomes of Primary versus Multiple-Staged Repair in Hirschsprung's Disease in England. Eur J Pediatr Surg 2020; 30(1): 104-110. doi:10.1055/s-0039-3402712 Bottle A, Honeyford K, Chowdhury F, Bell D, Aylin P. Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study. Southampton (UK): NIHR Journals Library; 2018 Jul. PMID: 30044581.

Expected measurable benefits

Imperial College London Dr Foster Unit (ICL DFU) works with the Care Quality Commission (CQC), contributing to its surveillance remit using the same methods and data. The unit has been generating monthly mortality alerts since 2007, based on high thresholds [1]. This was pivotal in alerting the then Healthcare Commission (HCC) to problems at the Mid Staffordshire NHS Foundation Trust between July and November 2007 [2; see Yielded Benefits section for more on this and for more recent examples]. If ICL DFU is given continued access to the data, this monitoring tool that detected Mid Staffs will continue to monitor patient outcomes at acute hospitals and be ready to detect any future outliers. ICL DFU mortality outlier alerts are used by CQC within the CQC’s Hospital Inspection framework. (Ongoing) MORTALITY MONITORING: Imperial College London Dr Foster Unit (ICL DFU) works with the Care Quality Commission (CQC), contributing to its surveillance remit using the same methods and data. The unit has been generating monthly mortality alerts since 2007, based on high thresholds [1]. This was pivotal in alerting the then Healthcare Commission (HCC) to problems at the Mid Staffordshire NHS Foundation Trust between July and November 2007 [2; see Yielded Benefits section for more on this and for more recent examples]. [1 paragraph unchanged] ICL DFU’s COVID-19 work will help to identify potential variations in outcomes for COVID-19 patients, which may help to identify avenues for best practice, both at a national level and at an individual Trust level. Analyses of the impact of the epidemic on non-COVID-19 patients will help to quantify the impact on those patients, help inform NHS recovery plans, and assist in the preparation for subsequent waves of infection or new epidemics. The first paper on this was published online in mid-2021 by BMJ Quality and Safety. COVID-19 EFFECTS: As part of the treatment pathways analysis, econometric modelling will suggest which elements of the patient pathway are the costliest. Combining this with modelling of variation by unit will suggest priorities for improvement. Outputs will benefit managers, commissioners and patients. ICL DFU is continuing to map out the pathways for patients with heart failure. For example, we have combined practice-level data with HES to explore the drivers of readmission and death rates in patients with heart failure or COPD (Bottle et al. NIHR Journals Library PMID: 30044581.) ICL DFU’s COVID-19 work will help to identify potential variations in outcomes for COVID-19 patients, which may help to identify avenues for best practice, both at a national level and at an individual Trust level. Analyses of the impact of the epidemic on non-COVID-19 patients will help to quantify the impact on those patients, help inform NHS recovery plans, and assist in the preparation for subsequent waves of infection or new epidemics. Two papers on the variation in death rates for COVID-19 admissions were published in 2022. NIHR-funded work with NHS England on admissions for some common non-COVID conditions in children and young people has been submitted to journals. (Ongoing 2024) Analyses of return to theatre, unplanned readmission and joint revision for elective hip and knee surgery will help orthopaedic surgeons, commissioners and patients understand these key quality markers for this specialty and devise appropriate improvement projects, for instance by determining which patients are at the highest risk and therefore need more rigorous follow-up. A paper on a complication of hip and knee replacements, periprosthetic fractures, was published by BMJ Open in 2020 (Ongoing) ORTHOPAEDICS: Well over 100,000 joint replacements occur each year in England. Analyses of return to theatre, unplanned readmission and joint revision for elective hip and knee surgery (arthroplasty) will help orthopaedic surgeons, commissioners and patients understand these key quality markers for this specialty and devise appropriate improvement projects, for instance by determining which patients are at the highest risk and therefore need more rigorous follow-up. This will also inform the growing use of day case arthroplasty, which saves resources due to short hospital stays and (it is hoped) lower complication rates. The team have just begun a comparison of the use of telephone versus face-to-face outpatient appointments following arthroplasty, which continues a theme of the published national analysis of this issue in children and young people before and since COVID-19. The former has risen greatly since COVID-19, but it is not known whether this is safe. Early analysis suggests that telephone appointments have higher attendance rates than in-person ones, but this needs to be proven. Safe use of phone appointments by the NHS has the potential to reduce costs. A paper on an important complication of hip and knee replacements, periprosthetic fractures, was published by BMJ Open in 2020 and was used as the basis for a successful grant application to NIHR. The analyses will investigate variations in the management and outcomes of these complicated fractures and provide consensus on how they should be managed. (Ongoing 2026) [1 paragraph unchanged]

Benefits reported

The initial analysis for the first wave of the COVID19 examining in-hospital COVID19 mortality was presented to the North West London Data Analytics Group and considered at the sector’s COVID19 Gold Command group (chaired by Julian Redhead), to provide assurance on outcomes in patients with COVID19 treated in hospital by acute providers in North West London. Further updates covering analysis of the second wave will also be provided to the groups, to provide assurance, and indications of best clinical practice. MORTALITY MONITORING: The national hospital mortality monitoring system mentioned above identified problems at the Mid Staffordshire NHS Foundation [39 words unchanged] work, are that all healthcare provider organisations should develop and maintain systems which that give effective real-time information on the performance of each health care provider’s [19 words unchanged] that summary hospital-level mortality indicators should be recognised as official statistics [5]. This led to the creation of the SHMI (see above for the team's role in its development). [1 paragraph unchanged] ICL DFU’s research on specific aspects of care has received a high media profile and has been highly cited. Research on weekend mortality in emergency care, analysis of mortality associated with the junior doctor changeover and work on elective procedures and mortality by day of the week resulted in front page broad sheet coverage, and radio and TV interviews: https://www1.imperial.ac.uk/publichealth/departments/pcph/research/drfosters/inthemedia/ COVID-19 EFFECTS: The unit’s “Out of hours” work has been a key driver in moving NHS towards 7/7 care. Headlines include, “NHS Services – open seven days a week: every day counts” and, “Sunday Times Safe Weekend Care”. As a result of the unit’s published research into the junior doctor changeover, a week's shadowing was introduced. This is where newly qualified doctors work alongside more senior ones for a week before they start work in August. The Academy of Medical Royal Colleges published proposals (16th April 2014) suggesting all Foundation Year 1 posts should begin on the first Wednesday in August as has always been the case, but other training posts should begin in September. The initial analysis for the first wave of the COVID-19 examining in-hospital COVID-19 mortality was presented to the North West London Data Analytics Group and considered at the sector’s COVID-19 Gold Command group (chaired by Julian Redhead), to provide assurance on outcomes in patients with COVID-19 treated in hospital by acute providers in North West London. Further updates covering analysis of the second wave were also provided to the groups, to provide assurance and indications of best clinical practice. CLINICAL GUIDELINES: The team's HES-based work has appeared in several clinical guidelines. Two examples are by NICE and are for fractured neck of femur (CG124, https://www.nice.org.uk/guidance/cg124/documents/ hip-fracture-full-guideline2) and heart failure (NG106, https://www.nice.org.uk/guidance/ng106/evidence/full-guideline-pdf-6538850029). OTHER: ICL DFU’s research on specific aspects of care has received a high media profile and has been highly cited academically. Research on weekend mortality in emergency care, analysis of mortality associated with the junior doctor changeover and work on elective procedures and mortality by day of the week resulted in front page broadsheet coverage, and radio and TV interviews: https://www1.imperial.ac.uk/publichealth/departments/pcph/research/drfosters/inthemedia/ The unit’s “Out of hours” work was a key driver in moving NHS towards 7/7 care. Headlines include “NHS Services – open seven days a week: every day counts” and, “Sunday Times Safe Weekend Care”. As a result of the unit’s published research into the junior doctor changeover, a week's shadowing was introduced. This is where newly qualified doctors work alongside more senior ones for a week before they start work in August. The Academy of Medical Royal Colleges published proposals (16th April 2014) suggesting all Foundation Year 1 posts should begin on the first Wednesday in August as has always been the case, but other training posts should begin in September.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + HES-ID to MPS-ID HES Accident and Emergency; + HES-ID to MPS-ID HES Admitted Patient Care; + HES-ID to MPS-ID HES Outpatients

Unchanged: Objective for processing, Processing activities, Expected output, Expected measurable benefits, Benefits reported.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

The Imperial College London Dr Foster Unit (ICL DFU) no longer receives funding, collaborates or liaises with Dr Foster Ltd and the commercial entity Dr Foster Ltd (A wholly owned subsidiary of Telstra Health UK). As a consequence, there are four main amendments to Imperial College London's (ICL) previous Data Sharing Agreement, DARS-NIC-12828-M0K2D-v7.2. 1. Removal of identifiable field, local patient identifier from HES APC. 2. Imperial College London becomes the sole data controller and sole processor, and no longer needs to forward an extract to Dr Foster Ltd/Telstra Health UK 3. Data storage and processing locations now limited to Imperial College London 4. Funding for research has changed from Dr Foster Ltd/Telstra Health UK to NIHR Imperial BRC. The research purpose has not changed. The rest of the Data Sharing Agreement with the ICL DFU remains the same. The research component remains focussed on quality and safety in healthcare , and the unit will continue to share its research findings with individual acute trusts (e.g. through mortality alert letters) and the NHS/academic community more widely through publication. Research projects related to the quality and safety of healthcare during the COVID19 pandemic, have been updated in this Data Sharing Agreement to include outputs and impact. Identifiable fields have been removed and destroyed in accordance with the conditions of Section 251, to review on an annual basis the requirement “to continue processing confidential patient information without consent” and after consultation with Dr Foster Ltd, Imperial College London have concluded that there is no longer a need to provide an NHS number re-dentification system. ICL have notified the Confidentiality Advisory Group that this service was withdrawn on the 31st August 2021 and securely deleted all identifiable fields, in all relevant tables and databases, and Local Patient Identifier (LOPATID) is no longer required. As Dr Foster Ltd (a wholly owned subsidiary of Telstra Health UK) have secured access to a de-identified HES feed under a separate Data Sharing Agreement, Imperial College London Dr Foster Unit are no longer required to provide an extract to Dr Foster Ltd for their tools and analysis/NHS management function. Dr Foster Ltd will no longer play a role under this Data Sharing Agreement. Imperial College London is now the Sole Data Controller and data Processor for this Data Sharing Agreement. The research will continue and the unit’s primary source of funding is now the NIHR Imperial Biomedical Research Centre. Processing and storage locations As a consequence of removing Dr Foster Ltd/Telstra Health UK from the agreement, the number of data storage and processing locations have been reduced. Data are now stored and processed in only two locations. Data are stored and processed at The Imperial College London - Data Centre which is based at Virtus SDC Limited in Slough. Imperial College has its own dedicated space within Virtus which provides a physical environment and power, to house ICL's own computing racks. No racks are shared with other organisations and ICL's racks have their own access controls that are restricted to approved ICL substantive staff. No network infrastructure is shared with any other organisation, and all network devices are owned and managed by Imperial College London. Virtus SDC Limited store data only and any access to this data by Virtus SDC Limited would be a breach of this data Sharing Agreement. The ICL DFU no longer use Iron Mountain for backup storage. A dedicated fibre communication between Imperial College and the Data Centre is used to backup data which is stored at Imperial College London. All data is encrypted at rest and in transit. Funding The unit’s primary source of funding is the NIHR Imperial Biomedical Research Centre. [2 paragraphs unchanged] Imperial College London Doctor Foster Unit (ICL DFU) uses Hospital Episode Statistics [19 words unchanged] themes are around developing and validating indicators of quality and safety of healthcare, particularly by GP practices, consultants, healthcare to examine variation in both primary and NHS Trusts. secondary care. This research finds variations in healthcare performance by unit, patient risk subgroups and develops risk prediction, risk adjustment and outlier detection for such indicators and variations, and any other methodological aspects as they arise. Tools and analysis for the NHS ICL DFU supplies Dr Foster Limited with pseudonymised HES and mortality data extracts so Dr Foster Limited can provide tools and analysis for healthcare organisations. Dr Foster Limited is a separate legal entity and must only receive these data as defined in Dr Foster Limited’s separate corresponding data Agreement - DARS-NIC-68697-R6F1T. Re-identification service for NHS Provider Trusts ICL DFU uses HES data to provide a patient re-identification service for the NHS which allows NHS Provider Trusts to investigate issues around quality and safety of care internally. These issues are identified using performance alerts from ICL DFU analyses (e.g. mortality alerts) or from Dr Foster Limited’s performance tools. The analyses and tools only give aggregate or pseudonymised information to NHS Provider Trusts, but the Trusts may need to investigate issues at a patient level. The re-identification service allows a Trust to send a pseudo identifier to retrieve a matching local hospital patient identifier or patient number (LOPATID) for patients under a Trust’s care. No other data is provided by the service. Trusts using the service then match the patient number with internal patient records to follow up and investigate. NHS Provider Trusts that use the performance tools can register with this service at no extra cost. The registration request is made to Dr Foster Limited; the request is passed on to ICL DFU and ICL DFU completes the registration. Dr Foster Limited does not have access to the registration utility. [1 paragraph unchanged] Since 2007 ICL DFU has generated used the outputs of the research to generate monthly mortality alerts using routinely collected hospital administrative data for all English [31 words unchanged] as an intervention to reduce avoidable mortality within English NHS Hospital Trusts. Justification and legitimate interests Imperial College London is processing the data being accessed under this Agreement as the performance of a task in the public interest under Article 6(1)(e) and 9(2)(j) of the General Data Protection Regulation. Imperial College London is processing the data being accessed under this Agreement as part of the public task around research under Article 6(1)(e) and 9(2)(j) of the GDPR. The re-identification service data will be processed as part of Article 6 (1)(f) - Legitimate Interests. [3 paragraphs unchanged] • All identifiable data are processed under ethical approval (reference: 20/LO/0611 until 23rd June 2025) with CAG section 251 (reference: 15/CAG/0005 for the duration of ethical approval). • The service will run until a replacement service is provided by NHS Digital. NHS Digital have discussed introducing a replacement service in the future. • Individuals can opt out of their individual data being used for this service using the national data opt-out. [6 paragraphs unchanged] ICL DFU develop and calculate a wide range of healthcare indicators (over 100) and as such [25 words unchanged] as possible to allow UK healthcare and Social care organisations to effectively: [4 paragraphs unchanged] This study evaluated patients who had a stroke for the first time and investigated each patient’s medical history for five years after the stroke. Because of the historical Historical HES data held by ICL DFU it was possible used to track patients for 10 years and follow up for 5 years [61 words unchanged] were initially stable but later became high users of health care resources. (Published 2017, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5448070/) ICL DFU and Dr Foster Limited ICL DFU and Dr Foster Limited collaborate to provide a management information function in the form of analysis for healthcare organisations but are separate legal entities. ICL DFU and Dr Foster Limited have separate corresponding data Agreements with NHS Digital. ICL DFU are sole data controllers for this Agreement and Dr Foster Limited are data controllers for Agreement DARS-NIC-68697-R6F1T. Dr Foster Limited is the unit's key funder, but Dr Foster Limited do not direct the work or research undertaken by ICL DFU. ICL DFU decides how the data received under this Agreement are used. [13 paragraphs unchanged] . Civil Registration (Deaths) - Secondary Care Cut [1 paragraph unchanged] Diagnosis information is captured in different ways in HES A&E and ECDS. ICL DFU are currently undertaking an interrupted a type of trends analysis (“interrupted time series analysis analysis”) of A&E visits and outcomes to assess the impact of COVID and [73 words unchanged] defined as those making three or more visits within a 12-month period. [21 paragraphs unchanged] A bespoke extract with fewer fields, lesser frequency, and smaller geographical area will not suffice given that ICL DFU and Dr Foster Limited require the most up-to-date information to inform Trusts of potential issues around [50 words unchanged] that all were implementing action plans to address these issues. ICL DFU and Dr Foster Limited research has found on average, an associated reduction in mortality of 55% [6 words unchanged] notified alert, suggesting timeliness of data may be key to saving lives. Identifiable data – LOPATID LOPATID is the local patient identifier / patient number used by a Provider Trust. The identifiable data requested with this Agreement are not used for research purposes and researchers do not have access to these data. Identifiable data is only processed by ICL DFU for use with the re-identification service. The processed identifiable data are only accessed by NHS Provider Trusts using the re-identification service. After reviewing the re-identification service, it was decided to remove the data field NHS Number for this Agreement. LOPATID is the minimum required to continue providing the service. [3 paragraphs unchanged] ICL DFU and Dr Foster Limited provide consultancy from analyses to authorised users within Trusts to enable reconciliation with local information systems and the instigation of clinical audits and case note reviews. Analyses by consultant activity are fed back to the NHS through a range of Management Information Systems provided by Dr Foster Limited in the forms of aggregation of teams into 'departments' or other hierarchies. Requirements for analyses by consultant activity are consistent with NHS needs and policy direction (to publish at consultant level). Consultant code is also used in research e.g. analysing volume and outcome relations for elective surgery. Some exclusions are applied e.g. Invalid codes, dental consultant etc. Consultant code is also used in ICL DFU research, e.g. analysing volume and outcome relations for elective surgery. [1 paragraph unchanged] Patient’s general medical practitioner practice is used to examine variations by GP practice and to enable mapping to practice level practice-level data such as The the Quality and Outcomes Framework (QOF) and practice staffing data etc. NHS Provider Trusts can identify the registered GP who referred the patient. This is essential useful to understanding rates of admission understand variation in hospital activity and rates of readmission by GP practice outcomes which may reflect issues of community and primary care. Person referring patient ICL DFU is funded by a grant from the NIHR Imperial BRC Analyses by the person referring patient activities are fed back to the NHS Provider Trusts through a range of Management Information Systems provided by Dr Foster Limited. These analyses allow NHS Provider Trusts to identify the person who referred the patient for calculation of referral rates. Understanding referral rates by GP practice and consultant can help to identify issues of quality of care. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data contributes to the research output of ICL DFU for the broader improvement of health and social care for the public. This is particularly important during the COVID-19 era, when data that are as up to date as possible are needed to inform policy. ICL DFU funding These data are extremely critical because mortality information may be a surrogate metric for success of medical care. Therefore, it is hoped this dataset will enable identification of factors that drive successful treatment of a patient. Cause and date of death may also be used to identify trends in causes of death in particular groups of patients. Historical death data are necessary for identifying trends. ICL DFU is part-funded by a grant from Dr Foster Limited. On approval of this Agreement and Dr Foster Limited’s Agreement DARS-NIC-68697-R6F1T-v6.5, Imperial College will supply derived pseudonymised data together with specific clear text sensitive fields to Dr Foster Limited use to develop indicators and methodologies to assist in the analysis of healthcare performance. Dr Foster Limited uses the transferred data to provide a management information function in the form of the Dr Foster Analysis Toolkit. Dr Foster Limited is the controller of the transferred data under Agreement DARS-NIC-68697-R6F1T. This purpose is fulfilled by analysis of HES data made available to customers via the following services provided by Dr Foster Limited: 1. Licensed subscriber of Dr Foster Analysis Toolkit a. Directly – i. NHS Provider Trust holding a subscription to the Dr Foster Analysis Toolkit can view data at a record level, with an option to use the patient re-identification service for approved individuals; or ii. other NHS organisations holding a subscription to Dr Foster Analysis Toolkit can view aggregated analysis to prevent any patients being identified in accordance with guidance provided by NHS Digital. b. Indirectly – non-NHS organisation that hold a subscription to the tool supply NHS organisations with aggregate small number suppressed analyses. 2. Value Added Services As an information intermediary, Dr Foster Limited responds to customer requests for analyses of NHS Digital's data, whose scopes are bespoke and customised to local needs. An established specialist team of Analysts provides statistical analysis for interpreting complex data and producing analysis on behalf of customers. It should be stated that this team, which is project based, conduct annual training on handling sensitive records and are highly conversant in national guidelines to protect patient confidentiality. Where there is any doubt the Dr Foster Limited's Head of Information Governance or SIRO will provide guidance and if required contact NHS Digital. Dr Foster Limited also provides analysis for publication for the benefit of the public and NHS e.g. Hospital Guide, and to support benefit to health and social care. Such analytical content may be published directly by Dr Foster Limited or within academic journals or articles to journalistic/media entities in the form of text, tables, and other data visualisation such as diagrams/graphs using aggregate information based on HES analysis. Dr Foster Limited is aware that publications, whether inside or outside the NHS, must adhere to strict guidelines in terms of disclosure, and will ensure any such publications are aggregated and comply with small number suppression in line with the HES Analysis Guide and other relevant legislation and standards as defined in the Terms and Conditions of the Data Sharing Agreement. ICL DFU receives Civil Registration (Deaths) data under Agreement DARS-NIC-383203-Q8B9L. These data are for use by ICL DFU only and are supplied annually. These data are used by ICL DFU for casemix-adjustments using 259 diagnosis groups and 200 procedure groups as part of the well-established national hospital mortality monitoring system that flagged Mid Staffordshire NHS Trust and other hospitals with problems. Death as an outcome is used within the varied programme of work, which covers a number of medical and surgical specialties. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research, and for Dr Foster Limited’s customers. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data will improve the research output of ICL DFU and the output of Dr Foster Limited’s products for the benefit of NHS customers and for the broader improvement of health and social care for the public. These data are extremely critical because mortality information may be a surrogate metric for success of medical care. Therefore, this dataset will enable identification of factors that drive successful treatment of a patient. Cause and date of death may also be used to identify trends in causes of death in particular groups of patients. Historical death data are necessary for identifying trends. [8 paragraphs unchanged] • Supports organisations in delivering the learning required by the Learning from Deaths agenda Framework and timely mortality reviews • Help organisations improve quality of care and identify where they could do more to help patients and patients’ families 30 day mortality (both in and out of hospital) is a well [18 words unchanged] will allow the provision of this outcome, which will improve engagement with clinicians, clinicians and allow comparisons with other published analyses.

Processing activities

[3 paragraphs unchanged] • Dr Foster Limited NHS Digital release pseudonymised HES data linked to Civil Registration data. ICL DFU processes the HES/Civil Registration Deaths data and uses it for research and to alert NHS Trusts around issues of quality of care. NHS Digital release pseudonymised and identifiable data. ICL DFU replace the pseudo identifier (a pseudo patient identifier generated by NHS Digital referred to as HESID) with a new pseudo identifier before transferring the pseudonymised data to Dr Foster Limited. The data flow for this agreement: The pseudonymised HES extracts (including sensitive fields) are stored in the research database where researchers can access the data for analyses. The research database is hosted in an Imperial College managed ISO27001-certified secure environment within the Imperial College London Data Centre . Patient level data remains in this environment for storage and processing analysis purposes, so researchers only have a remote view of the data. Registered users can only access the environment using registered terminals and two-factor authentication. NHS Digital release pseudonymised and identifiable HES data -> ICL DFU processes the HES data -> ICL DFU updates the re-identification service data -> ICL DFU replaces the HESID -> ICL DFU transfers the new pseudonymised data to Dr Foster Limited -> Dr Foster Limited receives and processes the data as described in data Agreement DARS-NIC-68697-R6F1T. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data contributes to the research output of ICL DFU for the broader improvement of health and social care for the public. This is particularly important during the COVID-19 era, when data that are as up to date as possible are needed to inform policy. As detailed in 'Objective for Processing', Dr Foster Limited process the pseudonymised data received from ICL DFU for: Users accessing the data must have an Imperial College London contract and have completed the mandatory training: • The Dr Foster’s Analysis Toolkit – a management information service for NHS organisations • Customer requests for analysis of HES data • Analysis for publication for the benefit of the public and NHS The pseudonymised HES extracts (including sensitive fields) are stored in the Research database where researchers can access the data for analyses. The research database is hosted in an Imperial College managed ISO27001 certified secure environment. Patient level data remains in this environment for analysis purposes, researchers only have a remote view of the data. Registered users can only access the environment using registered terminals or two-factor authentication. Identifiable data are not stored in the research database and are not used for research purposes. Users accessing the data must have an Imperial College contract and complete the mandatory training: [3 paragraphs unchanged] The HES extracts (including sensitive fields) are loaded on to the Research database with a unique identifier (field name FOSID) generated and added to each row of the data. A new pseudo identifier that replaces HESID is also generated for Dr Foster Limited’s use. The HES/Civil Registration Deaths extracts (including sensitive fields) are loaded on to the Research database. An extract with the generated FOSID is transferred to the server that provides the re-identification service for the NHS Acute Trusts. Further data processing is carried out on the onward supply of data by Dr Foster Limited who have dedicated staff and processes as per below: • Linkage into spells and superspells, which can often span across financial years • Healthcare Resource Group (HRG), Tariff and other Payment By Results related fields, using the HRG Grouper software • Various clinical groupings, including Clinical Classifications Software Diagnoses, Ambulatory Care Sensitive (ACS) conditions and Procedure Groups • Quality outcomes, including mortality, emergency readmission within 28 days, Long Length of stay and patient safety indicators • Patient-level predicted risks for these outcomes, based on national Logistic Regression models which are executed using R statistical software and updated monthly • Various other national benchmarks, including Length of stay percentiles and Standardised Admission Ratio benchmarks • Numerous efficiency-based metrics, including average length of stay, day case rate and potential bed days saved • Prescribed Specialised Services (PSS) groups, using the PSS Grouper software This process guarantees both Dr Foster Limited and ICL DFU are working from the same data (both in terms of underlying patient linkage and derived fields), which is necessary for joint projects. [2 paragraphs unchanged] There will be no data linkage undertaken with NHS Digital data provided under this Agreement that is not already noted in the this Agreement. The data will not be made available to any third parties not stated in this Agreement, this will include ICL DFU's parent company and group of companies. Agreement. [1 paragraph unchanged]

Expected output

1) Research into variations in quality of healthcare by provider: background to proposed work Imperial College London Dr Foster Unit (ICL DFU) work programme is designed [19 words unchanged] stratum and develop methods for risk prediction, risk adjustment and outlier detection. The unit’s work focuses on quality of care and patient safety, including healthcare-acquired infections (surgical wound infections and urinary tract infections) and safety indicators. Collaborative projects with clinical colleagues have helped develop and validate healthcare quality indicators other than mortality, including bariatric surgery, primary angioplasty rates, indicators for stroke care, obstetric care, orthopaedic redo rates and returns to theatre. The unit’s work focuses on quality of care and patient safety, including healthcare-acquired infections (e.g., surgical wound infections and urinary tract infections) and safety indicators. Collaborative projects with clinical colleagues have helped develop and validate healthcare quality indicators other than mortality, including bariatric surgery, primary angioplasty rates, indicators for stroke care, obstetric care, orthopaedic redo rates and returns to theatre. [1 paragraph unchanged] An investigation into ICL DFU are investigating the impact of the coronavirus pandemic on the quality and safety of secondary healthcare use (A&E attendances, emergency and elective hospital admissions, outpatient appointments) [28 words unchanged] characteristics such as age, gender, ethnicity and socio-economic status, have been most effected affected by the pandemic. And finally, ICL DFU will evaluate any long-term impact of the pandemic on secondary healthcare use including the recovery phase. (Ongoing 2021) 2022) An investigation into the impact COVID-19 has had on non-COVID-19 related A&E [20 words unchanged] injuries and poisonings (codes to be decided) both on first-time and subsequent presentations. UCL presentations: this work has been funded by NIHR until mid-2022. ICL DFU will also investigate any temporal changes by patient characteristics such as [30 words unchanged] use, such as A&E attendance and emergency admissions, after COVID-19. (Ongoing 2022) An investigation into risk factors and variation in hospital mortality rates for COVID19 inpatients. As inpatients: as part of ICL DFU’s ongoing research into variations in healthcare performance by [83 words unchanged] Trust, whether these are unaccounted for confounders or differences in care delivery. The first paper for COVID19 inpatients was published earlier this year, a second paper tracking the second wave is in in preparation. (Ongoing 2021) 2022) Treatment pathways for chronic diseases. By mapping out NHS hospital contacts and [20 words unchanged] been done as a day case) with the most potential for improvement. This The use of practice level data to identify potential primary care factors as explanatory variables will support this. ”This forms part of the unit’s work with Imperial’s NIHR funded Patient Safety Translational Research Centre on the use of information for service improvement. (Ongoing 2021) 2022) Drivers of unscheduled return to theatre (or reoperation) and readmission in elective hip and knee replacements: correlation between Return to Theatre (RTT) [16 words unchanged] objective is to better understand these key metrics for the specialty: revision and readmission rates are of major interest to surgeons and are on the NHS Choices website. The unit has recently established that there is greater non-random variation in RTT rates between surgeons than between hospitals. (Ongoing 2021) 2022) Predictors of readmissions and A&E attendance in patients with chronic diseases (heart failure, chronic obstructive pulmonary disease (COPD), cancer). Readmissions are the focus of much attention worldwide in efforts to reduce costs and improve outcomes, but little is known about the role of A&E attendance (not ending in admission) in observed variations in readmission rates. The study has revealed that earlier outpatient nonattendance is a strong risk factor for readmission. The objective is again to better understand readmissions as an indicator and to suggest reformulation if desirable. (Ongoing 2022) [1 paragraph unchanged] A selection of some recent publications: Giuliani, S., Honeyford, K., Chang, C. -Y., Bottle, A., & Aylin, P. (2020). Outcomes of Primary versus Multiple-Staged Repair in Hirschsprung's Disease in England.. Eur J Pediatr Surg, 30(1), 104-110. doi:10.1055/s-0039-3402712 Bottle A, Faitna P, Aylin PP. Patient-level and hospital-level variation and related time trends in COVID-19 case fatality rates during the first pandemic wave in England: multilevel modelling analysis of routine dataBMJ Quality & Safety Published Online First: 07 July 2021. doi: 10.1136/bmjqs-2021-012990 Ghafur, S., Kristensen, S., Honeyford, K., Martin, G., Darzi, A., & Aylin, P. (2019). A retrospective impact analysis of the WannaCry cyberattack on the NHS. NPJ DIGITAL MEDICINE, 2, 7 pages. doi:10.1038/s41746-019-0161-6 M Deputy, C Rao, G Worley, V Balinskaite, A Bottle, P Aylin, E M Burns, O Faiz, Effect of the SARS-CoV-2 pandemic on mortality related to high-risk emergency and major elective surgery, British Journal of Surgery, Volume 108, Issue 7, July 2021, Pages 754–759, https://doi.org/10.1093/bjs/znab029 Honeyford, K., Bell, D., Chowdhury, F., Quint, J., Aylin, P., & Bottle, A. (2019). Unscheduled hospital contacts after inpatient discharge: A national observational study of COPD and heart failure patients in England. PLOS ONE, 14(6), 13 pages. doi:10.1371/journal.pone.0218128 Bottle A, Griffiths R, White S, Wynn-Jones H, Aylin P, Moppett I, Chowdhury E, Wilson H, Davies BM. Periprosthetic fractures: the next fragility fracture epidemic? A national observational study. BMJ Open 2020;10(12):e042371. Wang, Y., Honeyford, K., Aylin, P., Bottle, A., & Giuliani, S. (2019). One-year outcomes for congenital diaphragmatic hernia. BJS OPEN, 3(3), 305-313. doi:10.1002/bjs5.50135 Ali AM, Loeffler MD, Aylin P, Bottle A. Timing of Readmissions After Elective Total Hip and Knee Arthroplasty: Does a 30-Day All-Cause Rate Capture Surgically Relevant Readmissions? J Arthroplasty 2021;36(2):728-733. Martin, G., Clarke, J., Liew, F., Arora, S., King, D., Aylin, P., & Darzi, A. (2019). Evaluating the impact of organisational digital maturity on clinical outcomes in secondary care in England. NPJ DIGITAL MEDICINE, 2, 7 pages. doi:10.1038/s41746-019-0118-9 Giuliani S, Honeyford, K, Chang C-Y, Bottle, A, Aylin P. Outcomes of Primary versus Multiple-Staged Repair in Hirschsprung's Disease in England. Eur J Pediatr Surg 2020; 30(1): 104-110. doi:10.1055/s-0039-3402712 ICL DFU has many research publications from using HES data. Publication history can be accessed on the unit’s web pages: Bottle A, Honeyford K, Chowdhury F, Bell D, Aylin P. Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study. Southampton (UK): NIHR Journals Library; 2018 Jul. PMID: 30044581. https://www.imperial.ac.uk/dr-foster-unit/publications/. 2) Support the provision of a management information systems (Dr Foster Analysis Toolkit) for the NHS Dr Foster Limited is an independent healthcare information company. Dr Foster Limited provides a research grant to ICL DFU to develop indicators and methodologies to assist in the analysis of healthcare performance. ICL DFU works in collaboration with Dr Foster Limited to provide the NHS with a number of management information systems via the Dr Foster Analysis Toolkit. The main output created are bench marked or standardised healthcare indicators & analysis such as mortality (SHMI (Summary Hospital-level Mortality Indicator) / HSMR [The Hospital Standardised Mortality Ratio]), LOS(Length of Stay), admission trends, readmission rates, patient safety indicators, referral patterns, market share analysis etc. As stated previously, outputs are to be used solely for the purposes of providing a management information function to the NHS. Outputs are provided by Dr Foster Limited via: • Dr Foster Limited's Dr Foster Analysis Toolkit – Use of Role Based Access to determine the level of data end users can see within the tool. • Dr Foster Limited's value added services - Tabulations, Reports, Spreadsheets, Presentations, Articles & Projects. Outputs will be used by customers to investigate Clinical Quality, Performance and Business Development, specifically: • Assess and manage clinical quality and patient safety within NHS Organisations • Identify pathways where there is potential for improvement • Identify areas of best practice either within the Provider Trust or local/national health economies • Better understand how they compare to other Provider Trusts with similar case mixes • Identify improvements in operational efficiency • Understand patient outcomes • Identify and understand market activity • Monitor the impact of implemented changes • Identify variations in outcomes 3) Provision of a patient re-identification service for the NHS ICL DFU provides a patient re-identification service for the NHS which allows NHS Provider Trusts to investigate issues around quality and safety of care internally, which have arisen out of performance alerts arising out of ICL DFU analyses (e.g. mortality alerts), or arising from Dr Foster Limited performance tools using ICL DFU methods. Authorised individuals within an NHS Provider Trusts can identify patients indicated in the Dr Foster Limited healthcare performance tools that were under the Trust’s care. From 1st April 2019 to 31st March 2020, there were over 1,493 successful logins from 59 NHS Provider organisations. The re-identification service allows ICL DFU to supply NHS Provider Trusts with the local patient hospital identifier using Dr Foster Limited’s healthcare performance tools without passing these identifiers on to Dr Foster Limited . No patient identifiers will ever be passed to Dr Foster Limited or any other organisation except the NHS Provider Trust from where the data originated. The patient identifiable data are kept separate to the pseudonymised and sensitive data. Identifiable data are held on a different system to clinical data. All patient identifiable data are securely deleted on a rolling 3-year programme. The re-identification service is maintained by ICL DFU and is in full compliance of Confidentiality Advisory Group approval reference:15/CAG/0005.

Expected measurable benefits

Imperial College London Dr Foster Unit (ICL DFU) works with the Care [89 words unchanged] outcomes at acute hospitals and be ready to detect any future outliers. The unit will be able to assist the investigation of variations in outcomes at a local level by providing NHS Number and Consultant Code from the unit’s analyses to authorised users within Trusts to enable reconciliation with local information systems and the instigation of clinical audits and case note reviews. ICL DFU mortality outlier alerts are used by CQC within the CQC’s Hospital Inspection framework. (Ongoing) As a result of the unit’s leading role in the development of [20 words unchanged] (Steering Group for the National Review of the Hospital Standardised Mortality Ratio) [6] to develop a national indicator of hospital mortality. The resultant Summary-level Hospital [13 words unchanged] Ratio] methods) is now a public indicator used by all acute Trusts. [7] It was suggested that a relatively “poor” SHMI should trigger further analysis [69 words unchanged] used as part of a broad set of triggers for conducting future inspections [8]. inspections. ICL DFU continues to advise NHSD on methodological issues around the Summary [7 words unchanged] out analyses relating to this measure to assist in its development. (Ongoing) ICL DFU’s COVID-19 work will help to identify potential variations in outcomes for COVID-19 patients patients, which may help to identify avenues for best practice, both at a [33 words unchanged] assist in the preparation for subsequent waves of infection or new epidemics. The first paper on this was published online in mid-2021 by BMJ Quality and Safety. As part of the treatment pathways analysis, econometric modelling will suggest which [30 words unchanged] is continuing to map out the pathways for patients with heart failure. A PhD student has begun work on this for For example, we have combined practice-level data with HES to explore the drivers of readmission and death rates in patients with heart failure or COPD (Ongoing) (Bottle et al. NIHR Journals Library PMID: 30044581.) Analyses of return to theatre, unplanned readmission and joint revision for elective [29 words unchanged] patients are at the highest risk and therefore need more rigorous follow-up. A paper on a complication of hip and knee replacements, periprosthetic fractures, was published by BMJ Open in 2020 (Ongoing) References As most benefits are achieved on an ongoing basis, it is not possible to outline a specific target date for achievement of the benefits outlined as they are reliant on a range of factors outside of ICL DFU. However, whenever there are areas of concern about performance against key indicators, ICL DFU act immediately to alert relevant stakeholders and offer assistance in better understanding and addressing those concerns. [1] CQC Quarterly publication of individual outlier alerts for high mortality: Explanatory text (URL available at http://www.cqc.org.uk/public/about-us/monitoring-mortality-trends) [2] Investigation into Mid Staffordshire NHS Foundation Trust. Healthcare Commission 2009. Outcomes for patients and mortality rates. Pages 20 - 25 http://www.midstaffspublicinquiry.com/sites/default/files/Healthcare_Commission_report_on_Mid_Staffs.pdf [3] Report of the Mid Staffordshire NHS Foundation Trust Public Inquiry 2013. Volume 1. Pages 458 - 466 http://www.midstaffspublicinquiry.com/report. [4] Report of the Mid Staffordshire NHS Foundation Trust Public Inquiry 2013. Executive Summary. Recommendation 262: http://www.midstaffspublicinquiry.com/report). [5] Report of the Mid Staffordshire NHS Foundation Trust Public Inquiry 2013. Executive Summary. Recommendation 271: http://www.midstaffspublicinquiry.com/report. [6] Development of the new Summary Hospital-level Mortality Indicator. Department of Health Website. http://www.dh.gov.uk/health/2011/10/shmi-update/ [7] Indicator Specification: Summary Hospital-level Mortality Indicator. http://www.ic.nhs.uk/SHMI [8] Review into the quality of care and treatment provided by 14 hospital Trusts in England: overview report Professor Sir Bruce Keogh KBE. http://www.nhs.uk/NHSEngland/bruce-keogh-review/Documents/outcomes/keogh-review-final-report.pdf

Benefits reported

The initial analysis for the first wave of the COVID19 examining in-hospital COVID19 mortality was presented to the North West London Data Analytics Group and considered at the sector’s COVID19 Gold Command group (chaired by Julian Redhead), to provide assurance on outcomes in patients with COVID19 treated in hospital by acute providers in North West London. Further updates covering analysis of the second wave will also be provided to the groups, to provide assurance, and indications of best clinical practice. [1 paragraph unchanged] The hospital-level and subgroup-level mortality figures available from ICL DFU’s monitoring tool [54 words unchanged] mortality) for sepsis in 2018/19 (see Quality Accounts for 2017/8 and 2018/19). Dr Foster Limited have published a case study of how Sherwood Forest Hospitals used ICL DFU’s tool to help tackle high sepsis mortality. [2 paragraphs unchanged]

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Expected measurable benefits

Imperial College London Dr Foster Unit (ICL DFU) works with the Care [108 words unchanged] the investigation of variations in outcomes at a local level by providing Local Patient ID, NHS Number and Consultant Code from the unit’s analyses to authorised users [23 words unchanged] alerts are used by CQC within the CQC’s Hospital Inspection framework. (Ongoing) [13 paragraphs unchanged] 2) Support the provision of a management information systems (Dr Foster Analysis Toolkit) for the NHS Expected benefits include: • Enabling NHS acute Trusts to measure, compare and benchmark key quality indicator trends – focusing on risk-adjusted measures of mortality, readmissions and length of stay in hospital. • Providing evidence to instigate clinical audit and investigations related to quality of care, such as highlighting potential poor clinical coding or quality/efficiency concerns. • Validating other mortality indicators – such as HSMR, custom alerts and crude mortality. • Enabling NHS acute Trusts and commissioners to use performance information to identify, quantify and act on opportunities to improve efficiency of health services. • Understanding areas of best practice amongst customers and facilitate interactions with other customers who are not performing as well to support quality and efficiency improvement. • Helping clinicians and managers by providing independent and authoritative analysis of the variations that exist in acute hospital care in a way that is meaningful and that is understandable to patients and the public. • Highlighting topics of interest to the health industry and wider public to enable discussion and improvement in healthcare provision. • Publication of articles around variations of healthcare within the NHS is in the public interest and supports the government agenda for transparency by promoting choice and accountability within the NHS. • Maintaining the focus of the organisations on improvement. • Raising public and professional awareness through the Dr Foster's Hospital Guide regarding issues that affect the quality and efficiency of care provided by the NHS by publishing new information about variation in outcomes at the level of individual hospitals. In recent years, the Dr Foster's Hospital Guide has focussed on issues of clinical and managerial concern such as weekend care, overcrowding, management of chronic conditions and variations in access to elective care. In each case, the approach has been to identify effects that are known from the academic literature and to show the impact here and now in English NHS hospitals. By publishing this information Dr Foster Limited support the improvement of healthcare in England. How these benefits will be measured: Benefits are ongoing as the outputs described above are used within NHS Trusts’ internal monthly reporting and quality processes. Dr Foster Limited services allow performance of NHS Provider Trusts to be monitored and trended over time and therefore provide customers with the ability to measure changes in quality and performance, particularly in instances where customers have been alerted and they have worked with customers to understand the causes of worse than expected performance. As noted in the Yielded Benefits section, all hospital Trusts must publish annual Quality Accounts documents that include the identification of problems and action plans to mitigate them. Many of these reference mortality figures, including those from ICL DFU via Dr Foster Limited’s web pages or ICL DFU’s monitoring tool. Subsequent years’ Quality Accounts documents report on the progress that the Trusts made on those problems, giving figures and Trusts’ sources. Dr Foster Limited intends to provide an online customer survey within the Dr Foster Analytics Tool to capture customer feedback and associated benefits, this data will form the foundation for improving Dr Foster Limited’s services and to provide NHS Digital, and other relevant bodies, with tangible evidence to support Dr Foster Limited’s ongoing use of HES data. Dr Foster Limited welcomes the opportunity to work with NHS Digital to ensure information captured can support Dr Foster Limited’s ongoing supply and use of HES data. When will these be achieved: As most benefits are achieved on an ongoing basis, it is not possible to outline a specific target date for achievement of the benefits outlined as they are reliant on a range of factors outside of ICL DFU and Dr Foster Limited’s control. However, whenever there are areas of concern about performance against key indicators, ICL DFU and Dr Foster Limited parties act immediately to alert relevant stakeholders and offer assistance in better understanding and addressing those concerns.

Changed only in punctuation, spacing or capitalisation: Objective for processing, Processing activities.

Unchanged: Expected output, Benefits reported.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Emergency Care Data Set (ECDS)

Objective for processing

Imperial College London Doctor Foster Unit (ICL DFU) currently uses HES data to identify measures of quality and safety in healthcare. DFU’s research themes are around developing and validating indicators of quality and safety of healthcare, particularly by GP practice, consultant, and NHS Trust, showing variations in performance by unit, patient risk subgroups and risk prediction, risk adjustment and outlier detection for such indicators and variations and any other methodological aspects as they arise. Aim and purpose of this application Imperial College are processing the data being accessed under this agreement as part of their public task around research under Article 6(1)(e) and 9(2)(j) of the GDPR. Specifically; for the re identification work - data will be processed as part of Article 6 (1)(F) - Legitimate Interests. The legitimate interest is the re-identification self service provided to trusts to identify their own patients contributing to mortality alerts or other quality and safety alerts for the purpose of case note audits and mortality reviews. Quality and safety in healthcare The other organisation involved in this work is Dr Foster Limited (DFI). ICL DFU works in collaboration with DFI to provide a management information function in the form of analysis for healthcare organisations. ICL DFU supplies DFI with pseudonymised data extracts, described later in this agreement. DFI is the unit's key funder but DFI do not direct the work or research undertaken by ICL DFU. ICL DFU decides how the data received under this agreement is used. Imperial College London Doctor Foster Unit (ICL DFU) uses Hospital Episode Statistics (HES) data and Civil Registration (death) data to identify measures of quality and safety in healthcare. ICL DFU’s research themes are around developing and validating indicators of quality and safety of healthcare, particularly by GP practices, consultants, and NHS Trusts. This research finds variations in healthcare performance by unit, patient risk subgroups and risk prediction, risk adjustment and outlier detection for such indicators and variations, and any other methodological aspects as they arise. This agreement permits ICL DFU to continue this work and to continue providing a service to healthcare organisations. Tools and analysis for the NHS ICL DFU supplies Dr Foster Limited with pseudonymised HES and mortality data extracts so Dr Foster Limited can provide tools and analysis for healthcare organisations. Dr Foster Limited is a separate legal entity and must only receive these data as defined in Dr Foster Limited’s separate corresponding data Agreement - DARS-NIC-68697-R6F1T. Re-identification service for NHS Provider Trusts ICL DFU uses HES data to provide a patient re-identification service for the NHS which allows NHS Provider Trusts to investigate issues around quality and safety of care internally. These issues are identified using performance alerts from ICL DFU analyses (e.g. mortality alerts) or from Dr Foster Limited’s performance tools. The analyses and tools only give aggregate or pseudonymised information to NHS Provider Trusts, but the Trusts may need to investigate issues at a patient level. The re-identification service allows a Trust to send a pseudo identifier to retrieve a matching local hospital patient identifier or patient number (LOPATID) for patients under a Trust’s care. No other data is provided by the service. Trusts using the service then match the patient number with internal patient records to follow up and investigate. NHS Provider Trusts that use the performance tools can register with this service at no extra cost. The registration request is made to Dr Foster Limited; the request is passed on to ICL DFU and ICL DFU completes the registration. Dr Foster Limited does not have access to the registration utility. Mortality alerts Since 2007 ICL DFU has generated monthly mortality alerts using routinely collected hospital administrative data for all English acute NHS Hospital Trusts. A mortality alert is sent to a Trust at no charge and another copy is sent to the Care Quality Commission (CQC). These mortality alerts can act as an intervention to reduce avoidable mortality within English NHS Hospital Trusts. Justification and legitimate interests Imperial College London is processing the data being accessed under this Agreement as part of the public task around research under Article 6(1)(e) and 9(2)(j) of the GDPR. The re-identification service data will be processed as part of Article 6 (1)(f) - Legitimate Interests. • The data are processed to provide a service to NHS Provider Trusts to support: administration and direct care of Trust patients, responding to mortality alerts for the purpose of case note audits and mortality reviews. • NHS Provider Trusts benefit from the data processed for this service to improve quality and safety of healthcare. • NHS Provider Trusts would lose the support for investigating issues raised in the performance tools at a patient level without this service. • All identifiable data are processed under ethical approval (reference: 20/LO/0611 until 23rd June 2025) with CAG section 251 (reference: 15/CAG/0005 for the duration of ethical approval). • The service will run until a replacement service is provided by NHS Digital. NHS Digital have discussed introducing a replacement service in the future. • Individuals can opt out of their individual data being used for this service using the national data opt-out. • The minimum amount of data are processed to make running this service possible. This Agreement permits ICL DFU to: • Continue research into quality and safety in healthcare • Support tools and analysis for the NHS • Provide mortality alerts How the data will support the aims and purposes of this applications [4 paragraphs unchanged] Imperial College London Dr Foster Unit (ICL DFU) provides a pseudonymised extract of data to Dr Foster Limited, an independent healthcare information company, to develop indicators and methodologies to assist in the analysis of healthcare performance Example longitudinal study using pseudonymised HES data: Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients Historical data is essential to enable ICL DFU: This study evaluated patients who had a stroke for the first time and investigated each patient’s medical history for five years after the stroke. Because of the historical HES data held by ICL DFU it was possible to track patients for 10 years and follow up for 5 years from the time of the first stroke event. Previous studies had been criticised for including patients with recurrent stroke, but ICL DFU was able to ascertain whether a patient’s stroke event was the first or recurrent. ICL DFU also evaluated important cardiovascular co-morbidities by looking at the patient’s hospital diagnosis made in previous years. The study also identified stroke patients that were initially stable but later became high users of health care resources. 1. Obtain longitudinal data on prior admissions for patients. Risk modelling will also require access to variables on prior admissions including previously recorded co-morbidities. (Published 2017, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5448070/) 2. Create, update and maintain statistical risk models to enable the regular production of risk adjusted measures of mortality, quality and efficiency (including mortality and cumulative sum alerts as used by NHS organisations and regulators) ICL DFU and Dr Foster Limited An example of a longitudinal study which ICL DFU is currently undertaking is a study which involves the evaluation of patients who had a stroke and following them up for 5 years. The study involves people who had a stroke for the first time. Previous studies have been criticised for including patients with recurrent stroke. Based on previous research, ICL DFU has tracked back their chosen stroke patients for 10 years to ascertain whether the stroke event under observation was the first or recurrent. Moreover, ICL DFU has to evaluate important cardiovascular co-morbidities by looking at the patients hospital diagnosis made in the previous years. The study aims to identify stroke patients who are initially stable but later become high users of health care resources. ICL DFU also plans to look at pattern of causes of subsequent hospitalisation in the same cohort of patients. The study requires tracking back patients 10 years and following up for 5 years from the time of their index stroke event. ICL DFU and Dr Foster Limited collaborate to provide a management information function in the form of analysis for healthcare organisations but are separate legal entities. ICL DFU and Dr Foster Limited have separate corresponding data Agreements with NHS Digital. ICL DFU are sole data controllers for this Agreement and Dr Foster Limited are data controllers for Agreement DARS-NIC-68697-R6F1T. Dr Foster Limited is the unit's key funder, but Dr Foster Limited do not direct the work or research undertaken by ICL DFU. ICL DFU decides how the data received under this Agreement are used. The datasets required from NHS Digital by ICL DFU and DFI are: The Care Quality Commission (CQC) • Admitted Patient Care ICL DFU contributes to the CQC’s surveillance remit by providing the CQC with monthly mortality alerts since 2007. ICL DFU mortality outlier alerts are used by CQC within the CQC’s Hospital Inspection framework. • Accident and Emergency Number of years requested • Critical Care Historical data is essential to enable ICL DFU to: • Outpatients 1. Obtain longitudinal data on prior admissions for patients, for example to identify a patient’s first admission for a particular diagnosis. Risk modelling will also require access to variables on prior admissions including previously recorded co-morbidities. The full HES datasets are required to increase the power of predictive models for rare diseases, procedures and events (e.g. ICL DFU and DFI build standard case mix adjustment models for 259 diagnosis groups and 200 procedure groups which include some rarer conditions). 2. Create, update and maintain statistical risk models to enable the regular production of risk adjusted measures of mortality, quality and efficiency (including mortality and cumulative sum alerts as used by NHS organisations and regulators). Datasets requested The datasets required from NHS Digital are: • Admitted Patient Care (APC) • Accident and Emergency (A&E) • Emergency Care Dataset (ECDS) • Critical Care (CC) • Outpatients (OP) ECDS has been added as a required dataset to prepare for the transition from HES A&E to ECDS, access to ECDS will allow the unit's research work to continue. ECDS with mental health data included as part of ECDS will enable the unit to develop new risk predictors and improve risk prediction models. Diagnosis information is captured in different ways in HES A&E and ECDS. ICL DFU are currently undertaking an interrupted time series analysis of A&E visits and outcomes to assess the impact of COVID and the lockdown. To estimate pre-lockdown trends, ICL DFU are using five years of HES A&E records and forecasting forwards to compare with the actual number of A&E visits both overall and by diagnosis, which requires consistency of terms and data recording. To continue this work by using the ECDS dataset without disruption ICL DFU need two years of historical ECDS as they also wish to look at the impact on regular A&E attenders, defined as those making three or more visits within a 12-month period. Having overlapping data will support the technical requirements for data validation and testing of existing processing routines. The full HES datasets are required to increase the power of predictive models for rare diseases, procedures and events (e.g. ICL DFU builds standard case mix adjustment models for 259 diagnosis groups and 200 procedure groups which include some rarer conditions). [18 paragraphs unchanged] A bespoke extract with fewer fields and lesser frequency will not suffice given that ICL DFU/DFI require the most up-to-date information to inform trusts of potential issues around quality. A soon-to-be-published NIHR-funded review of a subset of mortality alerts sent between 2011 and 2013 (and subsequently followed up by Care Quality Commission), found that Trusts reported areas of care that could be improved in 70% (108/154) of the alerts and that all were implementing action plans to address these issues. ICL DFU/DFI research has found on average, an associated reduction in mortality of 55% in the 12 months following a notified alert, suggesting timeliness of data may be key to saving lives. Level of data requested A bespoke extract with fewer fields, lesser frequency, and smaller geographical area will not suffice given that ICL DFU and Dr Foster Limited require the most up-to-date information to inform Trusts of potential issues around quality. A National Institute for Health Research (NIHR) funded review (published 2018, https://doi.org/10.3310/hsdr06070) of a subset of mortality alerts sent between 2011 and 2013 (and subsequently followed up by Care Quality Commission), found that Trusts reported areas of care that could be improved in 70% (108/154) of the alerts and that all were implementing action plans to address these issues. ICL DFU and Dr Foster Limited research has found on average, an associated reduction in mortality of 55% in the 12 months following a notified alert, suggesting timeliness of data may be key to saving lives. Identifiable data – LOPATID LOPATID is the local patient identifier / patient number used by a Provider Trust. The identifiable data requested with this Agreement are not used for research purposes and researchers do not have access to these data. Identifiable data is only processed by ICL DFU for use with the re-identification service. The processed identifiable data are only accessed by NHS Provider Trusts using the re-identification service. After reviewing the re-identification service, it was decided to remove the data field NHS Number for this Agreement. LOPATID is the minimum required to continue providing the service. [1 paragraph unchanged] Sensitive fields will only be available at a record level to NHS [31 words unchanged] a legitimate relationship with the patient. Where a legitimate relationship does not exist exist, data will be available at an aggregate level in line with the HES Analysis Guide and NHS Digital Small Numbers Procedure, with any sensitive fields suppressed. [1 paragraph unchanged] ICL DFU and DFI Dr Foster Limited provide consultancy from their analyses to authorised users within trusts Trusts to enable reconciliation with local information systems and the instigation of clinical [12 words unchanged] to the NHS through a range of Management Information Systems provided by DFI Dr Foster Limited in the forms of aggregation of teams into 'departments' or other hierarchies. [33 words unchanged] elective surgery. Some exclusions are applied e.g. Invalid codes, dental consultant etc. [1 paragraph unchanged] Patient’s general medical practitioner is used to examine variations by GP practice [11 words unchanged] and Outcomes Framework (QOF) and practice staffing data etc. NHS Provider Trusts are able to can identify the registered GP who referred the patient. This is essential to [8 words unchanged] by GP practice which may reflect issues of community and primary care. [2 paragraphs unchanged] ICL DFU is part-funded by a grant from Dr Foster Limited. On approval of this agreement, a sub-licence model between NHS Digital and Imperial College will exist to permit ICL DFU to supply derived pseudonymised data together with specific clear text sensitive fields (as stated within this application) to Dr Foster Limited. ICL DFU funding The unit works in collaboration with Dr Foster Limited to provide a management information function in the form Dr Foster Analysis Toolkit. This purpose is fulfilled by analysis of HES data made available to customers via the following services provided by DFI: ICL DFU is part-funded by a grant from Dr Foster Limited. On approval of this Agreement and Dr Foster Limited’s Agreement DARS-NIC-68697-R6F1T-v6.5, Imperial College will supply derived pseudonymised data together with specific clear text sensitive fields to Dr Foster Limited use to develop indicators and methodologies to assist in the analysis of healthcare performance. Dr Foster Limited uses the transferred data to provide a management information function in the form of the Dr Foster Analysis Toolkit. Dr Foster Limited is the controller of the transferred data under Agreement DARS-NIC-68697-R6F1T. This purpose is fulfilled by analysis of HES data made available to customers via the following services provided by Dr Foster Limited: [2 paragraphs unchanged] i. NHS Provider Trust holding a subscription to the Dr Foster Analysis Toolkit are able to can view data at a record level, with an option to use the patient re-identification service for approved individuals; or ii. other NHS organisations holding a subscription to Dr Foster Analysis Toolkit are able to can view aggregated analysis to prevent any patients being identified in accordance with guidance provided by NHS Digital. [2 paragraphs unchanged] As an information intermediary, Dr Foster Limited responds to customer requests for analyses of NHS Digital's data, whose scopes are by their nature bespoke and customised to local needs. An established specialist team of Analysts [30 words unchanged] sensitive records and are highly conversant in national guidelines to protect patient confidentiality, where confidentiality. Where there is any doubt the Dr Foster Limited's Head of Information Governance or SIRO will provide guidance and if required contact NHS Digital. [1 paragraph unchanged] Civil Registration (Deaths) - Secondary Care Cut data are requested to provide more timely and accurate analysis and insight for Dr Foster’s customers. It is essential for performing survival analyses and so represents a very valuable source of data. It will improve the output of Dr Foster’s products for the benefit of NHS customers and for the broader improvement of health and social care for the public. ICL DFU receives Civil Registration (Deaths) data under Agreement DARS-NIC-383203-Q8B9L. These data are for use by ICL DFU only and are supplied annually. These data are used by ICL DFU for casemix-adjustments using 259 diagnosis groups and 200 procedure groups as part of the well-established national hospital mortality monitoring system that flagged Mid Staffordshire NHS Trust and other hospitals with problems. Death as an outcome is used within the varied programme of work, which covers a number of medical and surgical specialties. These data are extremely critical because mortality information may be a surrogate metric for success of medical care. Therefore this dataset will enable identification of factors that drive successful treatment of a patient. Cause and date of death may also be used to identify trends in causes of death in particular groups of patients. Historical death data are necessary for identifying trends. Civil Registration (Deaths) - Secondary Care Cut monthly data are requested in this Agreement to provide more timely and accurate analysis and insight for ICL DFU research, and for Dr Foster Limited’s customers. It is essential for performing survival analyses and so represents a very valuable source of data. Monthly data will improve the research output of ICL DFU and the output of Dr Foster Limited’s products for the benefit of NHS customers and for the broader improvement of health and social care for the public. The capability to link the already held HES datasets with mortality data could provide valuable insights into how and why some patients with the same condition and at the same stage can have very different outcomes. In addition it would be used to: These data are extremely critical because mortality information may be a surrogate metric for success of medical care. Therefore, this dataset will enable identification of factors that drive successful treatment of a patient. Cause and date of death may also be used to identify trends in causes of death in particular groups of patients. Historical death data are necessary for identifying trends. The capability to link the already held HES datasets with mortality data could provide valuable insights into how and why some patients with the same condition and at the same stage can have very different outcomes. In addition, it would be used to: [2 paragraphs unchanged] • Assess potential quality of care issues by comparing the cause of [19 words unchanged] but who die at home and whether the death is related to their the patient’s disease process or to complications of treatment [4 paragraphs unchanged] • Supports organisations in delivering their Learning from Deaths agenda and timely mortality reviews • Help organisations improve quality of care and identify where they could do more to help patients and their patients’ families [1 paragraph unchanged]

Processing activities

Imperial College London Dr Foster Unit (ICL DFU) uses hospital administrative data in the form of HES bespoke/monthly extracts to identify measures of quality and safety of healthcare. The unit’s work focuses on quality of care and patient safety, including healthcare-acquired infections, mortality and safety indicators. Processing of HES data involves: ICL DFU holds 2 databases to store data – A Research database and a Patient Identifiable database. The patient identifiable database is used to provide a Re-Identification service to NHS provider trusts for patients that are / were under their care. The patient identifiable data is only used for the re-identification service and no other purpose. The patient identifiable database only contains NHS Number, local patient identifier, and a generated pseudo identifier. • NHS Digital Patient identifiers are stored separately to the unit’s research database which holds the HES extracts (including sensitive fields). ICL DFU researchers have no access to identifiable fields. Only two named data managers have access to the patient identifiable fields within the unit. The purpose of holding the patient identifiers for the last 3 years is to allow hospitals to further investigate any alerts around poor or good performance and to help improve the quality and safety of healthcare delivery. • ICL DFU The HES extracts (including sensitive fields) are stored in the Research database where researchers are able to access the data to do their analyses. • Dr Foster Limited The HES extracts (including sensitive fields) are loaded on to the Research database with a unique identifier (fosid) being generated and added to the datasets. A new Extract_hesid for Dr Foster Intelligence Limited (DFI) is also generated using the SHA-256 hashing algorithm. NHS Digital release pseudonymised and identifiable data. ICL DFU replace the pseudo identifier (a pseudo patient identifier generated by NHS Digital referred to as HESID) with a new pseudo identifier before transferring the pseudonymised data to Dr Foster Limited. The data flow for this agreement: An extract is taken from ICL DFU patient identifier server and copied to the server which is used to provide the Re-Identification service for the NHS Acute Trusts. NHS Digital release pseudonymised and identifiable HES data -> ICL DFU processes the HES data -> ICL DFU updates the re-identification service data -> ICL DFU replaces the HESID -> ICL DFU transfers the new pseudonymised data to Dr Foster Limited -> Dr Foster Limited receives and processes the data as described in data Agreement DARS-NIC-68697-R6F1T. Further data processing are carried out on the onward supply of data by DFI who have dedicated staff and processes as per below: As detailed in 'Objective for Processing', Dr Foster Limited process the pseudonymised data received from ICL DFU for: • The Dr Foster’s Analysis Toolkit – a management information service for NHS organisations • Customer requests for analysis of HES data • Analysis for publication for the benefit of the public and NHS The pseudonymised HES extracts (including sensitive fields) are stored in the Research database where researchers can access the data for analyses. The research database is hosted in an Imperial College managed ISO27001 certified secure environment. Patient level data remains in this environment for analysis purposes, researchers only have a remote view of the data. Registered users can only access the environment using registered terminals or two-factor authentication. Identifiable data are not stored in the research database and are not used for research purposes. Users accessing the data must have an Imperial College contract and complete the mandatory training: • Data Protection Awareness • Information Security Awareness • NHS Digital Data Security Awareness Level 1 The HES extracts (including sensitive fields) are loaded on to the Research database with a unique identifier (field name FOSID) generated and added to each row of the data. A new pseudo identifier that replaces HESID is also generated for Dr Foster Limited’s use. An extract with the generated FOSID is transferred to the server that provides the re-identification service for the NHS Acute Trusts. Further data processing is carried out on the onward supply of data by Dr Foster Limited who have dedicated staff and processes as per below: [8 paragraphs unchanged] This process guarantees both DFI Dr Foster Limited and ICL DFU are working from exactly the same data (both in terms of underlying patient linkage and derived fields), which is necessary for their joint projects. No record level data will be transferred outside of the EEA under this agreement. There is no requirement by ICL DFU to identify individuals using the HES data and no attempt will be made to identify individuals. No record level data will be transferred outside of England and Wales under this Agreement. [2 paragraphs unchanged]

Expected output

[2 paragraphs unchanged] ICL DFU is currently working on the following analyses: ‘Biggest bang per buck’ elements of treatment pathways for chronic diseases. By mapping out NHS hospital contacts and modelling the variation across units, the unit will determine the elements (e.g. readmissions, missed OPD appointments, surgery that could have been done as a day case) with the most potential for improvement. This forms part of the unit’s work with Imperial’s NIHR funded Patient Safety Translational Research Centre on the use of information for service improvement. (Ongoing) An investigation into the impact of the coronavirus pandemic on secondary healthcare use (A&E attendances, emergency and elective hospital admissions, outpatient appointments) in adults with non-COVID-19 conditions (e.g. heart attack, heart failure, stroke, hip fracture, cancer, elective surgery). Furthermore, ICL DFU will investigate which groups of patients, based on patient characteristics such as age, gender, ethnicity and socio-economic status, have been most effected by the pandemic. And finally, ICL DFU will evaluate any long-term impact of the pandemic on secondary healthcare use including the recovery phase. (Ongoing 2021) Drivers of unscheduled return to theatre (or reoperation) in elective hip and knee replacements: correlation between Return To Theatre (RTT) and revision rates by surgeon; volume-outcome relation for RTT; risk of RTT following revision rates. The objective is to better understand these key metrics for the specialty: revision rates are of major interest to surgeons and are on the NHS Choices website. The unit has recently established that there is greater non-random variation in RTT rates between surgeons than between hospitals. (Ongoing) An investigation into the impact COVID-19 has had on non-COVID-19 related A&E presentations and subsequent inpatient admissions in children with chronic or acute conditions such as asthma, epilepsy, type 1 diabetes, infections, injuries and poisonings (codes to be decided) both on first-time and subsequent presentations. UCL DFU will also investigate any temporal changes by patient characteristics such as age, ethnicity and socioeconomic position to understand better whom COVID-19 has impacted the most. Lastly, ICL DFU aims to follow-up the longer-term impacts that COVID-19 has had on hospital service use, such as A&E attendance and emergency admissions, after COVID-19. (Ongoing 2022) Predictors of readmissions and A&E attendance in patients with chronic diseases (heart failure, COPD, cancer). Readmissions are the focus of much attention worldwide in efforts to reduce costs and improve outcomes, but little is known about the role of A&E attendance (not ending in admission) in observed variations in readmission rates. The study has revealed that earlier OPD nonattendance is a strong risk factor for readmission. The objective is again to better understand readmissions as an indicator and to suggest reformulation if desirable. (completed, report due end of 2018) An investigation into risk factors and variation in hospital mortality rates for COVID19 inpatients. As part of ICL DFU’s ongoing research into variations in healthcare performance by unit, patient risk subgroups and risk prediction, risk adjustment and outlier detection, ICL DFU needs to understand and quantify the impact that COVID19 has had on ICL DFU’s established risk models. ICL DFU needs to develop new risk models for this group of patients, which will allow them to describe and consider important patient characteristics predictive of poor outcomes (including death). ICL DFU will then be able to compare outcomes in different hospitals and ask further explore explanations for variations in outcomes by Trust, whether these are unaccounted for confounders or differences in care delivery. (Ongoing 2021) Travel time. Due to the well-documented relation between patient volume and outcomes, there is a growing drive to centralise certain services such as for stroke and elective surgery. Treatment rates for many conditions such as thoracic aortic disease (TAD) vary around the country. Using Lower Super Output Areas of the patient’s residence and the hospital postcode, researchers will first calculate how far patients currently travel for their TAD treatment and then the travel distance that would be incurred were surgical services retained only at large centres. The effect on outcomes will also be assessed. (Completed with paper ready, 2018) Treatment pathways for chronic diseases. By mapping out NHS hospital contacts and modelling the variation across units, the unit will determine the elements (e.g. readmissions, missed outpatient appointments, surgery that could have been done as a day case) with the most potential for improvement. This forms part of the unit’s work with Imperial’s NIHR funded Patient Safety Translational Research Centre on the use of information for service improvement. (Ongoing 2021) Modelling Health trajectories for Stroke patients Drivers of unscheduled return to theatre (or reoperation) in elective hip and knee replacements: correlation between Return to Theatre (RTT) and revision rates by surgeon; volume-outcome relation for RTT; risk of RTT following revision rates. The objective is to better understand these key metrics for the specialty: revision rates are of major interest to surgeons and are on the NHS Choices website. The unit has recently established that there is greater non-random variation in RTT rates between surgeons than between hospitals. (Ongoing 2021) ICL DFU is currently undertaking a study which involves the evaluation of patients who had a stroke and following them up for 5 years. The study involves people who had a stroke for the first time. Previous studies have been criticised for including patients with recurrent stroke. Based on previous research, ICL DFU has tracked back their chosen stroke patients for 10 years to ascertain whether the stroke event under observation was the first or recurrent. Moreover, ICL DFU has to evaluate important cardiovascular co-morbidities by looking at the patients hospital diagnosis made in the previous years. The study aims to identify stroke patients who are initially stable but later become high users of health care resources. ICL DFU also plans to look at pattern of causes of subsequent hospitalisation in the same cohort of patients. The study requires tracking back patients 10 years and following up for 5 years from the time of their index stroke event. (Completed with paper out, 2018) Predictors of readmissions and A&E attendance in patients with chronic diseases (heart failure, chronic obstructive pulmonary disease (COPD), cancer). Readmissions are the focus of much attention worldwide in efforts to reduce costs and improve outcomes, but little is known about the role of A&E attendance (not ending in admission) in observed variations in readmission rates. The study has revealed that earlier outpatient nonattendance is a strong risk factor for readmission. The objective is again to better understand readmissions as an indicator and to suggest reformulation if desirable. (Ongoing 2022) ICL DFU is working in collaboration with the University of Manchester and supported by the Care Quality Commission, to improve understanding of the unit’s mortality alerts and to evaluate their impact as an intervention to reduce avoidable mortality within English NHS hospital trusts, focusing on two conditions commonly attributed to mortality alerts acute myocardial infarction and septicaemia. University of Manchester does not have access to the data held by ICL DFU. The aim of this study is to provide a descriptive analysis of all alerts, their relationships with other measures of quality and their impact on reducing avoidable mortality. (Report for funder published, Dec 2016) Publications International comparisons of service use and outcomes. England and the Italy. The unit holds data from Centre for Medicare and Medicaid Services enrollees and from the Nationwide Inpatient Sample from the Italy. Researchers have previously set out the methodological issues with using administrative data from multiple countries. This study will compare patient casemix, rates of outcomes such as infections and readmissions, and rates of surgery, for example in patients near the end of their life (overtreatment is a growing concern) between the two countries. The objective is to highlight areas of better or poorer performance by the NHS compared with the Italy. ICL DFU has an extract of the Italian data and will be using HES data to compare hospital use for patients with heart failure in England compared with Italy. (Completed with paper and NIHR report out and report in press, 2018) A selection of some publications: Examples of key published research that have used HES data include: Giuliani, S., Honeyford, K., Chang, C. -Y., Bottle, A., & Aylin, P. (2020). Outcomes of Primary versus Multiple-Staged Repair in Hirschsprung's Disease in England.. Eur J Pediatr Surg, 30(1), 104-110. doi:10.1055/s-0039-3402712 June 2017 to May 2018: Ghafur, S., Kristensen, S., Honeyford, K., Martin, G., Darzi, A., & Aylin, P. (2019). A retrospective impact analysis of the WannaCry cyberattack on the NHS. NPJ DIGITAL MEDICINE, 2, 7 pages. doi:10.1038/s41746-019-0161-6 Aylin P, Bottle A, Burnett S, Cecil E, Charles KL, Dawson P, et al. Evaluation of a national surveillance system for mortality alerts: a mixed-methods study. Health Serv Deliv Res 2018;6(7) Honeyford, K., Bell, D., Chowdhury, F., Quint, J., Aylin, P., & Bottle, A. (2019). Unscheduled hospital contacts after inpatient discharge: A national observational study of COPD and heart failure patients in England. PLOS ONE, 14(6), 13 pages. doi:10.1371/journal.pone.0218128 Friebel, R., Hauck, K., & Aylin, P. (2018). Centralisation of acute stroke services in London: Impact evaluation using two treatment groups. HEALTH ECONOMICS, 27(4), 722-732. doi:10.1002/hec.3630 Wang, Y., Honeyford, K., Aylin, P., Bottle, A., & Giuliani, S. (2019). One-year outcomes for congenital diaphragmatic hernia. BJS OPEN, 3(3), 305-313. doi:10.1002/bjs5.50135 Cecil, E., Bottle, A., Esmail, A., Wilkinson, S., Vincent, C., & Aylin, P. P. (2018). Investigating the association of alerts from a national mortality surveillance system with subsequent hospital mortality in England: an interrupted time series analysis.. BMJ Qual Saf. doi:10.1136/bmjqs-2017-007495 Martin, G., Clarke, J., Liew, F., Arora, S., King, D., Aylin, P., & Darzi, A. (2019). Evaluating the impact of organisational digital maturity on clinical outcomes in secondary care in England. NPJ DIGITAL MEDICINE, 2, 7 pages. doi:10.1038/s41746-019-0118-9 Bottle, A., Loeffler, M. D., Aylin, P., & Ali, A. M. (2018). Comparison of 3 Types of Readmission Rates for Measuring Hospital and Surgeon Performance After Primary Total Hip and Knee Arthroplasty.. J Arthroplasty. doi:10.1016/j.arth.2018.02.064 ICL DFU has many research publications from using HES data. Publication history can be accessed on the unit’s web pages: Furnivall, D., Bottle, A., & Aylin, P. (n.d.). Retrospective analysis of the national impact of industrial action by English junior doctors in 2016.. BMJ Open, 8(1), e019319. doi:10.1136/bmjopen-2017-019319 https://www.imperial.ac.uk/dr-foster-unit/publications/. Ali, A. M., Loeffler, M. D., Aylin, P., & Bottle, A. (2017). Factors Associated With 30-Day Readmission After Primary Total Hip Athroplasty: Analysis of 514455 Procedures in the UK National Health Service (vol 152, e173949, 2017). JAMA SURGERY, 152(12), 1184. doi:10.1001/jamasurg.2017.4857 Balinskaite, V., Bottle, A., Shaw, L. J., Majeed, A., & Aylin, P. (2017). Reorganisation of stroke care and impact on mortality in patients admitted during weekends: a national descriptive study based on administrative data.. BMJ Qual Saf. doi:10.1136/bmjqs-2017-006681 Honeyford, K., Greaves, F., Aylin, P., & Bottle, A. (2017). Secondary analysis of hospital patient experience scores across England's National Health Service - How much has improved since 2005?. PLOS ONE, 12(10), 11 pages. doi:10.1371/journal.pone.0187012 Ali, A. M., Loeffler, M. D., Aylin, P., & Bottle, A. (2017). Factors Associated With 30-Day Readmission After Primary Total Hip Arthroplasty Analysis of 514 455 Procedures in the UK National Health Service. JAMA SURGERY, 152(12), 6 pages. doi:10.1001/jamasurg.2017.3949 King, A., Mullish, B. H., Williams, H. R. T., & Aylin, P. (2017). Comparative epidemiology of Clostridium difficile infection: England and the USA. INTERNATIONAL JOURNAL FOR QUALITY IN HEALTH CARE, 29(6), 785-791. doi:10.1093/intqhc/mzx120 Previously included: Palmer WL, Bottle A and Aylin P. Association between day of delivery and obstetric outcomes: observational study. BMJ 2015; 351: h5774. Bottle A, Goudie R, Cowie MR, Bell D, Aylin P, 2015, Relation between process measures and diagnosis-specific readmission rates in patients with heart failure, HEART, Vol: 101, Pages: 1704-1710, ISSN: 1355-6037 Aylin P; Alexandrescu R; Jen MH; Mayer EK; Bottle A. Day of week of procedure and 30-day mortality for elective surgery: retrospective analysis of hospital episode statistics. BMJ 2013;346:f2424. Palmer WL; Bottle A; Davie C; Vincent CA; Aylin P. Dying for the Weekend: A Retrospective Cohort Study on the Association Between Day of Hospital Presentation and the Quality and Safety of Stroke Care. Arch Neurol. 2012;69:1296-1303. Aylin P; Bottle A; Majeed A. Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models. BMJ 2007;334:1044. Aylin P, Yunus A, Bottle A, Majeed A, Bell D. Weekend mortality for emergency admissions. A large, multicentre study. Qual Saf Health Care. 2010;19:213-217 Jen MH, Bottle A, Majeed A, Bell D, Aylin P. Early in-hospital mortality following trainee doctors' first day at work. PLoS One. 2009;4:e7103. For full publication list see unit website: http://www1.imperial.ac.uk/publichealth/departments/pcph/research/drfosters/unit_publications/ [1 paragraph unchanged] Dr Foster Intelligence Limited (DFI) is an independent healthcare information company. It Dr Foster Limited provides a research grant to ICL DFU to develop indicators and methodologies to assist in the analysis of healthcare performance. ICL DFU works in collaboration with DFI Dr Foster Limited to provide the NHS with a number of management information systems via the Dr Foster Analysis Toolkit. The main output created are benchmarked bench marked or standardised healthcare indicators & analysis such as mortality (SHMI (Summary Hospital-level [34 words unchanged] for the purposes of providing a management information function to the NHS. Outputs are provided by DFI Dr Foster Limited via: • DFI's Dr Foster Limited's Dr Foster Analysis Toolkit – Use of Role Based Access to determine the level of data end users can see within the tool. • DFI's Dr Foster Limited's value added services - Tabulations, Reports, Spreadsheets, Presentations, Articles & Projects. [11 paragraphs unchanged] ICL DFU provides a patient re-identification service for the NHS which allows NHS provider trusts Provider Trusts to investigate issues around quality and safety of care within their organisation, internally, which have arisen out of performance alerts arising out of ICL DFU analyses (e.g. mortality alerts), or arising from DFI Dr Foster Limited performance tools using ICL DFU methods. Authorised individuals within an NHS Provider Trusts are able to can identify their own patients indicated in the DFI Dr Foster Limited healthcare performance tools. tools that were under the Trust’s care. From April 2015 to April 2016, there were over 3,600 successful logins from 75 NHS provider organisations. 64 provider trusts have used it more than 12 times per year (once a month) and one trust has used the re-identification service 425 times within this period. From 1st April 2019 to 31st March 2020, there were over 1,493 successful logins from 59 NHS Provider organisations. The re-identification service allows ICL DFU to supply NHS provider trusts Provider Trusts with NHS Number and LOPATID the local patient hospital identifier using DFI Dr Foster Limited’s healthcare performance tools without passing these identifiers on to DFI. Dr Foster Limited . No patient identifiers will ever be passed to DFI Dr Foster Limited or any other organisation except the NHS provider trust Provider Trust from where the data originated. The patient identifiable data are kept separate to the anonymised pseudonymised and sensitive data. They Identifiable data are held on a different system to clinical data. All patient identifiable data are securely deleted on a rolling 3 year 3-year programme. The re-identification service is maintained by ICL DFU and is in full compliance of CAG Confidentiality Advisory Group approval reference:15/CAG/0005.

Expected measurable benefits

Imperial College London Dr Foster Unit (ICL DFU) works with the Care Quality Commission (CQC), contributing to its surveillance remit using the same methods and data. The unit generates has been generating monthly mortality alerts since 2007, based on high thresholds [1]. This was [9 words unchanged] problems at the Mid Staffordshire NHS Foundation Trust between July and November 2007[2]. The resulting Public Inquiry recognised the role that the unit’s surveillance system of mortality alerts had to play in identifying Mid Staffs as an outlier [3]. Key recommendations, [4] reflecting the unit’s work, are that all healthcare provider organisations should develop 2007 [2; see Yielded Benefits section for more on this and maintain systems which give effective real-time information on the performance of each of their services, specialist teams and consultants in relation to mortality, patient safety and minimum quality standards. A further recommendation is that summary hospital-level mortality indicators should be recognised as official statistics [5]. for more recent examples]. If ICL DFU is given continued access to the data, this monitoring [45 words unchanged] Number and Consultant Code from the unit’s analyses to authorised users within trusts Trusts to enable reconciliation with local information systems and the instigation of clinical audits and case note reviews. ICL DFU mortality outlier outputs alerts are used by CQC within their the CQC’s Hospital Inspection framework.(on-going) framework. (Ongoing) As a result of the unit’s leading role in the development of hospital mortality measures, in 2010 ICL DFU was invited to contribute to a DoH Department of Health (DoH) Commissioned expert panel (Steering Group for the National Review of the Hospital [10 words unchanged] hospital mortality. The resultant Summary-level Hospital Mortality Indicator (based in part on their the DoH’s HSMR [The Hospital Standardised Mortality Ratio] methods) is now a public indicator used by all acute trusts. Trusts. [7] Professor Sir Bruce Keogh suggests It was suggested that a relatively “poor” SHMI should trigger further analysis or investigation by the hospital Board. The recent review (published in July 2013) into the quality of care and treatment provided by 14 hospital trusts Trusts with consistently high mortality in either measure led to 11 out of the 14 trusts Trusts identified being immediately placed on special measures. The review also informs the [25 words unchanged] of triggers for conducting future inspections [8]. ICL DFU continues to advise the HSCIC NHSD on methodological issues around the Summary level Hospital Mortality Index (SHMI), (SHMI) and carry out analyses relating to this measure to assist in its development. (ongoing) (Ongoing) The unit’s research on specific aspects of care has received a high media profile and has been highly cited. Their research on weekend mortality in emergency care, analysis of mortality associated with the junior doctor changeover and work on elective procedures and mortality by day of the week resulted in front page broad sheet coverage, and radio and TV interviews. (ongoing) ICL DFU’s COVID-19 work will help to identify potential variations in outcomes for COVID-19 patients which may help to identify avenues for best practice, both at a national level and at an individual Trust level. Analyses of the impact of the epidemic on non-COVID-19 patients will help to quantify the impact on those patients, help inform NHS recovery plans, and assist in the preparation for subsequent waves of infection or new epidemics. https://www1.imperial.ac.uk/publichealth/departments/pcph/research/drfosters/inthemedia/ As part of the treatment pathways analysis, econometric modelling will suggest which elements of the patient pathway are the costliest. Combining this with modelling of variation by unit will suggest priorities for improvement. Outputs will benefit managers, commissioners and patients. ICL DFU is continuing to map out the pathways for patients with heart failure. A PhD student has begun work on this for COPD (Ongoing) The unit’s “Out of hours” work has been a key driver in moving NHS towards 7/7 care. Headlines include, “NHS Services – open seven days a week: every day counts” and, “Sunday Times Safe Weekend Care”. As a result of the unit’s published research into the junior doctor changeover, Bruce Keogh introduced a week's shadowing where newly qualified doctors worked alongside more senior ones for a week before they start work in August. The Academy of Medical Royal Colleges published proposals (16th April 2014) suggesting all Foundation Year 1 posts should begin on the first Wednesday in August as has always been the case, but other training posts should begin in September.(on-going) Analyses of return to theatre, unplanned readmission and joint revision for elective hip and knee surgery will help orthopaedic surgeons, commissioners and patients understand these key quality markers for this specialty and devise appropriate improvement projects, for instance by determining which patients are at the highest risk and therefore need more rigorous follow-up. (Ongoing) As part of the ‘biggest bang per buck’ analysis, econometric modelling will suggest which elements of the patient pathway are the most costly. Combining this with modelling of variation by unit will suggest priorities for improvement. Outputs will benefit managers, commissioners and patients. (Dec 2017) Analyses of return to theatre and joint revision for elective hip and knee surgery will help orthopaedic surgeons, commissioners and patients understand these key quality markers for this specialty and devise appropriate improvement projects, for instance by determining which patients are at the highest risk and therefore need more rigorous follow-up. (on-going) ICL DFU intends to examine demand and capacity measures for A&E and admissions, and the impact that pressure on resources might have on safety and patient outcomes. By profiling hospital trusts in terms of demand, patient mix and outcomes, researchers will better understand key NHS metrics and patterns of service use and thereby help managers manage demand. (Jun 2017) Regarding the travel time analysis, using Lower Super Output Areas would enable us to study the effect of distance from home to hospital on patient outcomes. This also allows geographical access to services to be estimated, as researchers can calculate how far patients must travel for their treatment both now and after any future service reorganisation. (Dec 2017) ICL DFU analysis of their mortality alerting system will allow us to improve the alerting process and provide a better indication of how hospitals should investigate them to reduce mortality (including what are the key contributing factors to the alerts and to subsequent improvement in mortality by the hospitals). (Dec 2016) The modelling of health trajectories in stroke patients will improve risk stratification and understanding of the medium-term prognosis and needs. This will also allow better econometric modelling of NHS service use. (Jul 2018) [15 paragraphs unchanged] • Understanding areas of best practice amongst our customers and facilitate interactions with other customers who are not performing as well to support quality and efficiency improvement. • Helping clinicians and managers by providing independent and authoritative analysis of the variations that exist in acute hospital care in a way that is meaningful for them and that is understandable to patients and the public. [3 paragraphs unchanged] • Raising public and professional awareness through the Dr Foster's Hospital Guide regarding issues that affect the quality and efficiency of care provided by the NHS by publishing new information about variation in outcomes at the level of individual hospitals. Hospital Guide regarding issues that affect the quality and efficiency of care provided by the NHS by publishing new information about variation in outcomes at the level of individual hospitals. In recent years, the guide Dr Foster's Hospital Guide has focussed on issues of clinical and managerial concern such as weekend [21 words unchanged] identify effects that are known from the academic literature and to show their the impact here and now in English NHS hospitals. By publishing this information Dr Foster Limited support the improvement of healthcare in England. How will these benefits will be measured: Benefits are ongoing as the outputs described above are used within NHS Trusts’ internal monthly reporting and quality processes. Dr Foster Intelligence Ltd (DFI) Limited services allow performance of NHS Provider Trusts to be monitored and trended over time and therefore provide customers with the ability to measure changes in quality and performance performance, particularly in instances where customers have been alerted and they have worked with them customers to understand the causes of worse than expected performance. As noted in the Yielded Benefits section, all hospital Trusts must publish annual Quality Accounts documents that include the identification of problems and action plans to mitigate them. Many of these reference mortality figures, including those from ICL DFU via Dr Foster Limited’s web pages or ICL DFU’s monitoring tool. Subsequent years’ Quality Accounts documents report on the progress that the Trusts made on those problems, giving figures and Trusts’ sources. DFI Dr Foster Limited intends to provide an online customer survey within the Dr Foster Analytics Tool to capture customer feedback and associated benefits, this data will form the foundation for improving their Dr Foster Limited’s services and enable them to provide HSCIC, NHS Digital, and other relevant bodies, with tangible evidence to support their Dr Foster Limited’s ongoing use of HES data. DFI Dr Foster Limited welcomes the opportunity to work with HSCIC NHS Digital to ensure information captured can support their Dr Foster Limited’s ongoing supply and use of HES data. [1 paragraph unchanged] As a majority of most benefits are achieved on an ongoing basis, it is not possible to [13 words unchanged] are reliant on a range of factors outside of ICL DFU and DFI’s Dr Foster Limited’s control. However, whenever there are areas of particular concern about performance against key indicators, the 2 ICL DFU and Dr Foster Limited parties act immediately to alert relevant stakeholders and offer their assistance in better understanding and addressing them. those concerns.

Benefits reported

Benefits detailed in measurable benefits section are ongoing. The national monitoring system mentioned above identified problems at the Mid Staffordshire NHS Foundation Trust between July and November 2007 [2]. The resulting Public Inquiry recognised the role that the unit’s surveillance system of mortality alerts had to play in identifying Mid Staffs as an outlier [3]. Key recommendations, [4] reflecting the unit’s work, are that all healthcare provider organisations should develop and maintain systems which give effective real-time information on the performance of each health care provider’s services, specialist teams and consultants in relation to mortality, patient safety and minimum quality standards. A further recommendation is that summary hospital-level mortality indicators should be recognised as official statistics [5]. The hospital-level and subgroup-level mortality figures available from ICL DFU’s monitoring tool have been used to identify problems and measure the effectiveness of quality improvement initiatives undertaken by hospitals to address those problems. These are documented in NHS Hospital Trusts’ annual Quality Account documents. An example is sepsis at Oxford University Hospital in 2017/18, with reports of improvements in both care processes and the HSMR (adjusted mortality) for sepsis in 2018/19 (see Quality Accounts for 2017/8 and 2018/19). Dr Foster Limited have published a case study of how Sherwood Forest Hospitals used ICL DFU’s tool to help tackle high sepsis mortality. ICL DFU’s research on specific aspects of care has received a high media profile and has been highly cited. Research on weekend mortality in emergency care, analysis of mortality associated with the junior doctor changeover and work on elective procedures and mortality by day of the week resulted in front page broad sheet coverage, and radio and TV interviews: https://www1.imperial.ac.uk/publichealth/departments/pcph/research/drfosters/inthemedia/ The unit’s “Out of hours” work has been a key driver in moving NHS towards 7/7 care. Headlines include, “NHS Services – open seven days a week: every day counts” and, “Sunday Times Safe Weekend Care”. As a result of the unit’s published research into the junior doctor changeover, a week's shadowing was introduced. This is where newly qualified doctors work alongside more senior ones for a week before they start work in August. The Academy of Medical Royal Colleges published proposals (16th April 2014) suggesting all Foundation Year 1 posts should begin on the first Wednesday in August as has always been the case, but other training posts should begin in September.