NHS Digital Data Release Register - reformatted
Lancashire Care NHS Foundation Trust projects
1 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
A single consolidated new request for commissioning purposes - Lancashire Care NHS Foundation Trust (Hosting the Innovation Agency) — NIC-79728-X2C2X
Opt outs honoured: N (Excuses: Does not include the flow of confidential data)
Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (NHS Trust)
Sensitive: Sensitive
When:DSA runs 2019-04 – 2020-03 2017.12 — 2018.02.
Access method: Ongoing
Data-controller type: LANCASHIRE & SOUTH CUMBRIA NHS FOUNDATION TRUST
Sublicensing allowed: No
AGD/predecessor discussions: igard-minutes-20th-september-2018.pdf, IGARD_Minutes_30.03.17.pdf, IGARD_Minutes_16.02.17.pdf, IGARD_Minutes_02.03.17.pdf, igard-minutes-15th-november-2018---final.pdf
Datasets:
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
Type of data: Anonymised - ICO Code Compliant
Objectives:
Objective for processing:
This is a new application for the following purposes:
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the area based on the full analysis of the linked pseudonymised SUS and Local Provider flows. This data will be shared with the NWC Connected Health Cities Analysis Team to develop new pathway indicators for clinical pathways relevant to North West Coast CCG – geographical area.
The emphasis of this early phase of the CHC project is in developing information models and processes that the health service can use to improve care pathway delivery directly.
The CHC Programme aims to:
- Support the development and delivery of innovative information models and algorithms to front line staff in timely ways that enable them to better plan, review and adjust the care they offer.
- Support the development and delivery of innovative information models and algorithms to front line staff in timely ways that enable them to and develop and monitor new and/or more effective pathways
- Develop models for connecting and engaging people with expertise and experience from across the health, social, local government, voluntary, commercial and public sectors to turn data into information into knowledge
This data will enable the NWC CHC Programme to test and define the CHC programme processes. The programme is ultimately aiming for regional coverage, so further applications will follow from other partner CCGs to cover the programme’s requirements in due course.
No record level data will be linked other than as specifically detailed within this application/agreement. Record level data or aggregated data containing small numbers will not be shared with any third party, including the CHC partner organisations, other than the data processor and controller named in this agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
Yielded Benefits:
By using the SUS data, the project team has gained a clear understanding around three pathways - alcoholic liver disease, COPD and epilepsy to provide information to inform actions on emergency and unplanned admissions. In particular, generating alcohol reports detailing the profiling of admissions, patient characteristics and patient care pathways. This project is already generating insights which are being picked up by regional quality improvement teams and the team is hoping to feed insights into Public Health England Intelligence teams, so that these methods are impactful at a national level. This work with individual Trusts is ongoing. The epilepsy reports detailing management of seizure patients within A&E and onward referral to neurology clinics is influencing services and how they manage seizure patients. The team is looking to evaluate how the findings have improved outcomes for these patients. The work is also influencing the National Seizures Audit Team. Reports on COPD indicating unplanned and emergency admissions are looking at how the team can support local services to improve management of COPD patients. This forms part of regional objectives. All reports have been circulated to key clinicians in the North West Coast region and feedback collected as part of the implementation of a learning health system. The team has developed the technical tools and algorithms which can extract data and models to analyse and gain insights from the data. The models will be better refined with more data and will be able to identify where services have been improved or developed. The team is currently working towards supporting regional teams to embed the work across and working with individual trusts and CCGs as well as health systems. Extending the data flows to support this project until 2020 will ensure that the team is able to refine the tools as well as look at the impact of services and changes to services over a longer time period to demonstrate the impact on patient outcomes. The aim is to have individual regions able to use these tools and techniques by 2020. As well as working on reports for COPD admissions, patient characteristics and care pathways, analysis of the SUS data for Wirral has enabled the team to identify COPD hotspots and to offer an intervention tool at GP practices. SUS analysis in future will allow the team to assess the impact of this intervention. Hotspots have also been identified for the Preston area where the same intervention is being planned.
Expected Benefits:
Expected measurable benefits to health and/or social care including target date:
Our CHC Demonstrator project will pilot new fluid and flexible Intelligence models, rapidly sourcing, managing and mining bigger quantities of pseudonymised data.
By the project end:
A demonstrator will have been produced which provides:
- algorithms, tools and models which have facilitated improvements to clinical pathways for our two chosen areas and which will drive future pathway improvements
- mechanisms which will improve the quality, depth and consequent value of future data reporting.
In the future the resulting algorithms, tools and models will be made available to organisations such as CCGs and CSUs.
Outputs:
Specific outputs expected, including target date:
By June 2017 the CHC project will:
- Define core datasets, outcome measures and metrics for the selected pathways
- Identify opportunities to use novel data linkage or analysis to improve intelligence about the progress of patients along the chosen pathways and communication between services
By November 2017:
- Documented results from investigating the broader potential ‘open’ sources of data that are available (e.g. alcohol sales or ‘events’ information to predict demand for emergency services, or social media to understand patient experience) to further inform either local and regional policy development or new intelligent indicators to guide clinical service development and design.
- Produce aggregated reporting outputs and algorithms capable of identifying service variation and granular clinical cohorts within the selected clinical pathways.
By January 2018, outputs will include:
- innovative, multi-dimensional analysis models built on consistently pseudonymised and linked data, tailored to the precise needs of a wide range of operational managers and clinicians
- High level data models, and infrastructure design models, for managing nationally defined pseudonymised datasets at scale will be available to support more robust service evaluation and planning within the selected Clinical Pathways
- Algorithms built on the CHC pseudonymised data collections to identify, categorise and monitor granular patient level cohorts will be available for testing to Clinicians and professionals working within the specific clinical areas
- Algorithm testing and validity reports will have been delivered to provide assurance around the information governance, statistical and technical approaches utilised by the programme
- A first level ‘documented issues’ report outlining the challenges and obstacles to the utilisation of pseudonymised and linked data will be available for public review (Data Quality, IG Barriers etc)
1. Define core datasets, outcome measures and metrics for the selected pathways
2. Identify opportunities to use novel data linkage or analysis to improve intelligence about the progress of patients along the chosen pathways and communication between services
3. Investigate the broader potential ‘open’ sources of data that are available (e.g. alcohol sales or ‘events’ information to predict demand for emergency services, or social media to understand patient experience) to further inform either local and regional policy development and new intelligent indicators to guide clinical service development and design.
4. Enforce the highest information security and governance standards
5. Produce aggregated reporting outputs and algorithms capable of identifying service variation and granular clinical cohorts within the selected clinical pathways.
Processing:
Processing activities:
1) North West Data Services for Commissioners Regional Office (North West DSCRO – part of NHS Digital) receives a flow of identifiable SUS data. North West DSCRO also receives identifiable local provider data directly from Providers.
2) Data quality management and pseudonymisation of data is completed by North West DSCRO and the pseudonymised data is then passed securely to Arden and GEM CSU for the addition of derived fields and analysis.
3) Arden and GEM CSU then pass the processed, pseudonymised data to the secure AIMES CHC Data Warehouse environment for the addition of derived fields and the linkage of SUS and Local Provider data sets.
4) AIMES CHC Data Warehouse will then make the processed, pseudonymised and linked data available to Lancashire Care NHS Foundation Trust who hosts the CHC programme. All analysts are either:
5) Substantive employees of the trust or
6) Individuals employed by the University of Liverpool working under Honorary Contracts
Access is via secure VPN and analysis of the data is to identify patient cohort journeys for pathways or service design, re-design and de-commissioning.
7) Patient level data will not be shared outside of the Data Controller and will only be shared within the Data Controller on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. Only aggregated reports with small number suppression can be shared externally.
Aimes may only process the data as defined within this agreement, and the data controller will ensure that a robust agreement is in place with AIMES to ensure that any requirements within this agreement are in place with AIMES.
Once data is sent from Arden and GEM CSU, the data will be deleted and not held on the CSU servers. Arden and GEM CSU will not share data with any organisations other that those listed within the Data Sharing Agreement.