Urgent research and surveillance on Covid-19 using the new OpenSAFELY secure platform across 55 million patients' full linked primary care records
Lead Research Organisation:
University of Oxford
Department Name: Primary Care Health Sciences
Abstract
We are delivering a platform for analysing healthcare data, currently including 27 million patients' GP records (with identifiable information removed), soon expanding to 55 million. This unprecedented scale is needed for rapid results during Covid-19.
OpenSAFELY uses a new model for maximum efficiency and privacy: rather than copying large volumes of information from GP records into another location, which involves security risks, we have instead built a secure analytics platform inside the data centres where GP records already reside, and linked to all relevant Covid-19 outcomes data such as death records and intensive care.
We have set this up rapidly and our first analyses are already complete. We now urgently need funds to sustain the platform, and to accelerate and expand our work on the following three workstreams:
1) Further research to identify which patients are at higher risk of admission, ventilation and death from Covid-19, to inform management, seclusion advice, service planning, and underlying mechanisms behind these findings (e.g. is there higher risk among BAME groups simply because of previous medical conditions?); and to explore hypotheses on certain drugs helping to protect people against poor outcomes, including ibuprofen, asthma drugs, anticoagulants, and other treatments.
2) Predicting local spread and service need, and evaluating exit strategies from lockdown, by creating models of disease transmission which combine "disease-dynamics" approaches with detailed clinical data on Covid-19 prevalence and the population at risk in every local area.
3) Measuring and mitigating the indirect health impacts of Covid-19 on, for example, cancer diagnosis and referrals, cardiovascular management, vaccinations, etc, and identifying urgent necessary actions both nationally and in smaller regions.
OpenSAFELY uses a new model for maximum efficiency and privacy: rather than copying large volumes of information from GP records into another location, which involves security risks, we have instead built a secure analytics platform inside the data centres where GP records already reside, and linked to all relevant Covid-19 outcomes data such as death records and intensive care.
We have set this up rapidly and our first analyses are already complete. We now urgently need funds to sustain the platform, and to accelerate and expand our work on the following three workstreams:
1) Further research to identify which patients are at higher risk of admission, ventilation and death from Covid-19, to inform management, seclusion advice, service planning, and underlying mechanisms behind these findings (e.g. is there higher risk among BAME groups simply because of previous medical conditions?); and to explore hypotheses on certain drugs helping to protect people against poor outcomes, including ibuprofen, asthma drugs, anticoagulants, and other treatments.
2) Predicting local spread and service need, and evaluating exit strategies from lockdown, by creating models of disease transmission which combine "disease-dynamics" approaches with detailed clinical data on Covid-19 prevalence and the population at risk in every local area.
3) Measuring and mitigating the indirect health impacts of Covid-19 on, for example, cancer diagnosis and referrals, cardiovascular management, vaccinations, etc, and identifying urgent necessary actions both nationally and in smaller regions.
Technical Summary
Our group is delivering analyses across 27 million patients' full pseudonymised linked primary care NHS records, soon expanding to 55 million. This unprecedented scale is needed for rapid results during Covid-19.
OpenSAFELY uses a new model for efficiency and privacy: we have built a secure analytics platform inside the data centres where GP records already reside, and linked to all relevant Covid-19 outcomes data.
This is not a proposal for theoretical future delivery. All permissions are signed, all data has flowed, our first analyses are complete. We have achieved this with no external resource.
We urgently need funds to sustain, accelerate, and expand our work across diverse collaborative analyses. We can flexibly discuss priorities with UKRI, amend or remove work packages. This application covers the platform, and three workstreams:
1) Observational epidemiology to identify patients at higher risk of admission, ventilation and death from Covid-19, to inform management, seclusion advice, service planning, and underlying mechanisms (e.g. higher risk among BAME groups); to rapidly assess specific hypotheses arising around treatment/prevention including ACEi's, ARBs, ibuprofen, inhaled corticosteroids, anticoagulants, and other treatments.
2) Deliver innovative transmission models that combine disease-dynamics approaches with near-real-time hyperlocal clinical data on prevalence and population at risk, to predict local spread and service need, and (for example) to design and evaluate exit strategies from lockdown.
3) Measure and mitigate the indirect health impacts of Covid-19 on, for example, cancer presentations and referrals, cardiovascular management, vaccinations, etc, using research and observatory approaches to identify urgent necessary actions.
OpenSAFELY uses a new model for efficiency and privacy: we have built a secure analytics platform inside the data centres where GP records already reside, and linked to all relevant Covid-19 outcomes data.
This is not a proposal for theoretical future delivery. All permissions are signed, all data has flowed, our first analyses are complete. We have achieved this with no external resource.
We urgently need funds to sustain, accelerate, and expand our work across diverse collaborative analyses. We can flexibly discuss priorities with UKRI, amend or remove work packages. This application covers the platform, and three workstreams:
1) Observational epidemiology to identify patients at higher risk of admission, ventilation and death from Covid-19, to inform management, seclusion advice, service planning, and underlying mechanisms (e.g. higher risk among BAME groups); to rapidly assess specific hypotheses arising around treatment/prevention including ACEi's, ARBs, ibuprofen, inhaled corticosteroids, anticoagulants, and other treatments.
2) Deliver innovative transmission models that combine disease-dynamics approaches with near-real-time hyperlocal clinical data on prevalence and population at risk, to predict local spread and service need, and (for example) to design and evaluate exit strategies from lockdown.
3) Measure and mitigate the indirect health impacts of Covid-19 on, for example, cancer presentations and referrals, cardiovascular management, vaccinations, etc, using research and observatory approaches to identify urgent necessary actions.
Publications
Bhaskaran K
(2021)
Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform.
in The Lancet regional health. Europe
Curtis HJ
(2022)
OpenSAFELY NHS Service Restoration Observatory 1: primary care clinical activity in England during the first wave of COVID-19.
in The British journal of general practice : the journal of the Royal College of General Practitioners
| Description | This grant has supported an extensive range of research, on diverse topics, as evidenced by the volume of publications linked to it. These projects have been completed by the OpenSAFELY team and many collaborators, and led to high-impact outputs which have changed clinical practice and been published in journals such as Nature, BMJ and Lancet. Topics and key findings include: Protection: OpenSAFELY has been used to describe which sub-populations were most likely to die from COVID-192; ethnic differences in COVID-19 infections and outcomes; the association between HIV infection and COVID-19 death; association between learning disability and risk of hospital admission and death from COVID-19; association between those living with and without children and COVID-19 infection; and association between household composition and severe COVID-19 outcomes in older people of different ethnicities. Changing patterns of mortality: OpenSAFELY has been used to evaluate the severity8 and case fatality9 of new variants; likelihood of Omicron or Delta infections resulting in Accident and Emergency attendance10; changes in COVID-19 mortality over time - including in care home residents12; comparing different methodological approaches for predicting COVID-19-related death; and to compare factors associated with COVID-19 death against those from other causes. Vaccination effectiveness and safety: OpenSAFELY has played a key role in ensuring the safety and effectiveness of COVID vaccines, including evaluating the potential link between neurological events and ChAdOx1 vaccination; the comparative effectiveness of initial vaccines; how effectiveness has changed over time17; the effectiveness of booster vaccination; population experiencing vaccine breakthrough following second vaccination; and the comparative effectiveness of two- and three-dose vaccination schedules in people with kidney disease. Pharmacoepidemiology: on treatment candidates and medication-associated risks: OpenSAFELY has been used to research COVID-19-related risks for people with immune-mediated inflammatory diseases and on immune-modifying therapies21; people currently prescribed warfarin22 and other anticoagulants23; people with COPD or asthma on inhaled corticosteroids; and users of non-steroidal anti-inflammatory drugs. OpenSAFELY has also been used to assess whether existing drugs, including hydroxychloroquine,, might be protective against severe COVID-19 outcomes. Coverage and effectiveness of antiviral and monoclonal antibody treatments for COVID-19: OpenSAFELY has been used to evaluate the real world effectiveness of new treatments, including comparing two of the first used treatments, molnupiravir and sotrovimab, in advance of comparable RCT data - later showing that patients receiving renal replacement therapy, who received sotrovimab, had lower risk of adverse COVID outcomes. Post-COVID-19 Outcomes: OpenSAFELY has been used to investigate the longer-term outcomes of COVID-19, looking at overall and cause-specific hospitalisation and death after COVID-19 hospitalisation29; and the risk factors associated with Long COVID. |
| Exploitation Route | Research findings continue used to inform clinical practice. Open code sharing by default facilitates future research projects in similar fields/using similar data, and open publication of all research results informs development of future research questions. The platform is open to use by a wide community, and now has over 150 projects approved from over 22 organisations including universities, UKHSA, and the NHS. There is a UKRI grant application for this data infrastructure currently under review by MRC to ensure that we are able to continue giving the research community access to this unprecedented scale of data, now 58 million patients' full GP records. |
| Sectors | Healthcare,Pharmaceuticals and Medical Biotechnology |
| URL | https://www.opensafely.org/ |
| Description | OpenSAFELY is a national Trusted Research Environment tool and team, built during the pandemic and partly funded by this grant. Implemented inside the data centres of Electronic Health Record system suppliers TPP and EMIS, under the Data Controllership of NHS England, OpenSAFELY has given researchers unprecedented access to 58 million patients' full GP records linked onto numerous other datasets, with greater depth and breadth of coverage than any other NHS data TRE. The data available covers >99% of patients in England (only 59 GP practices are missing), and can be used within 2-9 days of clinical event. It is the full GP record, and this GP data is not available anywhere else (GPES data in NHSD/ONS is a derived subset): it therefore represents a crucial national resource. Other key health datasets have been ingested and linked as needed including Secondary Uses Service (SUS/HES) data on outpatient, inpatient and A&E encounters; ONS death certificates; COVID-19 tests and vaccinations; ONS Covid Infection Survey and more. The benefits of enabling access to these data go beyond academia, and have directly informed decisions within healthcare and public policy during the Covid-19 pandemic. This data is now being used by a very wide range of key stakeholders with over 150 approved projects in the OpenSAFELY platform from over 22 organisations including universities, UKHSA, NICE, and the NHS. The demonstration of a new model of TRE, which can enable access to the most sensitive and detailed data while maintaining the trust of patients, the public and privacy groups, has influenced thinking on development of new TREs including within the NHS. In addition to the extensive range of research enabled by this grant, the investment in technical infrastructure means that OpenSAFELY delivers benefits far beyond those studies initially funded. This is evidenced by the wide range of research projects completed in OpenSAFELY, and many more planned or underway, which continue to inform clinical practice and deliver new insights, every year. However, such investments in infrastructure are significantly less common than funding for research projects, despite those projects requiring access to infrastructure such as OpenSAFELY. Better funding for technical infrastructure has the potential to deliver a significant return on investment well into the future, by enabling research projects focused on the priorities of tomorrow, as well as today's - This is well evidenced by the success of this investment in OpenSAFELY. |
| First Year Of Impact | 2021 |
| Sector | Healthcare |
| Impact Types | Policy & public services |
| Description | OpenSAFELY PI is leading The Goldacre Review for Sec of State DHSC. Press release from DHSC below. |
| Geographic Reach | National |
| Policy Influence Type | Contribution to a national consultation/review |
| URL | https://www.gov.uk/government/news/new-review-into-use-of-health-data-for-research-and-analysis |
| Description | Research produced using OpenSAFELY influencing policy and practice |
| Geographic Reach | National |
| Policy Influence Type | Citation in other policy documents |
| Impact | OpenSAFELY has delivered several key insights to the UK Government on how to respond to the COVID-19 pandemic which have led to changes in the public health response. For example, OpenSAFELY's paper "Factors associated with COVID-19-related death using OpenSAFELY" was used to inform the shielding list as well as the priority groups for the vaccine roll-out. Other examples, include, the use of OpenSAFELY's paper "OpenSAFELY: Association between living with children and outcomes from COVID-19: cohort study of 12 million adults in England, 7 March 2021" to inform policies regarding the re-opening of schools; and the use of OpenSAFELY's short data reports to monitor: vaccine effectiveness and safety, the impact of long-COVID, and the impact of ethnicity on COVID-19 outcomes. |
| URL | https://www.gov.uk/government/publications/opensafely-factors-associated-with-covid-19-related-hospi... |
| Description | COVID-19 Longitudinal Health and Wellbeing - National Core Study (LWH-NCS) |
| Amount | £10,291,535 (GBP) |
| Funding ID | MC_PC_20030 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2020 |
| End | 03/2021 |
| Description | Characterisation, determinants, mechanisms and consequences of the long-term effects of COVID-19: providing the evidence base for health care |
| Amount | £9,592,626 (GBP) |
| Funding ID | MC_PC_20051 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2021 |
| End | 02/2024 |
| Description | NHS Primary Care and Medicines Analytical Unit |
| Amount | £5,000,000 (GBP) |
| Organisation | NHS England |
| Sector | Public |
| Country | United Kingdom |
| Start | 12/2021 |
| End | 12/2026 |
| Description | OpenSAFELY, ISARIC, PHOSP: tracking consequences of COVID-19 infection across UK primary and secondary care. |
| Amount | £613,528 (GBP) |
| Funding ID | MR/W016729/1 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2021 |
| End | 08/2022 |
| Description | Phase 1 COVID-19 Data and Connectivity - National Core Study (Phase 1 D&C-NCS) |
| Amount | £1,760,000 (GBP) |
| Funding ID | MC_PC_20058 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2021 |
| End | 09/2022 |
| Description | Phase 1 COVID-19 Longitudinal Health and Wellbeing - National Core Study |
| Amount | £9,000,000 (GBP) |
| Funding ID | MC_PC_20059 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2021 |
| End | 09/2022 |
| Description | The OpenSafely Research Platform |
| Amount | £2,277,389 (GBP) |
| Funding ID | 222097/Z/20/Z |
| Organisation | Wellcome Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 11/2020 |
| End | 11/2023 |
| Title | The OpenSAFELY platform |
| Description | OpenSAFELY is a productive, highly secure, transparent, non-commercial, fully open-source software platform specifically developed for analysis of NHS electronic health records data. It can be deployed in any data centre to create a TRE with unprecedented security, transparency, and efficiency. With these privacy protections the OpenSAFELY team has earned public trust to implement OpenSAFELY across an unprecedented volume of NHS patient data. OpenSAFELY-TPP and OpenSAFELY-EMIS: 58 million full GP records OpenSAFELY has been fully implemented inside the data centres of TPP and EMIS, the two largest GP EHR providers in England, under COPI. This delivers analyses across the full raw primary care records of 58 million patients. Data includes all diagnoses, blood tests, prescriptions, investigations, and referrals. In total it is over 60 billion rows of detailed NHS data. This GP data has never been accessible before at national scale, and is not available from any other source (GPES in NHSD and ONS is a smaller derivative GP dataset). Other routes to access GP data have struggled with privacy and delivery problems. OpenSAFELY has active positive support from the professions and Citizens Juries. OpenSAFELY also has active positive support from privacy campaigners who typically block access to GP data at this scale. This is only possible because of the new approaches to privacy preservation and transparency in the OpenSAFELY tools. Additional datasets are easily and regularly ingested and linked in OpenSAFELY A range of crucial datasets for NHS service monitoring and academic research have already been linked on, including: SUS (hospital admissions, outpatient visits); ECDS (coded A&E attendances); CPNS (death in hospital from Covid); SGSS (Covid test results); Covid vaccination data; ONS (cause of death in and out of hospital); Household data (other pseudonymised occupants, is it a care home, approx location); ICNARC (ICU data); ISARIC (detailed hospital records of hospitalised covid patients); ONS Covid Infection Survey; And more. How is OpenSAFELY funded? OpenSAFELY is a fully open and non-commercial project for public good, funded solely by public money through research grants from UKRI, Wellcome Trust, NIHR, and others. All code is freely available and open to all for review and re-use in any setting. Who runs OpenSAFELY? The core OpenSAFELY technical team are the DataLab at Oxford, consisting of high-end software developers who have been trained with deep knowledge of NHS EHR data; working alongside NHS data analysts and researchers with deep training in software development. They work in close collaboration with Users (including researchers from LSHTM and 18 other external organisations, including multiple NHS users); The developer and data teams at TPP and EMIS with deep EHR data expertise. NHS England which is the Data Controller for OpenSAFELY. What is OpenSAFELY technically? OpenSAFELY is not a conventional TRE where users have unfettered access to data on a remote desktop, as that approach would not currently be secure enough to earn public and professional trust for national scale of GP data access. It is a complete set of bespoke tools for NHS data curation, privacy preservation, and efficient pipelining of analyses across vast NHS datasets, with: Modular open source code, reducing duplication of effort on data curation, analysis, workflow, dashboards, federated analytics, and more Bespoke NHS data curation tools where users curate the data once, then can easily share standard curation code to all for review, re-use, and modification. Innovative privacy methods (analysts write code for data preparation, analysis and visualisation using bespoke dummy data created for them by the OpenSAFELY curation modules; this is then deployed against the real data, but users never need unfettered direct access to disclosive patient records) A complete public open log of all code executed on the platform, earning public and professional trust through complete transparency on all actions (though outputs can be kept closed for an interim duration (typically set by a governance group) to allow researchers to develop their work before finally being made public). A set of live NHS dashboard tools (with optional login controls for local NHS data, including new NHS smart card integration). Teams can make and share their own bespoke and re-usable code modules for their own analytic needs. Because code is portable between settings, analyses can be run in multiple settings easily, delivering "federated analytics" between settings. This "federated analytics" is done regularly between OpenSAFELY-TPP and OpenSAFELY-EMIS; and has been done with ICS data also. All OpenSAFELY tools are portable and can be implemented wherever NHS data resides. When OpenSAFELY is built in a new environment, all the OpenSAFELY code for data cleaning, curation, efficient analysis and dashboards can simply be lifted and shifted to execute in those new environments. OpenSAFELY is now deployed in one ICS, and the data centre containing data for another 12 ICSs (where access can be turned on with an IG signature); NHSD (fully performant against dummy data; live data after an IG signature); and in various scales of deployment in other data centres nationally and internationally. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | What OpenSAFELY has achieved NHS service monitoring and improvement OpenSAFELY can be used to monitor clinical activity and outcomes in all NHS data in all practices and regions in near-real-time. We are happy to give demonstrations of all these outputs. Examples of completed work include: PINCER: this is a national patient safety programme previously delivered through AHSNs by running manual searches in hundreds of practices to identify patients where there treatment may not be adherent to who have breached various safety recommendations, some of which are complex clinical pathways; we have re-implemented all of PINCER in OpenSAFELY to deliver all PINCER metrics for all practices in a single command, and provide dashboards across the whole nation. NHS Service Restoration Observatory: we have deployed code that monitors volume of activity and clinical outcomes for any aspect of GP service during COVID to identify outliers, with outputs in reports, papers, and updating dashboards. Vaccine coverage dashboards: we deployed vaccine coverage dashboards immediately in Dec 2020, with detailed coverage data in fine grained clinical (as well as demographic) subgroups. OpenSAFELY was the first to raise the need to address lower vaccine uptake in: ethnic minorities; learning disabilities; severe mental illness; carehome residents; and more. Outputs in papers and live updating dashboards. This work is now being enhanced through our NHS Primary Care and Medicines Analytics Unit joint with the NHS England primary care and medicines teams. Research Outputs OpenSAFELY delivered its first output just 6 weeks after project commencement. Since then it has delivered 24 published papers and 26 preprints in high impact journals including Nature, the Lancet, the BMJ and more alongside numerous reports to SAGE, JCVI, CMO, and CSA. Specific papers are on various topics (COVID only, due to COPI notice permissions) including: COVID-19 risk factors Vaccine effectiveness, safety, and coverage Long COVID prevalence and risk factors RCT follow-up in EHR data at very low cost COVID risks in ethnic groups, learning disabilities, HIV, others Health service utilisation post-COVID Health consequences of COVID infection and admission. An Efficient, High Throughput Platform OpenSAFELY has delivered a very large number of completed outputs because the OpenSAFELY working methods are more efficient. The OpenSAFELY tools have been built to scale, with full documentation and automated pipelines built around shared re-usable modular code, rather than "manual labour" for each single analysis. All code is shared as open, but also designed to be re-usable by default, so every new analysis benefits from all prior analyses. These working practices are a deliberate choice: The curation pipeline is standardised, and all curation code easily re-usable. Repeated actions are turned into re-usable modules and features. Everything has detailed technical documentation for users. Developers are trained in NHS data analysis; analysts are trained in software skills. Developers and analysts work hand-in-hand. Other Users The OpenSAFELY team is currently supporting 30 projects from 18 organisations during the pilot phase. It is ready and able to scale rapidly, and support efficient use of NHS data by many more researchers in OpenSAFELY-TPP, OpenSAFELY-EMIS, OpenSAFELY-ICS, and OpenSAFELY-NHSD. Federated analytics OpenSAFELY has already delivered federated analytics, where the exact same analysis is run automatically in different locations containing NHS data, despite their being wildly different computational and data environments. The platform is built so that OpenSAFELY code for data curation, analysis and dashboards can run in any data centre where OpenSAFELY is implemented. Federated Analytics is how all national analyses in OpenSAFELY are already done: code is written in OpenSAFELY; it then executes separately in OpenSAFELY-TPP and OpenSAFELY-EMIS; and the results are stitched together after completion. Portable Analytics OpenSAFELY is now running inside the Graphnet data centre containing 13 ICS's data, with IG approval for live data access already in one ICS: we have now completed our first end-to-end analysis running the same code in OpenSAFELY-TPP and OpenSAFELY-ICS to get comparable outputs. We can happily implement OpenSAFELY in any setting where users want portable curation and analysis. All code for dashboards, reports or research created in any OpenSAFELY environment move smoothly to work in any new OpenSAFELY setting. Efficient Curation and Cleaning of Difficult NHS EHR and GP data OpenSAFELY has built the tools and framework for a systematic approach to cleaning and curating all raw NHS data, converting it into usable variables alongside documentation, validity tests, and the code to instantly implement those curated variables in analyses. This efficient, shared, systematic approach - "curate once, share to all" - means fast outputs. Capacity Building OpenSAFELY has developed a substantial team perfectly tuned to the job of getting better outputs from NHS data: high end software developers trained in the specific challenges of NHS data, NHS analytics, and academic research; pooling skills and working alongside NHS analysts and researchers trained in software development. This core team is ready to expand and train others. The OpenSAFELY Co-Pilot Programme Users of OpenSAFELY currently need basic familiarity with standard data science tools including GitHub, Python, and Docker. Some analysts in academia and the NHS lack fluent data science skills. To accelerate outputs the team have taken two approaches: The OpenSAFELY Co-Pilot programme gives each new user 5 person-days of one-to-one training and support over their first 4 weeks to get their first analysis complete. This has been a huge success and built analytic capacity across England. The OpenSAFELY team is also building "point and click" tools so that NHS analysts can easily generate graphs, dashboards and reports on NHS GP activity and outcomes without needing any data science skills. Public Trust and Data Access OpenSAFELY has earned unprecedented trust from organisations that traditionally obstruct NHS data access, by listening to their concerns and developing new technical solutions for privacy and transparency that address those concerns. OpenSAFELY was the single most strongly supported NHS data initiative in a major Citizens Jury sponsored by the NDG and NHSX: the Jury's only concern was that OpenSAFELY might be closed after COPI ended! Art of the Possible OpenSAFELY has finally proved it is possible to "have your cake and eat it" with NHS data: to have massive access to massive volumes of data but also preserve patient privacy and patient trust. It has proved that the NHS can deliver large scale data analytics in broad collaboration at reasonable cost for both research and service improvement. |
| URL | http://opensafely.org/about |
| Title | OpenSAFELY-TPP and OpenSAFELY-EMIS |
| Description | OpenSAFELY is a productive, highly secure, transparent, non-commercial, fully open-source software platform specifically developed for analysis of NHS electronic health records data. It can be deployed in any data centre to create a TRE with unprecedented security, transparency, and efficiency. With these privacy protections the OpenSAFELY team has earned public trust to implement OpenSAFELY across an unprecedented volume of NHS patient data. OpenSAFELY-TPP and OpenSAFELY-EMIS: 58 million full GP records OpenSAFELY has been fully implemented inside the data centres of TPP and EMIS, the two largest GP EHR providers in England, under COPI. This delivers analyses across the full raw primary care records of 58 million patients. Data includes all diagnoses, blood tests, prescriptions, investigations, and referrals. In total it is over 60 billion rows of detailed NHS data. This GP data has never been accessible before at national scale, and is not available from any other source (GPES in NHSD and ONS is a smaller derivative GP dataset). Other routes to access GP data have struggled with privacy and delivery problems. OpenSAFELY has active positive support from the professions and Citizens Juries. OpenSAFELY also has active positive support from privacy campaigners who typically block access to GP data at this scale. This is only possible because of the new approaches to privacy preservation and transparency in the OpenSAFELY tools. Additional datasets are easily and regularly ingested and linked in OpenSAFELY A range of crucial datasets for NHS service monitoring and academic research have already been linked on, including: SUS (hospital admissions, outpatient visits); ECDS (coded A&E attendances); CPNS (death in hospital from Covid); SGSS (Covid test results); Covid vaccination data; ONS (cause of death in and out of hospital); Household data (other pseudonymised occupants, is it a care home, approx location); ICNARC (ICU data); ISARIC (detailed hospital records of hospitalised covid patients); ONS Covid Infection Survey; And more. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | All OpenSAFELY outputs as per the rest of this RF submission. In addition there are currently 30 projects from 18 organisations being executed in OpenSAFELY. |
| URL | http://OpenSAFELY.org |
| Description | OpenSAFELY in collaboration with LSHTM EHR team and EHR vendors EMIS and TPP |
| Organisation | EMIS Group |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | OpenSAFELY |
| Collaborator Contribution | We devised and coordinated the project and built the software and delivered substantial research within it. LSHTM collaborated closely on a wide range of research outputs. TPP collaborated closely on code, project design and vision, and delivered the database and backend. |
| Impact | All of the OpenSAFELY outputs are by this collaboration. |
| Start Year | 2020 |
| Description | OpenSAFELY in collaboration with LSHTM EHR team and EHR vendors EMIS and TPP |
| Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
| Department | Faculty of Epidemiology and Population Health |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | OpenSAFELY |
| Collaborator Contribution | We devised and coordinated the project and built the software and delivered substantial research within it. LSHTM collaborated closely on a wide range of research outputs. TPP collaborated closely on code, project design and vision, and delivered the database and backend. |
| Impact | All of the OpenSAFELY outputs are by this collaboration. |
| Start Year | 2020 |
| Title | OpenSAFELY platform code |
| Description | OpenSAFELY is a new, secure, fully open source analytics platform for electronic health records research deployed in OpenSAFELY-TPP and OpenSAFELY-EMIS. |
| Type Of Technology | Software |
| Year Produced | 2021 |
| Open Source License? | Yes |
| Impact | Multiple papers and analyses, substantial policy impact leading in part to the Goldacre Review: https://www.gov.uk/government/news/new-review-into-use-of-health-data-for-research-and-analysis |
| URL | http://OpenSAFELY.org |
| Description | OpenSAFELY public website |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | OpenSAFELY has a public facing website (https://www.opensafely.org/) which describes, for a lay audience: how OpenSAFELY keeps patient data safe; which projects have been approved by the platform; and what research has been produced. |
| Year(s) Of Engagement Activity | 2020,2021,2022 |
| URL | https://www.opensafely.org/ |
| Description | Participation in a series of Citizens' Juries on Health Data Sharing in a Pandemic |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | In collaboration with NHSX and the National Data Guardian for Health and Social Care, the NIHR ARC-GM commissioned a set of three online citizens' juries about health data sharing in a pandemic between March and May 2021. The juries each spent eight days listening to evidence and deliberating on three national data sharing initiatives which were introduced to tackle the pandemic. The juries concluded that the government was right to use emergency powers to share patient data during the Covid pandemic but greater transparency is needed. OpenSAFELY was one of the data sharing initiatives reviewed by the the juries with a member of the team acting as the 'expert witness' and presenting to all three juries. The juries concluded that OpenSAFELY was, out of the three initiatives, the most trustworthy and transparent. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://www.arc-gm.nihr.ac.uk/projects/Citizens-Juries-on-Health-Data-Sharing-in-a-Pandemic |