NHS Digital Data Release Register - reformatted
Powys Teaching Lhb
Project 1 — DARS-NIC-95658-C4F7D
Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)
When: 2020/02 — 2021/04.
Repeats: Frequent Adhoc Flow, One-Off
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information'
Categories: Anonymised - ICO code compliant
- SUS for Commissioners
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the Health board area. The Health Boards commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) The pseudonymised data is required to for the following purposes: § Population health management: · Understanding the interdependency of care services · Targeting care more effectively · Using value as the redesign principle § Data Quality and Validation – allowing data quality checks on the submitted data § Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them § Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs § Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated § Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another § Service redesign § Health Needs Assessment – identification of underlying disease prevalence within the local population § Patient stratification and predictive modelling - to highlight patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models 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 Health Board area based on the full analysis of multiple pseudonymised datasets. Processing for commissioning will be conducted by NHS Midlands and Lancashire Commissioning Support Unit.
1. Identification of frequent attenders across multiple Health services throughout Wales and into England facilitating working with GP practices who are then able to proactively review the care for these high risk patients, this has led to; a. Improved Patient Care pathways to reduce attendance in Emergency and Elective Care in Secondary Care services. b. Identifying Cost savings for the NHS across Health Boards/Authorities due to reduced admissions into Secondary Care, as well as identifying investment available for more early intervention approaches. c. Better patient outcomes due to earlier intervention in Primary Care; 2. Linked to the above, the Powys THB has introduced Virtual Ward and Community Resource Teams to proactively manage patients in the primary Care setting. Given the complexities of the patient flows for Powys residents, and given Powys does not have a District General Hospital (DGH), approximately half of our patients access DGH’s in Wales and half in England with each having different £ currencies and charging mechanisms. This makes understanding and managing the whole system healthcare an incredibly complex task. The use of the pseudo data, when supplemented with Welsh Provider data, has for the first time given us a whole system costed dataset. This has directly led to identification of opportunities to reduce emergency admissions with more proactive Primary & Community care. This has resulted in a £1m investment, in GP’s and Practice based clinical staff, in proactive care in a primary care and community care setting which has reduced admissions (and growth in admission) considerably since it’s initiation, directly leading to better care and outcomes for Powys residents. Given the complex Commissioning and contracting landscape of Powys THB, there has been a lack of investment in local services. This has historically been due to limited information availability on cross-border flows and a high degree of financial uncertainty to support Business Cases with evidence based activity & accurate costings to facilitate changes to services and patient flows. The SUS dataset, together with costed national Welsh data, has been instrumental in identifying opportunities that the THB has taken forward; these include: Local Nurse led Endoscopy services. Investing in local services (local Theatre team including Nurse Endoscopists) to meet an accurate assessment of demand with surety of savings given accurate tariff information. Identified unwarranted variation in Respiratory admissions across the county. This identified unmet demand in many parts of Powys, identifying the requirement and facilitating the development of Respiratory Nurse Led services leading to reduced emergency admissions. (at least five Respiratory nurses have been recruited on the back of this). Identified unwarranted variation in Ear, Nose & Throat (ENT), Outpatients and procedures across the county. This identified unmet demand in many parts of Powys, identifying the requirement and facilitating the development of ENT Specialist Nurse Led services leading to reduced consultant referrals. (three whole time equivalents (WTE) Ear Care nurses have been recruited on the back of this). Identified unwarranted variation in Urology Outpatients (& procedures) across the county. This identified unmet demand in many parts of Powys, identifying the requirement and facilitating the development of Continence Specialist Nurse Led services leading to reduced consultant referrals. Powys THB relies on the pseudo record level data to help it understand the complexity of the PBR tariff and it’s complex iterations each year. It uses this information to validate the LTA numbers and charges from neighbouring providers in England. This work has on many occasions led to successful challenges with providers when tariffs charged on the LTA were not in line with pre-set agreements. Cumulatively this has saved the HB many £m’s over the years, which has been invested in local front line care. The knowledge gained on the Payment by Results (PbR) tariff also gives the THB full assurance on the financial implications and assumptions for service changes. Simply without this many changes would not have occurred leading to poorer outcomes for the Powys Population. An accurate costed patient level dataset for both Welsh and English Service provision is the bedrock of the HB’s: · identification of opportunities to improve patient care, in line with the THB’s Value based Healthcare approach. · planning of service change, and · accurate financial assessment thereof. All of this work needs to be robust before changes can be enacted. This type of information is core for all commissioners across the country, and presently it is unnecessarily complex when Powys THB is not able to have a seamless English + Welsh combined dataset to give it a whole system approach. Ultimately this is getting in the way of service development disadvantaging Powys residents and leading to poorer and more expensive health outcomes as a result.
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. Helth Board outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the Health Board. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. 14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. 15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice. 16. Provision of indicators of health problems, and patterns of risk within the commissioning region. 17. Support of benchmarking for evaluating progress in future years.
COMMISSIONING 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for Health Board Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Comparators of Health Board performance with similar Health Boards as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o Most expensive patients (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die. 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust. 17. Removal of patients from Risk Stratification reports. 18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Data must only be used as stipulated within this Data Sharing Agreement. Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake. Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) ONWARD SHARING: Patient level data will not be shared outside of the Health Board unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set. SEGREGATION: Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Data Minimisation in relation to the data sets listed within section 3 are listed below. This also includes the purpose on which they would be applied - For the purpose of Commissioning: • Patients who are normally registered and/or resident within the Powys Teaching Local Health Board geographical footprint (including historical activity where the patient was previously registered or resident in another Local Health Board). and/or • Patients treated by a provider where the Local Health Board is the host/co-ordinating Powys Teaching Local Health Board and/or has the primary responsibility for the provider services in the local health economy – this only relates to both national and local flows. and/or • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the Powys Teaching Local Health Board - this only relates to both national and local flows. Lima Networks UK Ltd supply IT infrastructure and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – NHS Midlands and Lancashire Commissioning Support Unit 1. Pseudonymised SUS only is securely transferred from the DSCRO to NHS Midlands and Lancashire Commissioning Support Unit. 2. NHS Midlands and Lancashire Commissioning Support Unit add derived fields, link data and provide analysis to: o See patient journeys for pathways or service design, re-design and de-commissioning o Check recorded activity against contracts or invoices and facilitate discussions with providers. o Undertake population health management o Undertake data quality and validation checks o Thoroughly investigate the needs of the population o Understand cohorts of residents who are at risk o Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. NHS Midlands and Lancashire Commissioning Support Unit then pass the processed, pseudonymised and linked data to Powys Teaching Local Health Board. 5. Aggregation of required data for Powys Teaching Local Health Board management use will be completed by NHS Midlands and Lancashire Commissioning Support Unit as instructed by the Powys Teaching Local Health Board or the Powys Teaching Local Health Board. 6. Patient level data will not be shared outside of Powys Teaching Local Health Board and will only be shared within Powys Teaching Local Health Board on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.