Discover-NOW: The Health Data Research Hub for Real World Evidence
Lead Research Organisation:
Imperial College London
Department Name: UNLISTED
Abstract
"Information is collected every time a patient sees their GP or attends hospital. This is used by patients and care teams to ensure the best care is delivered. With appropriate controls and consent, the de-identified data can also be used to support research to find new ways to diagnose and treat disease and make care better and safer.
North West London and Greater Manchester are home to some of the world’s leading hospitals and research organisations. We want to work across these ecosystems to build an applied research database that can help scientists and companies develop a new generation of tools and services that could help us manage many diseases and, in many cases, prevent them happening in the first place.
Building innovative healthcare technologies is possible only through partnership. We will work closely with local communities and patient groups to involve and engage them throughout in completely new ways, ensuring their data is only used under appropriate controls and consent.
There are substantial opportunities to improve healthcare through advances in genomics, artificial-intelligence and digital health and as a Digital Innovation Hub, we feel that we can undertake cutting edge research and develop new healthcare tools in a trusted way."
North West London and Greater Manchester are home to some of the world’s leading hospitals and research organisations. We want to work across these ecosystems to build an applied research database that can help scientists and companies develop a new generation of tools and services that could help us manage many diseases and, in many cases, prevent them happening in the first place.
Building innovative healthcare technologies is possible only through partnership. We will work closely with local communities and patient groups to involve and engage them throughout in completely new ways, ensuring their data is only used under appropriate controls and consent.
There are substantial opportunities to improve healthcare through advances in genomics, artificial-intelligence and digital health and as a Digital Innovation Hub, we feel that we can undertake cutting edge research and develop new healthcare tools in a trusted way."
Technical Summary
"Advanced technologies encompassing digital health, genomics and artificial intelligence (AI) promise to transform healthcare, free up staff time and empower citizens to better manage their health and well-being. This proposal (Discover-NOW, Clinical Trials and Real-World Evidence Hub category) sets out our aspiration to achieve this goal by establishing a secure, real-time, curated longitudinal health record initially focused on the diverse population of North West London (NWL) but in time scaling to all of London. We are also partnering with NorthWest EHealth (NWEH) in Manchester to make even more data discoverable and align functionality across the two leading longitudinal datasets.Trusted and appropriately governed access will support partners to develop new products for direct care that have the potential to dramatically improve outcomes and effectiveness through:
1. Novel clinical trial methodology that identifies new patterns and associations of disease and its effective treatment;
2. The development of apps, sensors and algorithms that benefit from real-time access to appropriately de-identified data encompassing, electronic health record
Discover-NOW builds on the strong foundations of Discover and NWEH:
2.3million diverse citizens from around the world call NWL home, meaning solutions built should be applicable globally;
1.1million additional patients from NWEH;
Deep trust and confidence have already been built with our citizens through their extensive engagement;
Discover, already one of the UKs leading longitudinal datasets, links data for 400 custodians across primary, secondary, community and mental health services and world-renowned specialist hospitals;
NWEH powered the innovative Real-World Evidence (RWE) Salford Lung Study;
Experience in the use of real-world data to improve direct-care and operational efficiency including RWE clinical trials;
Through Imperial College Healthcare Trust (ICHT), we work with leading scientists and clinicians at the forefront of precision medicine, therapeutics and AI;
We have long-standing and successful collaborations with industry that have powered cutting edge research and investment.
To establish Discover-NOW as a leading real-time longitudinal research dataset, we will use the Hub funding to:
Make more de-identified data discoverable by partnering with NWEH;
Move Discover to a high-performance cloud-based computing platform able to support traditional analytics and advanced AI;
Grow industry partnerships by providing access to our expertise and work closely with other DIHs and Local Health and Care Record Exemplars (LHCRE);
Introduce standards that promote the protection of privacy and data security and the proportionate use of data;
Shape what we do through the innovative deliberative engagement as part of our local LHCRE (OneLondon)."
1. Novel clinical trial methodology that identifies new patterns and associations of disease and its effective treatment;
2. The development of apps, sensors and algorithms that benefit from real-time access to appropriately de-identified data encompassing, electronic health record
Discover-NOW builds on the strong foundations of Discover and NWEH:
2.3million diverse citizens from around the world call NWL home, meaning solutions built should be applicable globally;
1.1million additional patients from NWEH;
Deep trust and confidence have already been built with our citizens through their extensive engagement;
Discover, already one of the UKs leading longitudinal datasets, links data for 400 custodians across primary, secondary, community and mental health services and world-renowned specialist hospitals;
NWEH powered the innovative Real-World Evidence (RWE) Salford Lung Study;
Experience in the use of real-world data to improve direct-care and operational efficiency including RWE clinical trials;
Through Imperial College Healthcare Trust (ICHT), we work with leading scientists and clinicians at the forefront of precision medicine, therapeutics and AI;
We have long-standing and successful collaborations with industry that have powered cutting edge research and investment.
To establish Discover-NOW as a leading real-time longitudinal research dataset, we will use the Hub funding to:
Make more de-identified data discoverable by partnering with NWEH;
Move Discover to a high-performance cloud-based computing platform able to support traditional analytics and advanced AI;
Grow industry partnerships by providing access to our expertise and work closely with other DIHs and Local Health and Care Record Exemplars (LHCRE);
Introduce standards that promote the protection of privacy and data security and the proportionate use of data;
Shape what we do through the innovative deliberative engagement as part of our local LHCRE (OneLondon)."
People |
ORCID iD |
Publications
Pollock KG
(2020)
Application of a machine learning algorithm for detection of atrial fibrillation in secondary care.
in International journal of cardiology. Heart & vasculature
Szymanski T
(2022)
Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients.
in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Sharma A
(2022)
Clinical characteristics and comorbidities associated with testosterone prescribing in men.
in Clinical endocrinology
Sekelj S
(2021)
Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study.
in European journal of preventive cardiology
Levy ML
(2021)
Risks of poor asthma outcome in 14,405 children and young people in London.
in NPJ primary care respiratory medicine
| Description | Patient and public involvement and engagement (PPIE) in decision-making around health and care data |
| Geographic Reach | National |
| Policy Influence Type | Contribution to new or Improved professional practice |
| Impact | Through our PPIE activity we have tried to establish a different relationship with the public - working in partnership with them to shape our work and to deliver and evaluate it. It is core to what we do and means we have been able to move further, faster. We are also proactively contributing to the wider cultural shift around PPIE in data through the HDRUK network. Our newly launched Discover-NOW website has a dedicated section highlighting our work with patients and the public, developed with feedback from our Citizen Partners. We also share regular case studies and blogs on both our own channels and HDRUK's. This has been key to raising awareness, demonstrating transparency and encouraging more citizens to participate, with benefits for the NHS, the life sciences sectors and our populations at large. |
| URL | https://discover-now.co.uk/patients-and-public/ |
| Title | Air Pollution Exposure Estimate |
| Description | Modelled concentrations (µg/m3) of annual average nitrogen dioxide (NO2) and particulate matter with diameter <2.5µm (PM2.5) were linked to postcode centroids in Greater London. Air pollution exposure estimates (i.e. concentrations) were derived using models developed for the year 2015 by overlaying the x,y location of postcode centroids with NO2 and PM2.5 maps (25m x 25m resolution) within a geographic information system (GIS). Following analysis of changes in air pollution measurements over time, using routine monitoring data from the DEFRA-run Automatic Urban and Rural Network (AURN), we made adjustments to the 2015 modelled concentrations to estimate 2010 to 2019 exposures using a method know as 'differencing' (Gulliver et al. 2013). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Modelled concentrations of annual average nitrogen dioxide (NO2) and particulate matter with diameter <2.5µm (PM2.5) were linked to postcode centroids in Greater London. The pollution values are joined to NWL Registered population using current postcode for research purposes for e.g. looking at impact of pollution on patients with Asthma |
| URL | https://web.www.healthdatagateway.org/dataset/584cbecc-43ef-4015-adf7-ff70178d7abe |
| Title | Consent to Contact Register |
| Description | The Consent to contact register includes data from NWL Health Research Register. The consent to contact register has been established to expedite and increase participation in health research projects using one of the largest depersonalised linked health data sets in Europe: the Discover data set, so making an important contribution to future of healthcare NWL London area and beyond. The consent to Contact register included name, address, telephone numbers, email addresses, contact preference and where they provided consent. We currently have over 55 thousand patients from NWL Registered Practices who have consented to contact for research. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The register is database of individuals who agree to be contacted about research projects and once contacted and registered, linking them with the matching health record in the Discover dataset. This enables researchers to identify cohorts of anonymised individuals who may wish to take part in a study related to their condition or elements of their personal health relating to the research programme. The registers' interoperability with the Discover dataset has delivered impact by enabling over 1000 North West Londoners to participate in research over the last year and researchers to identify eligible cohorts of volunteers to take part in clinical trials, surveys and evaluations of health management tools. For case studies please visit https://www.registerfordiscover.org.uk/researchers/case-studies. The latest acceleration of the consented patients on the NWL Register has provided strategic opportunities for consent service to be scaled pan-London via the OneLondon LHCR programme and also promoting the patient and recruitment service to a wide range of academic and clinical researchers, working closely with NWL Clinical Research Network. |
| URL | https://www.registerfordiscover.org.uk/ |
| Title | Enabling COVID research opportunity through improvement to data access |
| Description | Discover-NOW has enabled timely review of research opportunities to access the rapidly improving dataset during the crisis, through supporting the establishment of the COVID-19 NWL Data Prioritisation Group. |
| Type Of Material | Data handling & control |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | To make the most of opportunities for users across all data improvements, we know it is essential that data can be safely accessed and used within an appropriate timescale, especially in the fast-paced world of COVID-19. This group met weekly to review operational and research requests for COVID-19 related issues to access the Discover data and to date approving over 30 research applications from a range of sectors including academic, SMEs, national bodies (ONS) and the NHS. |
| Title | HDRUK Catalyst Project |
| Description | Revalidation of x3 AI predictive models for Type 2 Diabetes |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2021 |
| Provided To Others? | No |
| Impact | Working in collaboration with digital partners My Way Digital Health. Revalidation of x3 AI predictive models for Type 2 Diabetes in the North West London Dataset using Data Robot. Linking these models to end user interfaces. Piloting, iterating and evaluating these interfaces. |
| Title | HUMA Type 2 Diabetes |
| Description | Patients with Type 2 Diabetes have submitted information via the remote montoring app - this includes daily and weekly recording of information for clinical review. Through video consultation and remote monitoring via the Huma app, patients are seen more regularly and their data is reviewed more frequently. This helps to reduce cost and improve patient experience. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | HUMA type 2 diabetes data was collected by using a remote monitroing app, providing deeper insight into the delivery of care, and therefore improving value-based and personalised care. It will also give deeper insight into patient journeys, disease progression and new possibilities to improve care at scale. |
| URL | https://discover-now.co.uk/case-study/improve-patient-care-through-remote-monitoring/ |
| Title | Implementing of diabetes templates in all primary care sites in NWL |
| Description | Implementation of diabetes templates in all primary care sites in NWL (Systm1 and EMIS) improving data going into Discover from the source. |
| Type Of Material | Data handling & control |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Historically GP templates have only allowed the clinicians to input free text into patient records, as a result vital patient information was unable to enter Discover for researchers. The templates now focus on inputting patient data using dropdown lists which coordinate with SNOMED codes, alongside very limited use of free text. Benefiting researchers by provider consistency in coding and increasing the ability to derive insights from patient data which was unavailable when in free text format. Templates have been implemented in all primary care sites in NWL in turn improving all primary care data entering Discover. The implementation of these templates has had a positive impact on the quality and consistency of clinical care and patient involvement in their own care. |
| Title | Implementing templates to support the capture of Heart Failure information in NWL |
| Description | Prior to this project clinical sites had no template to input patient's HF information, this has resulted in vital patent information being stored in free text boxes which are not captured by Discover and researchers. Also, old templates often contained biomarker boxes which are no longer in use often leading to inaccuracies in the data inputted and entering Discover. |
| Type Of Material | Data handling & control |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Heart Failure (HF) templates have now been implemented in primary care sites using Systm1 and at Imperial College Heathcare Trust secondary care sites thorough put the HF pathway. Systm1 primary care sites have stopped using a fully free text approach and are now using SNOMED codes which is improving the quality of coding entering Discover. The use of these templates has directly improved the quality and granularity of the information entering Discover along the HF patient pathway and any HF related research. |
| Title | Improved coding and templates to understand and manage post COVID-19 syndrome |
| Description | Implementing standard SNOMED templates into Electronic Health Records in all care settings. |
| Type Of Material | Data analysis technique |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | Working with primary and secondary care, the Discover-NOW team are implementing standard templates into Electronic Health Records in all care settings in order to better monitor, manage, and research the emerging post COVID-19 syndrome. By using clinically agreed SNOMED coded templates, data quality flowing back to Discover data is improved, enabling better service planning, research, and evaluation of interventions for Hub users. |
| Title | NHS Digital shielded-patient |
| Description | The Shielded Patient List (SPL) is a record of vulnerable patients thought to be at high risk of complications from COVID-19. |
| Type Of Material | Data handling & control |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | Discover-NOW, through linking NHS Digital shielded-patient criteria to Discover data has been able to achieve a richer linked integrated care record than ever before possible. This linkage has enabled NWL to identify and flag those at-risk of worse outcomes from COVID-19, and ensure appropriate measures are put in place to reduce risk. Discover data is ready to be used in future research into the impact of the shielded patient processes to inform any further waves or pandemics. |
| URL | https://digital.nhs.uk/coronavirus/shielded-patient-list |
| Title | North West London COVID-19 Patient Level Situation Report (NWL COVID19 SITREP |
| Description | The Daily Situation Report collects data on: the number of urgent operations cancelled, including those cancelled for the 2nd time or more, throughout the month critical care capacity, including adult, paediatric and neonatal available and occupied critical care beds |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | The Discover-NOW team worked with hospital Business-Intelligence teams to link daily patient-level data on admissions, ICU beduse, and HDU bed use into Discover data, enabling forcasting of hospital and critical care demand and capacity for NWL. The NWL ICS now relies on this data to plan hospital capacity and patients transfers across the system. In the future this data will also be used for economic analysis and pandemic research. |
| URL | https://metadata-catalogue.org/hdruk/#/catalogue/dataModel/04f22c93-53df-440a-a71a-50d6827450bc/data... |
| Title | North West London Coordinate My Care (NWL CMC) |
| Description | List of patients with CMC care plan (end of life care plan). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | This dataset covers patients across all pathway and information related to their CMC record including resuscitation details. |
| Title | North West London Pathology (NWL PATH) |
| Description | The NWL Pathology linked table is a direct feed from The Doctors Laboratory and North West London Pathology for patients registered within NWL. Some of the data items included are test dates and times, test codes and names and test results. Pathology results from NWL Pathology and Doctors Labs in include COVID-19 Tests. Each patient will be identified by an unique patient key that can be used to link to all other datasets available within Discover-NOW hub |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | While working alongside NHS, Local Authority teams and Hub users, it become apparent that understanding the spread of COVID-19 at a granular level would be key to targeting interventions, preventing local breakouts and keeping vulnerable people safe. It was also clear that the ability to track infection rates would be essential for developing and rolling out targeted vaccination plans and proving their efficacy in the future. The Discover-NOW team worked at pace to safely integrate patient-level laboratory data (see Figure 1) to enable infections to be tracked and to predict COVID-19 healthcare demands. The data sourced contains all lab pathology data including Pillar I COVID-19 test results and all haematology, biochemistry, immunology, microbiology and therapeutic monitoring results for the 2.5m patient records available in Discover-NOW. This data improvement significantly increased the novel research opportunities previously not feasible due to the complexities of collecting so many clinical measures. |
| URL | https://metadata-catalogue.org/hdruk/#/catalogue/dataModel/38194ca7-57f5-40ff-b463-900e306cd40f/summ... |
| Title | North West London Vaccination Data |
| Description | Discover-NOW is receiving data from all vaccination sites in NWL (North West London). This includes acute providers, mass vaccination hubs and primary care sites. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Discover data has also been improved to link with data that includes details of people vaccinated, by vaccine, allowing breakdown by age, gender, ethnicity, indices of deprivation. For local healthcare and public health users, this data linkage has enabled a novel and detailed view of the vaccine rollout ensuring data insight driven resource management. This has ensured that vaccines are getting to the NWL populations that need them the most, tracked against the Joint Committee on Vaccination and Immunisation Priority Lists for vaccination to ensure those at risk are protected. For commissioners and health care professionals, the linked data has also enabled the increased understanding and management of inequalities in vaccination take-up using a population health management approach. The Discover-NOW team achieved this through the development of a COVID-19 vaccination dashboard for use across the health care system to monitor population take up and to target populations at risk. |
| Title | Waiting List Clock Starts |
| Description | The Waiting List weekly Clock Starts linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains all RTT pathways with a clock start date after 23:59 on Sunday 4th April 2021 and before 23:59 on the Sunday of the reporting period and not recorded to date (in a previous submission). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Restoration of elective activity is one of the highest priorities for NHS England and NHS Improvement following the impact of the Covid-19 pandemic. Understanding the composition of the waiting list is critical to managing restoration within North West London. |
| URL | https://web.www.healthdatagateway.org/dataset/2b847fd2-0f65-43b7-84e1-10cec99d699e |
| Title | Waiting List Clock Stops |
| Description | The Waiting List weekly Clock Stops linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains all RTT pathways with a clock stop date after 23:59 on Sunday 4th April 2021 and before 23:59 on the Sunday of the reporting period and not recorded to date (in a previous submission). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Restoration of elective activity is one of the highest priorities for NHS England and NHS Improvement following the impact of the Covid-19 pandemic. Understanding the composition of the waiting list is critical to managing restoration within North West London. |
| URL | https://web.www.healthdatagateway.org/dataset/3f073707-50b4-48cf-93b6-76843519a5c0 |
| Title | Waiting List Diagnostics |
| Description | The Waiting List weekly Diagnostics linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains all open (incomplete) and planned diagnostic waits for modalities in scope DM01 before 23:59 on Sunday of the reporting period. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Restoration of elective activity is one of the highest priorities for NHS England and NHS Improvement following the impact of the Covid-19 pandemic. Understanding the composition of the waiting list is critical to managing restoration within North West London. |
| URL | https://web.www.healthdatagateway.org/dataset/e508951d-e118-4217-84a4-722e50fdd400 |
| Title | Waiting List Open Pathways |
| Description | The Waiting List weekly Open Pathways linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains all open (incomplete) RTT & not current RTT pathways as at 23:59 on the Sunday of the reporting period. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Restoration of elective activity is one of the highest priorities for NHS England and NHS Improvement following the impact of the Covid-19 pandemic. Understanding the composition of the waiting list is critical to managing restoration within North West London. |
| URL | https://web.www.healthdatagateway.org/dataset/c7b1e328-f2d7-4d11-b38f-ce9930b95ca0 |
| Title | Weekly SUS ECDS Dataset |
| Description | The NWL weekly SUS ECDS linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains records of care in A&E within NWL. The Discover-NOW team worked with hospital Business-Intelligence teams to map the weekly SUS CDS data for Emergency Care to help support emergency demand, as well as any other acute capacity work. The CDS data helps with any pathway review/changes that is needed for better patient care. During this pandemic, the frequent data has helped a lot with rising volume of demand in acute providers and helped with forecasting and supporting the changes that were needed. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The NWL weekly SUS ECDS linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains records of care in A&E within NWL and allows for timely use of the data we receive to use for research or patient pathway review. The data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). SUS is usually submitted monthly and so there would be a 1-2 month lag on data to share with researchers. The Emergency Care Data Set (ECDS) collects information about why people attend emergency departments and the treatment they receive to: 1. improve patient care through better and more consistent information 2. allow better planning of healthcare services 3. improve communication between health professionals. V6.2.3 introduces the SNOMED UK preferred term columns and new SNOMED Reference tables. ECDS is better equipped to keep pace with the increasing complexity of delivering emergency care than its predecessor. This means that the improved quality of data collected in emergency departments provides better support to healthcare planning and better informed decision making on improvements to services. This improved data helps the understanding of 1. the complexity and acuity of attending patients; 2. the causes of rising demand 3. the value added by emergency departments ECDS also allows: 1. the capture of better diagnostic data to ensure an enhanced understanding of need, activity and outcomes; 2. consistent monitoring of data across local and national initiatives 3. support for injury surveillance, such that it will be possible to identify patterns that may be amenable to targeted interventions and improved public health Which in turn informs more effective and efficient resource management. The statistics are known to be used for: 1. national policy making 2. benchmarking performance against other hospital providers or CCGs 3. academic research 4. analysing service usage and planning change 5. providing advice to ministers and answering a wide range of parliamentary questions 6. national and local press articles 7. international comparison |
| URL | https://web.www.healthdatagateway.org/dataset/f75b02f0-a45f-433a-a669-420c8bd40720 |
| Title | Weekly SUS Inpatient Dataset |
| Description | The NWL weekly SUS IP linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains Inpatient records of care within NWL. The Discover-NOW team worked with hospital Business-Intelligence teams to map the weekly SUS CDS data for Inpatient Care to help support demand, as well as any other acute capacity work. The CDS data helps with any pathway review/changes that is needed for better patient care. During this pandemic, the frequent data has helped a lot with rising volume of demand in acute providers and helped with forecasting and supporting the changes that were needed. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The NWL weekly SUS IP linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains Inpatient records of care within NWL and allows for timely use of the data we receive to use for research or patient pathway changes. The data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). SUS is usually submitted monthly and so there would be a 1-2 month lag on data to share with researchers. Each SUS record contains a wide range of information about an individual patient admitted to an NHS hospital, including: 1. clinical information about diagnoses and operations 2. patient information, such as age group, gender and ethnicity 3. administrative information, such as dates and methods of admission and discharge 4. geographical information such as where patients are treated and the area where they live The statistics are known to be used for: 1. national policy making 2. benchmarking performance against other hospital providers or CCGs 3. academic research 4. analysing service usage and planning change 5. providing advice to ministers and answering a wide range of parliamentary questions 6. national and local press articles 7. international comparison |
| URL | https://web.www.healthdatagateway.org/dataset/3858647c-5161-45dc-ba49-66a4fc4499c2 |
| Title | Weekly SUS Outpatient Dataset |
| Description | The NWL weekly SUS Outpatient linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains records of care in Outpatients within NWL. The Discover-NOW team worked with hospital Business-Intelligence teams to map the weekly SUS CDS data for Outpatient Care to help support demand, as well as any other acute capacity work. The CDS data helps with any pathway review/changes that is needed for better patient care. During this pandemic, the frequent data has helped a lot with rising volume of demand in acute providers and helped with forecasting and supporting the changes that were needed. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The NWL weekly SUS Outpatient linked table is a weekly submission from our 4 main providers (Imperial College Healthcare Trust, Hillingdon Hospital, Chelsea & Westminister Hospital and London North West Hospital) and contains records of care in Outpatients within NWL and allows for timely use of the data we receive to use for research or patient pathway changes. The data is collected during a patient's time at hospital as part of the Commissioning Data Set (CDS). SUS is usually submitted monthly and so there would be a 1-2 month lag on data to share with researchers. Patients are seen for New/Follow up face to face appointments and now the NHS is giving patients greater control and convenience in their NHS hospital or clinic appointments - by offering telephone or video consultations, empowering people to book their own follow-up care, and working with GPs to avoid the need for an onward referral where possible. This work also plays a significant role in supporting the recovery of hospital services in response to the COVID-19 pandemic. This data is used to monitor the activity levels against what we set out in our Operating Plan. The statistics are known to be used for: 1. national policy making 2. benchmarking performance against other hospital providers or CCGs 3. academic research 4. analysing service usage and planning change 5. providing advice to ministers and answering a wide range of parliamentary questions 6. national and local press articles 7. international comparison |
| URL | https://web.www.healthdatagateway.org/dataset/572cd3e2-9119-40ff-ab2e-49e8a0a02ab8 |
| Description | Janssen Pharmaceuticals |
| Organisation | Johnson & Johnson |
| Department | Safety Pharmacology in Janssen |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We have used the Discover datasets to provide real world evidence in a retrospective study aiming to quantify healthcare resource use and related cost of patients with the burden of active IBD disease compared with a well-controlled disease and the cost impact of anti-TNF versus non anti-TNF biologics. We have a second collaborative study with Janssen looking at the efficacy of utilisation of a biologic in treatment of IBD. In addition to the above, we have a third a retrospective study with Janssen utilising the Discover dataset to investigate the current treatment pathways for Treatment Resistant Depression (TRD) in NWL, and comparison of the care delivered in NWL with the national predefined standards for quality of care in this patient population to inform subsequent action plans to improve care. |
| Collaborator Contribution | Insight into the management of IBD disease as well as funding. |
| Impact | In the first retrospective study, the data from this study has been accepted for presentation as an abstract at the Digestive Disease Week (DDW) meeting May 2022. This will be followed with a full Manuscript. The second retrospective study outcomes are currently being written up as a manuscript for publication in Peer review journals. Similarly, the outcomes of the third study relating to treatment resistant depression is currently being written up as a manuscript for publication in Peer review journals. |
| Start Year | 2020 |
| Description | NorthWest EHealth Limited |
| Organisation | University of Manchester |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We have used the algorithm for the FARSITE tool to incorporate the primary care arm of the Discover dataset. This will enable identifications of patients who may be eligible for participation in clinical trials as well as provision of patient numbers for feasibility studies ahead of retrospective studies. We now aim t additionally incorporate the secondary care arm of the Discover dataset in to this tool to make it even more versatile as a health data research tool. |
| Collaborator Contribution | Provision of the algorithm for the FARSITE platform |
| Impact | The output from this collaboration is the adaptation of the FARSITE health data research tool to the Discover dataset to enable this tool to be used for research in NWL |
| Start Year | 2021 |
| Description | Partnership between Imperial College Health Partners and AstraZeneca |
| Organisation | AstraZeneca |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | With AstraZeneca we have been engaged in transforming the pathway of care for patients suffering with Diabetes, Heart Failure and Chronic Kidney disease (CKD). In this context, we have used the Discover datasets to provide real world deviance in mapping the patient's journey in the health care system, its the associated costs and patient outcomes. Additionally, we have examine inequalities in provision of care for each indication. Specifically, in heart failure, by applying health economic evaluations we have predicted significant improvements in patient outcomes and financial savings as a direct result of implementation of two artificial intelligence powered platforms (Luscii and Eko Duo). Subsequently, we have engaged in small scale clinical studies to establish the accuracy of our predictions and have shown that these platforms can be used to transform the pathway of care for HF patients and bring significant improvements in health outcomes for the patients and significant cost savings to the healthcare system. These findings are currently being prepared as manuscripts for peer reviewed publications. We are currently engaged in replication this transformation of path way of care for patients with CKD and preparing manuscripts for publication from our findings in Diabetes. Pathway transformation accelerates clinical practice improvements and makes them actionable and sustainable. |
| Collaborator Contribution | AstraZeneca (AZ) have provided the funding to support real world evidence generation through application of the Discover dateset and the subsequent health economic evaluation, publication of the data to disseminate the results. Additionally, AZ have supported the clinical application of the AI powered tools , design of the pathways for transformation in each indication through providing funding as well expertise in pathway co-design, bringing the imminent clinical leads together and to the programme to aid implementation and deployment of the transformation steps. Going forward the idea is to scale up these findings and improvements across all ICSs. Pathway transformation closes the gap between national policies, guidelines and actual clinical practice by driving bottom-up change. Additionally, pathway transformation accelerates clinical practice improvements and makes them actionable and sustainable. Our unique partnership with AZ has enabled us to marry our expertise with those of AstraZeneca and clinical specialist to make a significant contribution to the improvement of pathways of care in NWL for patients suffering wit long term conditions such as heart failure, diabetes and CKD. We are currently engaged in presenting the findings from our studies as manuscripts for publication in peer review journals and abstracts for presentation in clinical meetings. In this context, we have 2 publication and one abstract in preparation from the heart failure work and two from the diabetes work. The CKD work is in set up but is equally expected to generate a number publications |
| Impact | N/A |
| Start Year | 2019 |
| Description | Telstra Health UK |
| Organisation | Telstra |
| Country | Australia |
| Sector | Private |
| PI Contribution | We collaborate with Telstra Health to deliver Real World Evidence retrospective studies, Dashboarding studies and Health Economic evaluation. |
| Collaborator Contribution | Telstra Health bring analytic capabilities to our collaboration |
| Impact | We are currently collaborating on production of a number of dashboards with Telstra Health |
| Start Year | 2021 |
| Title | Discover-NOW Trusted Research Environment |
| Description | The Discover-NOW Trusted Research Environment (TRE) is a DID (deidentified ) server which hosts data in a SQL server with data from all care settings: coded primary care, secondary, acute, mental health, community health and social care record for over 2.6 million patients who live and are registered with a GP in North West London. There is also over 50k of patients who have given consent to contact for research purposes. Researchers will be able to analyse the data within this environment and all software required for researchers are made available i.e. R, Python, Excel, Tableau, STATA. We have a number of R packages and Python libraries avilable and have the mechanism to include required packages as requests come from researchers. |
| Type Of Technology | New/Improved Technique/Technology |
| Year Produced | 2019 |
| Impact | The DID SQL server hosts NWL linked dataset, researchers are able to apply for access to this asset by completing the NWL data access form and getting approval from the NWL data access sub-group. We have currently circa 120 'live' projects approved by this committee. Here is a link to the latest projects that have been approved: https://discover-now.co.uk/the-data/data-access-requests/ Case studies following completion of projects on data from this environment is documented here - https://discover-now.co.uk/case-studies/ |
| URL | https://discover-now.co.uk/the-data/data-access-requests/ |
| Title | FARSITE |
| Description | FARSITE is web application which allows, at the front end, participating organisations/researchers to glean more information from an anonymised dataset. It can also allow the data controllers, if required, to access identifiable demographics information in order to recruit for research and improve care. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2020 |
| Impact | FARSITE benefits include: - Improved study success rates - by testing and refining early protocol designs using real world data, clinical expertise, and electronic health record (EHR) know-how - More accurate modelling of potential value - using large, detailed, linked, and longitudinal patient level data from existing electronic health records - Increased confidence of patient recruitment to time and target - Population health management interventions e.g. addressing inequalities in health outcomes for patients with chronic conditions by ethnicity and demographics. - From 2022, we are in the process of including Acute Data into Farsite, this will facilitate Health Research across Primary and Secondary Care. |
| URL | https://imperialcollegehealthpartners.com/discover-now/farsite/ |
| Title | HUMA Remote Monitoring App |
| Description | The Huma Remote Monitoring App is a digital 'hospital at home' and decentralized clinical trial platform that uses real-time health data from smartphones to help patients, clinicians, researchers, and healthcare systems. We have developed a technical solution that enables the data, generated by the patients that are using the HUMA app, to be used in an integrated data platform. The data enables us to identify, quantify and measure the impact of changes made through patient pathways that can then be compared to the standards of care that exist today to evaluate co-designed improvements. |
| Type Of Technology | Webtool/Application |
| Year Produced | 2020 |
| Impact | In collaboration with NHSx, working alongside clinicians and using the remote monitoring service by 'HUMA' (another partner of Discover-NOW), the team were able to digitally enhance clinical practice through 'Community virtual hubs'. During the COVID-19 pandemic, these hubs enabled clinicians to rapidly identify deteriorating patients, react quickly, avoid further complications and better manage system capacity and improve overall survival rates. The HUMA App helped create and deploy a new 12-week intensification of care service, "Fresh Start", for patients with Type 2 Diabetes. The App enabled Virtual Group Consultations with peers and health care professionals and a structured education campaign. All delivered to the patient in their own home. The Fresh Start Evaluation Program is currently in progress and we believe it will deliver a highly sustainable partnership and service offer across North West London. |
| URL | https://discover-now.co.uk/case-study/improve-patient-care-through-remote-monitoring/ |
| Title | North West London (NWL) Health Research Register - a 'consent to contact service' that supports the adult population within North West London to be involved with and participate in health research using real world data. |
| Description | The NWL Health Research Register consent to contact service has been established to expedite and increase participation in health research projects using one of the largest depersonalised linked health data sets in Europe: the Discover data set, so making an important contribution to future of healthcare NWL London area and beyond. The register is database of individuals who agree to be contacted about research projects and once contacted and registered, linking them with the matching health record in the Discover dataset. This enables researchers to identify cohorts of anonymised individuals who may wish to take part in a study related to their condition or elements of their personal health relating to the research programme; NWL Health Research Register team to contact those individuals to invite them to take part in relevant research studies; Researchers to contact research participants, once have consented to be contacted. Since 2021 the Consent to Contact for Research has been implemented onto the CIE (Care Information Exchange) electronic patient record platform which has enabled acceleration of the uptake to over 55 thousand patients from NWL Registered Practices. |
| Type Of Technology | New/Improved Technique/Technology |
| Year Produced | 2019 |
| Impact | The registers' interoperability with the Discover dataset has delivered impact by enabling over 1000 North West Londoners to participate in research over the last year and researchers to identify eligible cohorts of volunteers to take part in clinical trials, surveys and evaluations of health management tools. For case studies please visit https://www.registerfordiscover.org.uk/researchers/case-studies. The latest acceleration of the consented patients on the NWL Register has provided strategic opportunities for consent service to be scaled pan-London via the OneLondon LHCR programme and also promoting the patient and recruitment service to a wide range of academic and clinical researchers, working closely with NWL Clinical Research Network. |
| URL | https://www.registerfordiscover.org.uk/ |
| Description | Asthma pathfinder patient focus group |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Patients, carers and/or patient groups |
| Results and Impact | The asthma pathfinder project is funded by the London Health Data Strategy programme, with a goal to improve the health and wellbeing of Londoners and solve health and care challenges using the power of data at scale. Imperial College Health Partners are key delivery partners, including leading on the PPIE element. The aim of the project is the development of a decision support tool for healthcare professionals, enabling accurate diagnosis, improved prescribing, and targeted interventions to improve asthma care. The current priority is defining what metrics the dashboard should include. To help inform this important stage, the team have delivered x3 workshops with healthcare professionals and a patient focus group (attended by 14 people affected by asthma) to ensure the tool includes data that feels relevant and important to these key audiences. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.digitalhealth.net/2021/12/pathfinder-projects-london-healthcare-data-at-scale/ |
| Description | Chronic Kidney Disease health implementation project - Patient Representatives and co-design |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Patients, carers and/or patient groups |
| Results and Impact | This is a health implementation project being led by Discover-NOW in partnership with one of our industry partners, Astra Zeneca, in conjunction with the London Kidney Network and ARC North West London. The project secured £160k of income to Discover-NOW from the National Insights Programme, funded by NHS England. Our project aims to transform CKD care by using data alongside clinical and patient input to design a new care pathway, which will support early identification and management. The new pathway will seek to improve equality of access, experience, and outcomes through addressing health inequalities. We have recruited two Patient Representatives to support us to plan and deliver the co-design element with patients and to provide strategic input. |
| Year(s) Of Engagement Activity | 2022 |
| Description | Discover-NOW Citizen Advisory Group (CAG) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Discover-NOW is committed to ensuring that all our current and future ways of working reflect and embed the recommendations made by the public through this deliberation. This is particularly evident through the formation of a Citizens Advisory Group (CAG) that is forming part of the Hub's governance structure and future decision making and policy development. We have partnered with Ipsos MORI as CAG design and delivery partners and together are advancing this approach with participants reflective of the north west London population. The group are coming together over the next year in a set of mini-deliberations (similar to the OneLondon Citizens Summit) to explore, discuss and deliberate key dilemmas facing the hub to help inform our next steps. The deliberations have consisted of four virtual workshops in February/ April 2021, comprising c40 people recruited to reflect the North West London population. Each workshop lasted three hours and included a combination of informative expert presentations and moderated group discussions in which smaller groups of around six participants reviewed stimulus materials and deliberated their views, experiences and expectations. These workshops explored the deliberation questions of: "What conditions need to be in place for non-NHS partners (universities, commercial organisations, charities) to have access to health and care data in a trusted research environment?" "How should the value of Discover-NOW's health and care data for research be realised and distributed?" This work is already directly influencing how data is used and accessed for research purposes in North West London. The report and recommendations have been shared and were well received by the Discover-NOW Board and there was unanimous support to embed and align to the recommendations. Specifically: Refining the criteria for data access requests to ensure that data access requests reflect what is important to the CAG Reviewing the membership of the NWL region's existing data access committee to ensure it reflects the recommendations of the CAG. Steering the development of its new Trusted Research Environment and how this can be potentially safely linked with other datasets. This work is viewed as a huge step forward in influencing and shaping how non-NHS organisations will access depersonalised data in a trusted way. As such, these findings are also being shared on a larger scale across our networks in North West London and all the other Health Data Research Hubs nationally. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://discover-now.co.uk/case-study/discover-now-citizen-advisory-group-cag/ |
| Description | Discover-NOW Virtual Launch Event |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | 50-100 people attended a virtual launch event of Discover-NOW's new service offer from the life sciences industry - this comprised of an introduction to Discover-NOW, live case studies and a chance to meet the team. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://www.eventbrite.co.uk/e/discover-now-service-offer-virtual-launch-event-tickets-262462892577 |
| Description | Membership of Board and data access committee |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | Lay members of Discover-NOW have key roles in both the Discover-NOW board and data access committees. The access committee meets regularly to review both operational and research related requests to access the de personalised Discover data for research. |
| Year(s) Of Engagement Activity | 2020,2021 |
| Description | North West London Health Research Register |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | NWL Health Research Register is a register of adults 18 and over living in North West London who are interested in health research and want to find out more about health research opportunities. By joining the register participants will be told about research opportunities that are relevant to them, giving them more opportunities to be involved in creating a healthier future for them and their families. The more people that join NWL Health Research Register, the more people that will potentially participate in research, helping to create a healthier future for all. The COVID-19 pandemic necessitated a shift to virtual recruitment and in response we have introduced a new process for patients to consent via the Care Information Exchange (an electronic patient record used across NWL). This has led to a spike in engagement with the register, with the number of registrants reaching 43,000 - a growth of 70% since the start of the grant award in 2019. We are exploring whether we can scale our impact further by rolling this model out across London. Alongside recruitment via the Care Information Exchange, community outreach with a specific focus on engaging under-represented audiences has continued to be a priority. Our approach has been multi-stranded: - Local radio - Posters in pharmacies - Social Media - Universities - Community groups and faith leaders -Charities and patient groups - Outpatient clinics The register responds to a consistently identified need across multiple sectors of needing to speed up the time it can often take to recruit study participants that match research protocols. The recruitment conversion rate is much higher than other methods - often in the region of 25% - which is delivering real impact for researchers across multiple sectors, speeding up the time it takes to recruit to their studies and avoiding costly delays. |
| Year(s) Of Engagement Activity | 2020,2021,2022 |
| URL | https://www.registerfordiscover.org.uk/ |
| Description | North West London National Data Lab (children and young people's access to mental health care) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Patients, carers and/or patient groups |
| Results and Impact | Imperial College Health Partners (ICHP), Imperial College London and the Institute of Global Health Innovation were successful in being named as one of the five Network Data Labs (NDL) across the UK, funded by the Health Foundation. This is an extremely exciting opportunity for our partnership, as it gives us the opportunity to work with our local community in North West London to identify research priorities for health and care since COVID-19, and translate those findings into practice - helping to reduce inequalities. The current theme is 'children and young people's access to mental health care' and we are using Discover data to delve into how the pandemic has impacted our community. Across the project duration we have involved 100 young people aged 11-25 from NWL - through a focus group, surveys and an ongoing Young People's Advisory Group (YPAG). The perspectives of young people have influenced every stage of our NDL activities from supporting us to identify research topics that matter locally, through to reviewing our early data and supporting us to build a narrative around the trends. As we move towards project completion, the YPAG will also be key partners in helping us share the findings and we are working with one of the members to author a blog. We also have a Professional Reference Group supporting this work. |
| Year(s) Of Engagement Activity | 2021,2022 |
| URL | https://discover-now.co.uk/case-study/network-data-lab-the-young-voices-shaping-our-work-around-chil... |
| Description | North West London Network Data Lab (priority setting) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Engaging community leaders and champions to shape research priorities and understand needs, providing opportunity to explore common areas of interest and avoids risk of duplication and mis-alignment. Imperial College Health Partners (ICHP), Imperial College London and the Institute of Global Health Innovation were successful in being named as one of the five Network Data Labs (NDL) across the UK, funded by the Health Foundation. This is an extremely exciting opportunity for our partnership, as it gives us the opportunity to work with our local community in North West London to identify research priorities for health and care since COVID-19, and translate those findings into practice - helping to reduce inequalities. In North West London we are also very fortunate to have access to a linked data set, known as Discover-NOW, which provides information from primary care, acute, mental health, community and social care. This gives us the unique opportunity to delve deeper into health inequalities, and use data to try and discover how communities have been affected by the pandemic. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://imperialcollegehealthpartners.com/network-data-lab-how-seldom-heard-groups-are-helping-us-sh... |
| Description | Participating in research - Risk Algorithms for Decision Support and Adverse Outcomes Reduction (RADAR) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Study participants or study members |
| Results and Impact | Involving people with lived experience to inform design and development of research tools and methodologies - The project team delivered a series of workshops in January and February with patients living with Type 2 Diabetes in order to gather their feedback on risk prediction tools designed to reduce complications, as well as to gather insight on how conversations about risk are best managed. Valuable feedback was gathered, consolidated and fed into the iteration and will be part of the further development of the risk prediction tools. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://imperialcollegehealthpartners.com/portfolio/predicting-complications-in-diabetes/ |