NHS Digital Data Release Register - reformatted

NHS England

Project 1 — CASEMIX_NHSE

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2016/04 (or before) — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Episode and Spell level grouper results; underlying patient level data.

Objectives:

To inform the decision making process for determination of the scope and structure of the future Grouper Products


Project 2 — DARS-NIC-15336-S8W9K

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/09 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Diagnostic Imaging Dataset

Benefits:

NHS England will utilise DID data to continuously: • Monitor and improve diagnostic imaging services, by measuring access to imaging services • Improve cancer survival rates by reducing referral to treatment times and diagnosing cancers earlier • Reduce unnecessary exposure to radiation by monitoring compliance with clinical guidelines Benefits achieved to date The reported measures for nine key modalities including X-ray, Ultrasound, CT and MRI scans. This provides more information on NHS provision of these services than any other resource and is the only source of national information on some modalities. The trends and patterns of provision demonstrate where there is scope for improving the early of diagnosis of cancer, in particular highlighting the share of referrals made by GPs.

Outputs:

Aggregated data is produced on a monthly basis, using accumulated annual figures, with small numbers suppressed in line with the HES analysis guide. This is published as an official statistic, conforming to National Statistics protocols on a public website https://www.england.nhs.uk/statistics/statistical-work-areas/diagnostic-imaging-dataset/ In additional to production of the official statistics, NHS England will use the DID data to produce ad-hoc reports and analyses for the purposes outlined in the objective for processing section. All outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. No third party will have access to any record level DID data. Outputs already produced Official statistics from the Diagnostic Imaging Dataset (DID) have been published by NHS England (previously Dept of Health) monthly since 2012-13. In addition, annual reports and additional analyses have been published for 2012-13 to 2014-15. Key statistics include: • Number of diagnostic tests performed • Period from referral to test • Period from test to the test report being issued These measures are reported for nine key modalities including X-ray, Ultrasound, CT and MRI scans. In addition, data are published for a subset of tests that are particularly used to identify or discount a diagnosis of cancer. These statistics are published for England and by Provider on a monthly basis and additionally by Commissioner on an annual basis. They are accompanied by information on data quality, coverage and completeness. Additional annual analyses include: • Annual reports incorporating maps and additional analysis by age, sex, referral source and Provider • Annual technical reports that further explain and describe the data collected • Standardised imaging rates by CCG, showing the variation in provision • Supplementary information on other modalities • A comparison of 2013-14 DID imaging activity with other data sources: DM01 and KH12. In addition to the material published on the NHS England web pages, NHS England produce ad hoc analyses to respond to queries raised by our clinical or policy contacts and others via the contact address did@dh.gsi.gov.uk. Examples of the outputs and associated benefits of these analyses include: • Rates of CT virtual Colonoscopy and Barium enema, which were compared with endoscopy rates (from HES) to show areas of best practice • Cardiac imaging comparisons, showing relative proportions of CT and MRI activity • Analysis by day of the week, to inform the debate around 7-day services • Evaluation with CRUK of ‘Be Clear on Cancer’ initiatives such as for ‘Blood in pee’ and Lung cancer, by demonstrating increased diagnostic activity in periods and areas of the publicity campaigns • Usage of individual NICIP or SNOMED CT codes, to review changes in coding practice • Additional analysis to compare DID waiting times with DM01, to investigate delays around diagnostics • Contributions for consideration or use in the Diagnostic Atlas of Variation published by Rightcare at http://www.rightcare.nhs.uk/index.php/atlas/diagnostics-the-nhs-atlas-of-variation-in-diagnostics-services/ • Data quality analyses, to work together with HSCIC to improve the completeness and usability of DID.

Processing:

NHS England currently hold peudonymised DID data from April 2012 onward . The DID data received within this agreement will be added to the DID data already held by NHS England which is used to create monthly and annual Official Statistics publications. DID data will be provided to NHS England on a monthly basis. Each new months’ data is appended to the existing dataset until all files for a financial year have been published. Data is added to the database on 4th of each month and a report is normally published around the third Thursday of the month. NHS England do not hold any identifiable DID data. NHS England will not link DID data to any other data set. All individuals with access to the record level data are employees of NHS England and no third party will have have access to the record level DID data.

Objectives:

The primary purpose of the flow is for production of Official Statistics, answering Parliamentary Questions (PQs) and media queries, which are the current responsibility of NHS England as subject matter experts. In addition, NHS England will use the data for jointly assessing and addressing data quality problems with HSCIC. Access to pseudonymised record level DID data will also enable NHS England: • To perform better analysis of cancer pathways by indicating where, what and when imaging takes place in the pathway • To allow Public Health England to calculate more accurate estimates of the distribution of individual radiation dose estimates from medical exposures • To enable analysis of demographic and geographic variation in access to diagnostic imaging tests • To provide detailed national data on trends and patterns in NHS imaging to demonstrate how expensive equipment and trained workforce are deployed and support capacity planning • To discontinue the existing annual KH12 dataset and reduce burden on providers • To understand and influence issues around delays in access and turnaround times for tests (including analysis of median periods and distributions) • To provide more detailed national data than is otherwise available on test type (modality), body site of test and patient demographics, which can reveal the impact of initiatives to improve outcomes for patients by influencing the type, timing and number of tests • To allow benchmarking in the rate of provision of diagnostic tests overall and in GPs’ direct access to tests, to encourage increased use of tests leading to earlier diagnosis and hence improved outcomes • To inform accreditation processes for imaging departments through the UK Imaging Services Accreditation Scheme and the assessment of imaging services by the Care Quality Commission. • To inform work on development of accurate tariffs for all diagnostic imaging tests


Project 3 — DARS-NIC-18798-V2J6C

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/09 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Outpatients

Benefits:

NHS England has an objective to allow everyone to have greater control of their health and wellbeing, support individuals to live longer, healthier lives by the provision of high quality health and care services that are compassionate, inclusive and constantly-improving. The vision for that was set out in the NHS Five Year Forward View, published in 2014. NHS England's effectiveness in achieving this is summarised in their Annual Report: https://www.england.nhs.uk/wp-content/uploads/2016/07/nhse-annual-rep-201516.pdf Public examples of earlier work drawing on HES outputs that have benefitted patients and Health communities include: • The route map for Urgent and Emergency Care that includes the piloting of outcome metrics to demonstrate improvements for patients: https://www.england.nhs.uk/wp-content/uploads/2015/11/item5-board-20-11-15.pdf. Without these outcome metrics, there is no measure of success for the initiatives implemented. • Publishing a breach rate for mixed sex accommodation that uses HES data in combination with NHS England data: http://www.england.nhs.uk/statistics/statistical-work-areas/mixed-sex-accommodation/. Without this breach rate there would be no accountability and patients would continue to suffer the problems of mixed sex wards. • Tools helping the NHS (and the public) to review and address variation such as the Diagnostic Atlas of Variation: http://www.rightcare.nhs.uk/index.php/atlas/diagnostics-the-nhs-atlas-of-variation-in-diagnostics-services/. Without these tools, local health communities may invest in services that do not provide maximum benefit for patients. • The latest stages of the NHS cancer strategy that include work on improving diagnostic test capacity (drawing on HES analysis): https://www.england.nhs.uk/wp-content/uploads/2016/05/cancer-strategy.pdf. Without this information, there may be insufficient resource put in place to meet demand for cancer diagnostics, leading to worse outcomes.

Outputs:

NHS England use HES data on an ongoing basis for management purposes, for internal review, for information and tools to support the commissioning and provision of NHS services and in publications relevant to NHS England business plan and the objectives of NHS England mandate. The following examples illustrate the ongoing use of the HES data and outputs expected in the coming year: • Enumerating activity for specialised commissioning; • Reviewing trends in diagnostic testing to improve early cancer detection; • Validating the claims of New Care Model vanguards to improve eg emergency admission rates and bed days or A&E attendance for children and young people; • Supporting the Maternity Transformation Programme (currently being launched) to deliver safer, more personalised care; • Contributing to the Right Care Commissioning for Value packs to help CCGs do efficient and effective commissioning; • Informing the Congenital Heart Disease Review to secure the best outcomes for patients; • Providing baselines for the CCG Improvement and Assessment Framework for performance monitoring; • Producing hospital related indicators for the Primary Care Dashboard for GP Practices; • Refining the formula for the Mental health tariff; • Developing system wide indicators for Urgent and Emergency Care Networks, to implement from 2017. In addition, NHS England users will analyse HES data to contribute to many other workstreams and handle briefing requests on an ad hoc basis. Each item is separately commissioned and target dates are set during the programme. Examples of external-facing uses of the data are given in the benefits section below. Recent examples of internal and unpublished briefing, tools and analysis are as follows. • Internal analysis paper investigating the appropriate metric for calculating bed-days; • High-level briefing on trends in the use of the independent sector by the NHS; • Dashboard showing variations in endoscopy provision across England; • Briefing paper assessing evidence for the impact of a New Care Models vanguard. The data are used for internal purposes such as briefing and specialised commissioning, for advising NHS organisations such as Trusts and CCGs or for wider publication such as in the examples below. The data are not used for commercial use. Small numbers are suppressed in line with the HES Analysis Guide.

Processing:

NHS England users access HDIS via a secure portal from encrypted laptops and desktops based in a number of locations. These are encrypted by Bitlocker to the AES-256 standard These devices have the VMware software necessary to access HDIS, but not HDIS itself, which remains always in the NHS Digital remote environment. Access is not possible without additionally having a user id, password and RSA token. NHS Digital grant NHS England the ability to carry out analysis on HES data using the SAS Enterprise Guide analytical tool. Data are viewed and analysed remotely via this secure means. NHS England users also have the ability to locally download record level results, outputs and extracts from the HDIS system. Such downloads are stored and processed securely on NHS England servers (or equivalent for Strategic Clinical Network users who are legally part of NHS England). These are generally in the form of tables for further analysis, aggregation, standardisation and computation or for inclusion in briefing, documents, models and tools. Record level extracts are only required for small numbers of cases where further manipulation is required eg to understand how episodes relate to the same spell, pathway or patient. No patient identifiable data are provided and records are not linked to any other source. The data are not used for commercial use. For all outputs small numbers are suppressed in line with the HES Analysis Guide. Any unsuppressed tables are stored and, where necessary, shared securely with colleagues involved in the analysis of results and the unsuppressed data will not be shared with third parties. The data will be processed for the purposes described in this document. Most tables extracted from HDIS are aggregated to CCG, Hospital provider or national level, but further breakdowns may be required eg to build geographies based on Local Authority District or GP practices. HES data may be analysed at aggregate level with other data sources, especially resident or GP registered populations to create activity rates. NHS England have 30 analyst users who are part of the agreed 50 licenses (together with DH, no DH users have access to the HDIS system under the terms of this agreement) that are covered by the GIA arrangement.

Objectives:

NHS England supports across a wide spectrum of responsibilities to support Health and Social care within England access to HDIS is required to support this for the following areas; - commissioning - policy - finance - economic development - research and analysis The above all assist NHS England in its aim to create the culture and conditions for health and care services and staff to deliver the highest standard of care and ensure that valuable public resources are used effectively to get the best outcomes for individuals, communities and society for now and for future generations. Data will only ever be used for purposes relating to healthcare or the promotion of health in line with the requirements of the Health and Social Care Act 2012 as amended by the Care Act 2014. HDIS users are based across the organisation and their access is from the secure NHS England environment. They help NHS England to oversee the delivery of NHS funded services and the continuous improvements to the quality of treatment and care by using HES data to inform, target, strategies, monitor, benchmark, cross-check and plan services. An example is the £2.1 billion Sustainability and Transformation fund set up to stabilise NHS finances, in tandem with higher rates of efficiency growth, and to provide funding for transition to more effective models of care. Many of this fund’s uses impact on hospital care and require good evidence and understanding of hospital activity – at a local level but within a national context as provided by HES. Another example is the redesign of urgent and emergency care (UEC) services to cope with the increasing demand on A&E departments and emergency admissions. A specific part of that is the development of new indicators to monitor UEC effectiveness due in October 2016. Some of this analysis will be for internal management purposes and key outputs will be published in various forms (see examples below). NHS England access to record level data is necessary to devise appropriate aggregations eg of activity relating to diseases or groups of operations, to calculate statistics such as median length of stay, to break down total counts to understand their components and to analyse connected activity such as A&E attendance and emergency admission. Any record level data extracted from the system will not be processed outside of the analytics team. Only registered HDIS users who form the analytics team, will have access to record level data downloaded from the HDIS system. Following completion of the analysis the record level data will be securely destroyed.


Project 4 — DARS-NIC-370749-W1R8Z

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2017/09 — 2017/11.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Bespoke Extract : SUS PbR A&E
  • Bespoke Extract : SUS PbR APC Episodes
  • Bespoke Extract : SUS PbR APC Spells
  • Bespoke Extract : SUS PbR OP

Benefits:

An updated and improved formula has allowed more equitable funding of CCGs across England and thereby supported more equitable access by patients to NHS health care services. The benefits of equitable allocations are difficult to quantify, but the size of the budget being allocated (over £65bn) is sufficiently large that a small marginal improvement would have significant absolute benefits. A recent longitudinal study by Barr et al (www.bmj.com/content/348/bmj.g3231.reprint) has provided the clearest evidence so far of the impact of additional resources on health status, demonstrating a link between a reduction in deaths amenable to healthcare and increased investment. This demonstrates that an effective distribution of resources in line with need should, if followed by appropriate commissioning, be expected to deliver improvements in healthcare outcomes for individuals.

Outputs:

The outputs were predicted average need related expenditure per head for health care services for each age/gender group for each GP practice in England, and at CCG level for specialised services. The outputs were the coefficients from the regression model, and also these multiplied by the values of the explanatory variables for each patient, the products of which are then aggregated to give average need per head by age/gender group by GP practice and for specialised services by CCG. The coefficients from the regression models were published in NHS England’s technical guide to allocations. The predicted average need per head by age/gender group by GP practice were published in the technical guide. The average need per head was suppressed in the publication where they apply to small numbers in line with the HES analysis guide. These will be equivalent to the previous research by Nuffield Trust published in the Excel file C Need per head (General and Acute), worksheets GP practice Need Values and Nuffield Model Variables, at: http://www.england.nhs.uk/2014/03/27/allocations-tech-guide/ The values of the explanatory variables or record level data were not published. The data are requested for retention for five years to allow NHS England to respond to queries on the allocations, and re-model for future changes in CCG responsibilities arising with co-commissioning. The further analysis NHS England want to perform in 2017/18 is to investigate a query they have had from a CCG regarding their needs weighting from the model. This will involve looking at some of the inputs to the model from that geographical area and comparing them to other areas. This will be done through access to the secure connection to the data stored in the NHS Digital facility. NHS England is not permitted to transfer any of the data out of the NHS Digital facility, nor is it permitted to attempt to do so. The outputs will be qualitative descriptions of what have been found when comparing the CCG’s input data with other areas. This will allow NHS England to understand whether any mistakes were made in the calculation of the formula and therefore whether the formula may need to be refined to ensure that allocations are as fair as possible in relation to need; or whether there were some local data issues that skewed the output for that particular CCG; or whether in fact there is no issue at all. NHS England need to be able to confirm that resources have been allocated in accordance with the objectives of providing equal opportunity of access to healthcare for equal need, and addressing health inequalities. Without being able to re-look at the original data used for current allocations NHS England cannot be confident that allocations have been carried out in the most equitable and efficient manner possible, and cannot make changes to improve the process in future. In addition, in an extreme scenario, should NHS England find any significant mistakes in the outputs then certain CCGs could theoretically be eligible for compensation which would have a direct impact on patient care. The predicted need per head was used to calculate CCG target funding allocations, by combining with population sizes and other components of the target formula which were not calculated from this requested data set.

Processing:

The requested data and linkage will be used to create a record for each individual in England. The record will include for four years their admitted care, outpatient care, A&E attendances and critical care, or alternatively that they have received no hospital care. The record will also include diagnostic information from SUS PBR. This data set will be held solely by NHS Digital on their IT systems. Access to the data will be via secure virtual access using tokens and individual login details on NHS England computers. Data will be accessed by a limited number of authorised individuals from NHS England who are all substantive employees. Processing took the form of statistical modelling of individual patient record level data. The modelling had annual estimated expenditure for each patient as the dependent variable and the patient’s age, diagnoses, and characteristics of the local area where the patient resides as the explanatory variables. The characteristics of the local area where the patient resides are publicly available data from e.g. the 2011 Population Census. Other data was linked to the data set, but only organisational level data (eg: QOF) or reference data (eg: organisational name against an organization code). No additional record level data was linked to the dataset. The only data from this work taken away to NHS England’s premises was a) the coefficients from the regression modelling and diagnostic test results of the robustness of the modelling; b) the estimated need per head by age-gender group by GP practice; c) the estimated proportion of need per head by age-gender group by CCG by groups of specialised services (for changes in CCGs’ responsibilities); d) aggregate level descriptive data eg the number of people receiving treatment not registered with a GP. No record level data was taken away from the HSCIC Secure Data facility, and thus only aggregate or organisation level statistical information will be published. The results of the analysis performed on this data are published here: https://www.england.nhs.uk/2016/04/allocations-tech-guide-16-17/ The work has allowed the publication of 5 years of allocations to CCGs. All persons accessing the data are substantive employees of NHS England.

Objectives:

The efficient and equitable allocation of funding to support different services, geographies and patient groups is a fundamental underpinning to the operation of the health service. Without this, the opportunity for patients to access healthcare in line with need would be unequal, and the ability to address inequalities in health would be undermined. The approach to achieving the efficient and equitable allocation of resources has two key steps: first, understanding the current distribution of resources and estimating the relative target distribution; the second is that which would deliver the most efficient and equitable distribution of resources based on the relative need for healthcare services between geographical areas and patient groups. The data that is the subject of this application would be used to develop the target allocation shares for Clinical Commissioning Groups (CCGs) of the national budget for England. The target formula used for allocation of resources for CCGs was developed by the Nuffield Trust (see www.nuffieldtrust.org.uk/our-work/projects/person-based-resource-allocation-pbra) and is the most robust resource allocation methodology we have ever used. Its strength comes from building organisational allocations up from individual level estimates of need for health services, which can exploit interacting information about each patient’s age, gender, area of residence and hospital recorded diagnosis information. These individual level estimates can then be built up in to organisational level estimates; the estimates for individuals themselves are not reliable and are not used (nor published). The Nuffield work was updated for two reasons. First, the original modelling is based on information that is several years old (2007-08 to 2009-10) and we would want to update this to ensure it remains robust. Second the development of commissioning and a more place-based approach is driving a reconsideration of where the boundaries are between different commissioning streams. If the responsibilities of Clinical Commissioning Groups change, the relative distribution of resources that is most efficient will also change. In particular NHS England need to consider how the target allocation would need to change if significant elements of the directly commissioned specialised services became part of CCGs’ funding responsibilities. In summary, therefore, the objective is to estimate the relative need for healthcare services for each CCG’s population and for specialised services at CCG level, based upon modelling the use of healthcare services and diagnoses data. To confirm, the data will only be used for the development of a formula for target funding allocations for each Clinical Commissioning Group and for specialised services currently commissioned by NHS England and to then follow up on queries submitted following publication.


Project 5 — DARS-NIC-371011-F4X5F

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/09 — 2016/11.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Identifiable

Datasets:

  • Monthly Subscription Assuring Transformation

Benefits:

Understanding the differences in the data sets is important for giving confidence in the AT data - whilst the discrepancy is unexplained there will be lingering uncertainty that AT is able to accurately report on inpatient care for people with learning disabilities, and be used for monitoring delivery of the Transforming Care programme. Where under-reporting is identified, NHS England will be able to work with commissioners to improve their reporting - this will in turn enable AT to be used effectively to identify poor practice (particularly around discharging patients) and hence will drive up quality of care.

Outputs:

HSCIC will supply a summary report to NHS England, giving aggregate figures for patients included in one data set but not the other, and patients coded in HES under 'respite care'. HSCIC will also supply a pseudonymised, patient-level data set, to allow NHS England to carry out detailed analysis. It is anticipated that NHS England will want to identify any under-reporting in Assuring Transformation that is not accounted for by respite care admissions, so that it can work with the relevant commissioners to help them improve their reporting. NHS England will analyse the detailed data set and produce its own qualitative report in early 2016 - this is intended for NHS England management and operational managers, and for partners in the cross-system Transforming Care programme (Department of Health, Public Health England and CQC).

Processing:

Comparative analysis, linking provisional HES and AT will be undertaken within HSCIC. A consistent pseudonym will be applied to HES and AT data, and the sets will be linked via the pseudonymised patient ID. As well as a summary report, HSCIC will supply NHS England with a patient level, non-identifiable data set, which will be used by NHS England analysts to examine the differences between the two data sets. NHS England analysts will provide qualitative reports to NHS England management. In particular, analysts will use the linked data set to test the hypothesis that much of the activity reported in provisional HES but missing from AT is for patients admitted for short-term respite care. If this hypothesis is correct, it will give confidence that AT is accurately recording all patients being admitted for assessment and treatment. If it is not correct (respite care does not account for all or most of the difference between the two data sets) then it is evidence of under-reporting in AT – NHS England can then use this evidence to work with commissioners to improve reporting in AT. The data set will be held by NHS England in the secure environment already set up for Assuring Transformation data. It will be stored securely but separately from these identifiable data sets, and no attempt will be made to link the different data sets. The Assuring Transformation data set already received and stored by NHS England is fully identifiable, not pseudonymised. NHS England will not have access to the pseudonymisation algorithm used by HSC IC, so the two data sets (identifiable AT, pseudonymised HES-AT) cannot be linked as there is no common identifiable field. This application specifically asks for HSC IC to link pseudonymised HES with pseudonymised AT, and analyse this linked data set – once this is done there is no requirement for any further linkage to AT. The data will not be stored, processed or in any other way accessible by a third party organisation or across multiple locations within NHS England. No record-level data will be shared with any third party. As noted above, data will be stored on a secure network drive, to which only named analysts working in NHS England’s Learning Disability Programme have access. The central analytical support for the LD programme in NHS England consists of three people, one of whom does not have access to the secure drive where the identifiable data set is stored. Should NHS England carry out any analysis on the pseudonymised data set, it will be carried out by the same two analysts in the team, as there are no other analysts supporting the central NHS England LD programme. NHS England has no intention of attempting to link the pseudonymised and identifiable data sets and will carry out stand-alone analysis only of the pseudonymised data set.

Objectives:

Transforming Care Programme - NHS England has set out a clear programme of work with other national partners, outlined in ‘Transforming Care – Next Steps’, to improve services for people with learning disabilities and/or autism, and drive system-wide change. This will enable more people to live in the community, with the right support, ideally close to home. The programme is led jointly by NHS England, the Association of Adult Social Services (ADASS), the Care Quality Commission (CQC), Local Government Association (LGA), Health Education England (HEE) and the Department of Health (DH). A key objective of the Transforming Care programme is a reduction in the reliance on inpatient care – reducing the number of people being admitted to hospital and discharging current inpatients, with a net reduction in the number of people with LD and/or autism in hospital. The Assuring Transformation data is the principle data set used to monitor the number of inpatients. When compared to published Assuring Transformation (AT) data, published HES data shows significantly more admissions each month (an order of magnitude greater). By carrying out a comparative analysis of the two data sets we will be able to understand and explain why this difference occurs. If the analysis shows that some organisations are under-reporting in AT, NHS England and partners in the cross-system Transforming Care programme (Department of Health, Public Health England and the Care Quality Commission) will be able to work with commissioners to improve their reporting. The analysis will be at aggregate level and small numbers will be supressed in line with the HES analysis guide.


Project 6 — DARS-NIC-379704-S6H6R

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2016/04 (or before) — 2016/08.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Diagnostic Imaging Dataset

Benefits:

Objectives 1-3 provide a rigorous quality assurance of the data, ensuring data quality issues are fully understood and addressed and the types of analysis undertaken are appropriate to inform decision making. Objectives 4-5 will realize benefits to the health system as follows: Analysis of this data would inform how resources could be more efficiently distributed within the diagnostic part of a cancer pathway – there is evidence that providers and commissioners currently are limited in their ability to undertake capacity and demand planning and this linked data will assist. Where efficiencies were achieved, this would be expected to result in a decrease in the waiting times for this period and an increase in the cancer waiting time performance for the Urgent GP referral to first definitive treatment standard. A return of performance for this operational standard to 85% would mean 4,000 patients per year would receive more timely cancer treatment. These benefits are expected to be realised through 2016/17. The newly published cancer strategy makes reference to investment in diagnostics, and this analysis will inform this. The cancer strategy also makes a direct reference to the ineffective use of the Diagnostic Imaging Dataset see section on ‘cancer data and intelligence’ pg 72. This highlights the importance of making better use of linked datasets. See http://www.cancerresearchuk.org/about-us/cancer-taskforce To quote the report: “An inability to link data sets and make these available to providers, commissioners and researchers sustains the provision of sub-standard care.”

Outputs:

All outputs produced at each stage will be provided free of charge. For Objective One – 6- 8 weeks from receipt of linked data (mid-Nov to end Nov 2015) - Produce rates of diagnostic test per patient, periods from request to test, and test to report for relevant groups of diagnostic test to enable trend analysis at provider, CCG, and national level. - Provider and CCG level outputs would be produced. The level of breakdown of each of these would be based on combinations of: type of cancer pathway as defined by cancer waiting times operational standards; tumour types as detailed in the cancer waiting times official statistics publication; and type of diagnostic test (based on groupings of NICIP/ SNOMED codes for similar types of imaging, including those groups of tests currently reported in the DID official statistics publication) - The results would be non-identifiable and aggregated for different tumour sites to decrease the risk of disclosure of sensitive information due to small numbers. - The audience for this first objective, the output of which is first iteration findings, would be the internal steering group. - All outputs to be aggregate data with small numbers suppressed For Objective Two – 8-10 weeks from receipt of linked data (Dec 2015) - Second iteration of objective 1 outputs, addressing comments from internal steering group. - All outputs to be aggregate data with small numbers suppressed For Objective Three – 10- 12 weeks from receipt of linked data (Jan 2016) - Report based on assured outputs (from objective 1 and 2) shared with Cancer Waiting Times Taskforce. - All outputs to be aggregate data with small numbers suppressed For Objective Four – From 13 weeks from receipt of linked data onwards (Jan/Feb 2016 onwards) - Interpret findings to test the following hypotheses – more diagnostics are taking place per cancer pathway now compared with 2 years ago, there are delays in the 62 day pathway caused by access and period taken to report diagnostic tests. Staff involved in the processing and analysis will include Analytical Officer who is on an honorary contract from Cancer Research UK to NHS England. This is as per the application NHS England made to HSCIC to access the DID-HES linked data which was approved by DAAG. The arrangements made for the DID-CWT linkage are exactly as per the DID-HES application. - All outputs to be aggregate data with small numbers suppressed For Objective Five - Report specifying what benefits additional analysis would grant. - All outputs to be aggregate data with small numbers suppressed Notes on distribution of outputs Aggregate results may be published by NHS England as an official statistic, analysis may be published in journals. Once outputs fully assured, disseminate results, anticipated to be through CWT Taskforce. Initially outputs would be disseminated within NHS England central and regional teams. The CWT task force may wish to disseminate results to Providers, Commissioners and other NHS organisations. Any information would be aggregate data with small numbers suppressed Use findings from these results to inform investment in diagnostics as recommended in the cancer strategy “Achieving world-class cancer outcomes: a strategy for England 2015-2020”. All outputs produced will be freely provided. No charge for access to the results will be collected. No record level data will be published in any journal and only aggregate data will form part of the analysis published. Small numbers will be suppressed in line with HES analysis guide.

Processing:

The data would be stored by NHS England in their secure database and held in a secure set of folders. This database also hosts the pseudonymised CWT dataset currently held by NHS England. These folders are only accessible to the CWT team at NHS England. Both the linked data and the data already held by NHS England will be stored separately in password protected folders. NHS England will not link the two CWT datasets at any stage. Before any Objective - Process csv files such that are manageable for analysis in STATA - Run quality assurance scripts to sense check the data for volumes of cancer pathways and diagnostics (all diagnostics and pre-identified diagnostics which may be used for cancer diagnosis e.g. chest x-ray, chest CT, brain MRI) For Objective One - Apply first version of algorithm to identify diagnostics of most interest e.g. tests taking place subsequent to a two week wait urgent referral for suspected cancer, tests taking place in the diagnostic phase of a 62 day pathway, tests taking place in the 3 months before a decision to treat on a 62 day pathway and 31 day pathway. - Calculate rates of diagnostic test per patient, periods from request to test, and test to report for relevant groups of diagnostic test to enable trend analysis at provider, CCG, and national level. - Produce national level aggregated analyses. Sense check outputs. - Develop version 2 algorithm to account for issues arising from first run. Recreate all outputs. - Produce provider level aggregated analyses from first version algorithm, Sense check outputs – e.g. identify outliers and level of influence these have. - Produce CCG level aggregated analyses from first version algorithm. Sense check outputs as with provider level. For Objective Two - Present early version 2 findings to steering group for analysis. - Address feedback from steering group, produce further set of analyses covering trend analyses of rates of diagnostics on cancer pathways, times waited for diagnostics from request to test, and test to report issued . For Objective Three - Simplify results from Objective One with an easier user Interface. - Once outputs fully assured, disseminate results, anticipated to be through CWT Taskforce. For Objective Four - Control usage of results from Objective One with centrally controlled document and sign-off on usage of results to ensure end users don’t misuse the data. For Objective Five - Assess impact of results and questions raised during process of Objectives One to Four. - Annual update of results to investigate the changing nature of the data. No record level data will be shared with any third party, and the data will only be processed and stored at the address stated in Annex C.

Objectives:

The diagnostic period of a cancer pathway is currently largely unknown. Recent analysis of Cancer Waiting Times (CWT) has shown that the diagnostic period of the pathway is the main factor in causing delays in waiting times. The objective of linking the CWT dataset and the Diagnostic Imaging Dataset (DIDS) is to investigate this period and provide evidence to answer questions such as: Are the number of diagnostics tests per cancer patient increasing? Are tests taking longer due to an increase in activity or due to more complex diagnostics? Are the tests consistent with published clinical guidelines? What is the ration of test for diagnostic purposes compared to surveillance post treatment? Of diagnosed cancers, what proportion had diagnostic tests referred by a GP? Does the source of diagnostic tests matched to cancer waits affect the detection and conversion rates? Objective One - Analysis of the pseudonymised, non-sensitive record level data by NHS England CWT team, producing national level and provider level analysis which is aggregate data with small numbers suppressed. Objective Two - Present early findings of aggregate data with small numbers suppressed to steering group for analysis. Address feedback from steering group, produce further set of analyses covering trend analyses of rates of diagnostics on cancer pathways, times waited for diagnostics from request to test, and test to report issued . Objective Three - The data would be used to measure and compare the performance of organisations conducting cancer diagnostics, based on aggregate data with small numbers suppressed. Objective Four - Inform developments to diagnostic pathways by analysing the data and making aggregate data with small numbers suppressed available to Department of Health and Arm’s Length Bodies with a role in provision and commissioning of cancer services Objective Five - Monitor and develop outputs over three year period, all outputs to be aggregate data with small numbers suppressed


Project 7 — DARS-NIC-389823-P1P6B

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Identifiable

Datasets:

  • Monthly Subscription Assuring Transformation

Benefits:

The data gives insight at organisational (provider/commissioner) level, the benefits are that operational managers will have an evidence base through which to drive improvements in services and patient experience. As soon as this evidence base is available actions can be taken to begin these improvements. Without this evidence base targeted work to improve services and patient experience cannot take place. The data enables performance management of trajectories to reduce inpatient numbers. The information will be used day-to-day, to reduce the reliance on inpatient care and to manage the safe discharge of current inpatients to the community. Benefits will flow immediately as NHS England national and regional managers are able to take immediate action when necessary. Commissioners are developing trajectories for inpatient numbers to March 2017 and these reports will help manage delivery of these trajectories. As well as an in-year delivery target commissioners are developing three-year (2016/17 - 2018/19) transformation plans in line with the published national transformation plan Building the Right Support. Operational management data is important for helping manage delivery of these plans, to ensure any deviation from trajectory is identified early and can be acted on. Detailed information is required by TCPs to plan and commission effectively. The additional request to share detailed data with TCPs will allow TCPs to effectively plan and commission appropriate services, and to reduce the reliance on inpatient care. It will enable patients to be moved from inappropriate inpatient facilities to community care which is closer to home and more appropriate to each individual's needs, improving their quality of life. More effective commissioning of any required inpatient services will save the NHS money, reducing the need for spot-purchasing of care and lengthy block contracts with providers. The data already received by NHS England has allowed them to carry out detailed analysis to support delivery of the Transforming Care programme, in particular the objective of reducing the reliance on inpatient care. NHS England has been able to monitor patients at commissioner level, and identify blockages which are preventing patients being discharged. NHS England have been able to carry out specific pieces of analysis, such as detailed work on the u-18 age group – this has contributed to the reduction in the number of u-18 patients. Changes to the contents of the data set in 2015 included the ‘CCG of origin’ field which has enabled NHS England to map patients whose care is specialised-commissioned by NHS England (over half the inpatient total) to be mapped to their home CCG. This is vital to the process of planning services – without this information local Transforming Care Partnerships (TCPs) do not understand the total number of inpatients that they need to be planning services for. Using this information TCPs have been able to develop 3-year transformation plans. Amending the agreement to allow NHS England to share unsuppressed data with TCPs will allow TCPs to properly and accurately complete these plans, giving them a full understanding of their inpatient numbers and the services these patients are using.

Outputs:

(a) Outputs are aggregated commissioner-level analysis, used for internal management purposes. The monthly data and analysis allow local operational managers to ensure commissioners are delivering national performance indicators, and to intervene when they are not. (b) The operational MI outputs will only be available to operational managers within NHS England. No other organisations will have access to this data. This information will not be used or shared outside NHS England. [Note that this is a weekly output - section 9 of this template does not include 'weekly' as an option in the Frequency table] Analysis will not be published in journals or be used in relation to clinical trials, nor used for direct marketing. Performance dashboards and other analysis will be used internally and with commissioners once the Management Information has been published by NHS Digital. These will be in aggregated form only. NHS Digitals’ guidance on suppression of small numbers will be followed. (c) Aggregate, unsuppressed TCP-level reports showing the numbers of patients at each provider site, the number of patients at each level of ward security and the numbers of patients in hospital split by length-of-stay groups. This will be used to plan services and identify services which will be decommissioned as services are transformed and bed numbers are reduced.

Processing:

Data will not be stored, processed or in any other way accessible by a third party. Data is stored in the secure storage that was set up when NHS England managed this data collection themselves. (a) Monthly data will be analysed to produce aggregate level reports, to allow operational managers to work with challenged organisations to improve delivery and performance against key national indicators. Patient level data will be accessible only to those named individuals that have been given access to the secure data storage, and will only be accessed in the safe haven environment set up for this purpose. (b) NHS Digital supplies operational management information reports to NHS England on a weekly basis. NHS England does not carry out any processing, but ensures the operational MI reports are provided to the named operational managers, who use the reports generated as produced by NHS Digital to manage CCG performance. (c) NHS England will supply data to TCPs to allow them to plan and deliver transformational change to services for people with learning disabilities and/or autism. To allow them to effectively plan and deliver these services they need access to unsuppressed data showing the number of patients originating from the TCP at each hospital site. The data supplied to each TCP will only include information for patients originating from that TCP, and will not include NHS number, date of birth or home postcode.

Objectives:

Use monthly and weekly Assuring Transformation (AT) data to derive performance and quality indicators for Learning Disability services, in order to drive improvements in the services and to identify where good/poor practice is taking place. Analysis will be carried out by NHS England analysts. The analysts will use the fully identifiable data set to produce useful analysis for operational managers and LD Programme staff. The analysis they produce will not include identifiable information. (b) Use timely operational management information, to allow NHS England to monitor and manage delivery of Transforming Care improvements to care for inpatients with a learning disability, behaviour which challenges or an autism spectrum disorder. Unsuppressed small numbers are included in this data set to ensure that commissioners are carrying out their duties in relation to discharging people with a learning disability who are placed inappropriately in hospital. Each CCG is likely to have small numbers in each category and it is important to be able to track if they have reduced their number from e.g. three to two, which unsuppressed numbers do not allow. The operational management report cannot be used for its intended purpose of monitoring commissioner CCG-level activity unless it is populated with unsuppressed data. NHS Digital will be supplying operational management information reports to NHS England on a frequent weekly basis. NHS England will not be doing any processing, but will be using the reports as produced by NHS Digital to manage CCG performance. The new data fields in the AT data set give further insight into delivery of improvements, specifically the Care & Treatment Review process which is used to identify patients suitable for discharge and the barriers currently preventing discharge. Including the new AT fields in the extracts and reports sent to NHS England will facilitate targeted work to discharge patients who have been identified as ready to be discharged from inpatient care. (c) Use information on the location of services and the number of patients using these services to effectively plan and deliver transformational change, reducing the reliance on inpatient care for people with learning disability and/or autism. Planning and delivery will be carried out by Transforming Care Partnerships (TCPs) - CCGs, specialised commissioners and local authorities working together to ensure appropriate and effective services are put in place for this vulnerable group of people. TCPs are responsible for the delivery of the transformation of services, reducing the reliance on inpatient care and using local services to help people live in the community. This will ensure people with learning disability and/or autism receive effective and appropriate care close to their homes. To be able to plan and deliver these new services, TCPs need to have reliable detailed data about the people currently in hospital who originate from their CCGs / local authorities. This will allow them to put appropriate services in place for when patients leave hospital, and to ensure the appropriate provider capacity is available for those people that do still require hospital care. No TCP would see another TCP's unsuppressed data.


Project 8 — HDIS_NHS England

Opt outs honoured: N

Sensitive: Non Sensitive

When: 2016/04 (or before) — 2016/08.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Access to HES Data Interrogation system

Objectives:

The HES (Hospital Episode Statistics) Data Interrogation System (HDIS) allows users to securely access HES, interrogate the data, perform aggregations, statistical analysis, and produce a range of different outputs. Access to HDIS is only provided to organisations who work within the public sector with a specific interest in public health. There is a strict information governance applications process in place to protect and control how the data is managed.


Project 9 — NIC-92346-T4Z0F

Opt outs honoured: N

Sensitive: Sensitive

When: 2017/03 — 2017/11.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Community
  • Local Provider Data - Demand for Service
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Experience Quality and Outcomes
  • Local Provider Data - Public Health & Screening services
  • Local Provider Data - Mental Health
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Population Data
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Improving Access to Psychological Therapies Data Set

Benefits:

General benefits applicable to all requested data sets 1. Analysis and reporting will help ensure that NHS England meets its statutory duties (as outlined above) to commission effective and efficient services in line with NHS England’s Five Year Forward View. 2. tNR to act as a proving ground for the Commissioner Assignment Methodology (CAM) and to convert the CAM methodology to a system algorithm. Benefits expected from commencement of provider implementation of the CAM include: a. Equitable distribution of resources b. More accurate identification of commissioners c. Improved performance data from providers for monitoring contract performance d. Consistency of approach makes national analyses easier and more accurate e. Efficient local processes for providers 3. Support analysis of development and monitoring outcomes for new models of care. 4. Developing improved methodology for calculation of commissioner budget allocations. 5. Provides robust findings on which complex changes to care are most effective, enabling large transformation programmes to improve the effectiveness of their interventions. For example, SUS data has been used extensively (monitoring trends in acuity of cases, investigating the characteristics of attenders, understanding the relationship between attendances and admissions, etc.) in the development of the recent A&E Plan. 6. Enable NHS England to make better use of existing data, without compromising data security and by using data that is anonymised in line with the ICO Anonymisation Code of Practice to mitigate the risk of compromising patient privacy. 7. Reduced resources whilst delivering robust assessment of national programmes. 8. 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. 9. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 10. Enables monitoring of: a. CCG outcome indicators. b. Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. 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. 11. There have already been significant benefits realised from the use of activity data derived from SUS. NHS England now share a common understanding of activity levels across the system, which has enabled better local and regional performance management, as well as the development of national policies e.g. new demand and capacity plans for elective care. Better activity data has also enabled a more robust national planning process, and so improved the allocation of funds across the system. Additional benefits applicable to specific data sets Data set specific benefits, in addition to those listed above, include the following. Mental Health (MHMDS, MHLDDS, MHSDS) data will also support: 12. Increased access to Mental Health and IAPT data are widespread given the relative lack of evidence (as compared to measuring physical health), despite £34 billion being spent each year on mental health (source: MH FYFV). The data will allow us to better monitor (for example by looking at local variation or the links with physical health) progress against some of the priority actions identified in the MH FYFV, such as waiting time standards for early intervention in psychosis. Data access will facilitate the development of new standards e.g. on eating disorders or out of area placements (where patient-level data will allow us to monitor the impact of various thresholds). To monitor progress against policy programmes NHS England need high quality data, and access to Mental Health and IAPT will allow the Data Controller (NHS England) to assist in driving up quality, and cease the aggregate data collections which are currently in place (so reducing burden on providers and administrative costs). 111 data will also support: 13. A reduction in unnecessary use of A&E. 14. An increase in referrals to alternatives to A&E. 15. Improvement to performance of A&E waiting times

Outputs:

General outputs applicable to all requested data sets All datasets will be used to: 1. Allow NHS England to meet its ongoing statutory duties under the NHS Act 2006 and the Health and Social Care Act 2012 s13N, s23. Specifically – ‘to exercise its functions ensuring that health services are provided in an integrated way where this would improve quality and outcome of services and reduce inequalities’. 2. Realise data quality improvements initiatives including reports to ensure that NHS England data processing has been carried out correctly (e.g. expected volume of specialised activity service line codes derived). 3. Provide an aggregate activity and finance report which will be used to populate an NHS England integrated activity and finance report for the monthly NHS England Executive Group Meeting. This has now been introduced (the benefits from this, and related SUS analyses included in the following section). 4. Analyse the impact of changes to NHS commissioning business rules (e.g. tariff changes, commissioner assignment, specialised services identification rules, HRG grouping). 5. Facilitate proactive management of NHS England directly commissioned services using pseudonymised or aggregate data only. (This is dependent on the analysis requirement as to whether the output used is pseudonymised or aggregate data.) 6. Enhance statistical analysis to facilitate proactive management of transformation programmes by local health systems on behalf of NHS England. 7. Monitor and analyse outpatient and community services; alternatives to inpatient care. 8. Monitor and analyse of new patient care pathways introduced to support the transformation of services for people with learning disability and/or autism. Access to data will specifically allow: - Analysis of inpatient services and activity for people with learning disability and/or autism - Analysis of outpatient and community services and activity for people with learning disability and/or autism - Analysis of patient pathways as patients move between services 9. Analyse factors that result in high service usage. 10. Analyse the usefulness of diagnosis coding. Analysis will firstly focus on an understanding of the completeness and quality of coding in the dataset to provide a basis for any further analysis. NHS England would like to understand the completeness and validity of this data item, as well as identifying any geographical trends or particular providers which show problems with coding completeness. Access to the data would enable further discussion of coding practices in providers for casemix complexity. The intelligence can be shared through commissioning routes to help drive up coding completeness and accuracy to make any subsequent analysis more meaningful. 11. Analyse the spread of diagnoses geographically and demographically, to identify any trends as well as diagnoses recorded over time (given a robust starting point for coding accuracy and completeness). Admissions and readmissions and activity could also be analysed by diagnosis to better understand these trends and potential differences in provider models to inform commissioning decisions and service improvement. 12. Provide intelligence to commissioners to support the reduction of unnecessary restraint and potentially abusive restraint. An analysis of restraint to identify any trends or outliers across providers, CCGs and sub-regions. The analysis will also include the frequency of restraint per patient and by ward type. This will highlight any areas for concern in the use of restraint to inform further discussions with commissioners. As the restraint type is added to the MHSDS in v2.0 this will provide further insight and areas for focus in discussions with commissioners. The aim of this is to provide intelligence to commissioners to support the reduction of unnecessary restraint and potentially abusive restraint. 13. Achieve the service improvements required, in association with the findings from the report “The commissioning of specialised services in the NHS” by the National Audit Office (NAO), whereby the findings suggested that NHS England does not have sufficient information to drive service improvement in specialised commissioning. 14. Undertake health economic modelling using: a. Analysis on provider performance against 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. 15. Provide commissioning cycle support for grouping and re-costing previous activity. 16. Undertake commissioner reporting, including: 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. 17. Produce aggregate reports for CCG Business Intelligence. 18. Produce project / programme level dashboards. 19. Monitor acute / community / mental health quality matrix. 20. Facilitate clinical coding reviews / audits. 21. Undertake budget reporting down to individual GP Practice level. 22. Produce GP Practice level dashboard reports, including high flyers. Additional outputs applicable to specific data sets Outputs applicable to specific data sets include the following. SUS will also support: 23. Gap and reconciliation analyses between monthly activity returns versus SUS/CDS data. 24. Gap and reconciliation analyses between aggregate contract monitoring reports submitted to DSCROs versus SUS/CDS. Mental Health (MHMDS, MHLDDS, MHSDS) data will also support: 25. A Mental Health Five Year Forward View (5YFV) dashboard; delivered in response to the recommendation in the 5YFV. NHS England recently published a first version of this dashboard, which will allow us to hold national and local bodies to account for implementing the 5YFV strategy. The dashboard is structured around the core elements of the MH programme as set out in the 5YFV implementation plan, and include perinatal mental health, children and young people’s mental health and elements across the common, crisis and secure adult mental health pathway including health and justice and suicide prevention. NHS England require improved Mental Health/IAPT data to further develop some of the indicators in the dashboard. 26. To use the Mental Health data to support contract payment and clinical case management (and develop a reliance in this data flow akin to acute services and their use of SUS data). 27. Regular monitoring reports of commissioners (inpatient services) to meet NHS England’s statutory duties and to demonstrate the delivery of NHS England’s Learning Disability Programme by cross-referencing relevant activity with Assuring Transformation data, due to end in 2018 28. To support ongoing updates to the Mental Health Quality Dashboard using quality measures derived from the MHMDS and MHLDDS. (The current dashboard is under review to focus the measures further on quality and utilising the dataset will enable a wider availability of measures as well as robust data. The dashboard can be used by QSG, commissioners and providers for benchmarking and identifying areas for service improvement as well as to inform commissioning decisions.) 29. To support the development of Clinical Services Quality Measures (CSQMs) that provide an at-a-glance indication of how well services are performing. They have been/will be developed as composite measures for Psychosis and Dementia specifically as a series of metrics that, for example, will allow for comparisons between services such as units within hospitals; providing better information for patients clinicians and citizens. Supressed numbers currently available in the published reports do not allow annual aggregation to be input into the composites. The measures will be developed according to statistical principles and will be assured by clinical and technical experts. (NHS England is involving patients, the public, service providers and clinicians in the development of these measures with aggregate – service level information to be available via NHS Choices and My NHS.) 111 data will also support: 30. A single national system, white-labelled and provided locally to CCGs by each CSU through their local BI portal, from April 2017 31. Reporting and analysis to support the proactive assurance of CCG-commissioned 111 services – including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities, from April 2017 32. Data quality analysis and data quality management, to ensure data processing has been carried out effectively, from April 2017 The target commencement date for the above outputs is December 2016 for existing data sets and March 2017 for the 111 data, with the aim to monitor changes on a monthly basis going forward.

Processing:

Data will only be shared with or processed by the parties listed in this application and will only be used for the purposes stipulated. Any further reports sent beyond the data controller and processors as stipulated in this agreement will contain aggregate data only, and will be subject to the disclosure controls of the relevant datasets. As part of the monitoring and evaluating of the transformation programmes, it will be necessary for the processed data to be enhanced by linking in publicly available contextual information on aggregate level. Examples of publicly available data include GP patient survey result aggregated to GP practice level (source: https://gp-patient.co.uk/surveys-and-reports), measures of deprivation aggregated at LSOA level* (source: https://data.gov.uk/dataset/english-indices-of-deprivation-2015-lsoa-level) and disease prevalence, again geographically aggregated (source: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases). AGEM CSU (in capacity of tNR host) Activities: Data will flow to AGEM DSCRO for de-identification in line with the ICO’s anonymisation Code of Practice. The pseudonymised dataset will then flow to other data processors, as listed below, to undertake processing activities on behalf of NHS England for a specific project(s) under Service Level Agreements. • Data linkage between the data sets being requested in this application will be undertaken on pseudonymised record level data (anonymised in accordance with the ICO Anonymisation Code of Practice) held within the tNR by NHS England data analysts operating under strictly controlled conditions and any inadvertent or malicious re-identification of data subjects will be recorded and reported in line with the NHS England’s incident (disciplinary) management process and appropriate action taken. A national feed of identifiable commissioning datasets (SUS, MHMDS, MHLLDS, MHSDS and IAPT) will be transferred from NHS Digital to Data Services for Commissioners Regional Office (DSCRO) AGEM who will complete data quality checks, pseudonymisation and validation of the data. • The DSCRO will apply the same pseudonymisation key to all NHS England required datasets in order to enable linkage by the AGEM CSU Data Processor (within the tNR). • DSCRO AGEM, in addition, also send a copy of identifiable SUS data to DSCRO North England. DSCRO North England collate all 111 data from all other DSCROs into a central processing area, link the 111 data with SUS data and transfer the data to DSCRO AGEM. • DSCRO AGEM securely transfer the following pseudonymised data (anonymised in accordance with the DSfC Anonymisation Requirements for Data used for Commissioning Purposes and in line with the ICO Anonymisation Code of Practice) to Arden and GEM CSU who act as NHS England’s main data processor: - SUS - Mental Health (MHMDS, MHLDDS, MHSDS) - IAPT - Linked SUS and 111 The data will be stored on a repository server within Arden and GEM CSU, known as the temporary national repository (tNR). • The data will be processed in the tNR on behalf of NHS England (as recipient data controller) to meet the reporting requirements, by adding value to the data (e.g. adding a tariff and grouper) to support integrated patient care analysis. • Under strict access controls, NHS England’s analysts (including those based within CSUs) will use remote access arrangements to query the pseudonymised record level data which is held within the tNR in order for them to analyse the data. The data can be accessed remotely from multiple locations in England using secure VPN or the N3 network, depending on where NHS Analysts are based. Access is secured via two personal user IDs and passwords; one to login in the terminal services server giving access to the Arden GEM network domain and then a further login into the SQL Server environment where the user is given read-only access to the data. Further information surrounding tNR access management can be found at the end of this section. North England CSU (in capacity of urgent care dashboard host) In order to provide a national view of all UEC activity on behalf of NHS England to all CCGs, in addition to the transfer of linked SUS and 111 data from DSCRO North England to DSCRO AGEM, DSCRO North England also transfer the linked SUS and 111 data to North England Commissioning Support Unit (NECS) for further processing and in order to upload the data to the dashboard tool. The data flow sequence and arrangements are specified below: Activities: • North England DSCRO consolidate all 111 data collected by the other DSCROs into a central processing area. • AGEM DSCRO will supply a relevant extract of NHS England’s SUS data to North England DSCRO. • North England DSCRO link the 111 and SUS data to create a purpose-specific linked data set and flow the linked data to AGEM for upload to the tNR in pseudonymised form. • North England DSCRO also submit a pseudonymised extract to NHS England’s nominated CSU data processor – North East Commissioning Support (NECS). • NECS will further process the pseudonymised patient level data so that each CCG in the country is able to receive the 111 data relating to their patients only (as per local DSAs) and upload to the dashboard. • CCGs will also have the ability to see aggregate reports from the dashboard tool for the whole of England and their STP footprint which will enable them to benchmark their service providers and validate and analyse this across wider health economies in line with the statutory duties under the Health and Social Care Act 2012. Please note that the individual (209) CCG DSAs will be updated and approved by IGARD to capture the use of NECS for this processing, prior to NECS enabling CCG access to pseudonymised, record level SUS and 111 data. (NECS will work upon instruction from NHSE as Data Controller.) The Health Foundation The Health Foundation has partnered with NHS England to deliver the Improvement Analytics Unit (IAU), which exists to support all NHS England’s major transformation programmes. The IAU will utilise data to help build a body of knowledge about which interventions and major new initiatives in the English NHS are successfully improving patient care and share that learning more widely. The unit supports delivery of NHS England’s commitment in the Five Year Forward View to evaluating the impact of major national programmes (such as the new care models). The IAU will expand NHS operational research and statistical methods to promote more rigorous ways of answering high impact questions in health services redesign. Activities: The Health Foundation (THF) will only be provided with access to or given extracts of the specific commissioning data they require in order to undertake their activities set out within the SLA or data processing agreement. Processing activities would only take place on patient-level data where it has been anonymised in line with the ICO’s anonymisation code of practice and would include: • Data quality checks • Data validation • Generation of ad-hoc analysis and reports to support specific projects Datasets: The Health Foundation will receive the following data flows: • SUS • Mental Health (MHSDS, MHLDDS, MHMDS) • IAPT tNR Access Management NHS England will limit the amount of pseudonymised data which is made available to analysts. Where access to the tNR is required by internal users (based within NHSE and CSUs), a robust user registration process is in place, which involves: • Sign-off by the analyst’s lead manager to ensure that all users have a suitable level of knowledge about SQL Server and tNR processed data. • Submission of an access request application, outlining the purposes for which they require access. • The IAO of the tNR assessing the request to ensure that it is in line with the agreed purposes included in the data sharing agreement. Once access to data on the tNR is granted, according to the role and user requirements, access is secured by using 2 factor authentication, via VPN and on the N3 network. As recipient data controller, NHS England are responsible for and will ensure that the use of the data is in line with the NHS Digital data sharing framework contract and data sharing agreement and will take all steps necessary to minimise the risk of inadvertent or malicious re-identification. NHS England believe that the wider benefits of using the data to meet its statutory duties to ensure that patients receive the most appropriate care outweigh the extremely low risk of re-identification from the processing activities required. *a LSOA is a small geographical area typically covering about 1500 people

Objectives:

Generic objectives applicable to all requested data sets The requested datasets are required to ensure that NHS England can meet its statutory duties (as per NHS Act 2006 and the Health and Social Care Act 2012 s13N,s23) and to meet the requirements of the Five Year Forward View. The objective for processing can be summarized as the provision of an ad-hoc and routine analysis and reporting service to support the work of NHS England (NHSE) in the following responsibility areas: 1. Proactive management of commissioned services – including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities 2. Analysis and reporting to support QIPP (Quality, Innovation, Productivity and Prevention) programme activities 3. Data quality analysis and data quality management, to ensure data processing has been carried out effectively 4. To engage the Health Foundation to provide their analytical expertise to the Health Data Lab project 5. There is a requirement to link all datasets available on the tNR in order to fully understand patient pathways. This enables better planning of patients care to realise improvements and efficiencies. This will be possible through the creation of a consistent pseudonym applicable to all datasets. In summary, to better understand the relationship between physical and mental health, NHS England intend to link SUS, Mental Health (MHMDS, MHLDDS, MHSDS), IAPT and 111 record level data (anonymised in accordance with the ICO Anonymisation Code of Practice) for commissioning purposes to ensure commissioners can understand full patient pathways for their patients and plan their care. This is an area where the evidence is currently relatively weak, for example NHS England cannot currently answer questions such as whether patients with MH issues are more likely to be admitted or readmitted to hospital, or whether they have longer stays, and therefore linking data is an important requirement. Objectives applicable to specific data sets Mental Health (MHSDS, MHLDDS, MHMDS): Despite previous initiatives such as the 2011 mental health strategy, challenges with system-wide implementation coupled with an increase in people using mental health services has led to inadequate provision and worsening outcomes in recent years, including a rise in the number of people taking their own lives. NHS England and the Department of Health published Future in Mind in 2015, which articulated a clear consensus about the way in which NHS England can make it easier for children and young people to access high quality mental health care when they need it. The 2016 Five Year Forward View for Mental Health report from the Mental Health Taskforce builds on this strategy and sets out the start of a ten-year journey for the transformation which clearly states the role that NHS England has to play. The Mental Health data is crucial in monitoring progress against the Five Year Forward View. In particular, it will help: • Understand current patient pathways, what care is available now and what level of referrals to mental health services are anticipated to ensure 70,000 additional children and young people each year will receive evidence-based treatment. • Ensure that there will be the right number of CAMHS T4 beds in the right place reducing the number of inappropriate out of area placements. • Support at least 30,000 additional women each year to access evidence-based specialist perinatal mental health treatment. • Ensure that appropriate services are being commissioned to reduce the premature mortality of people living with severe mental illness (SMI); and 280,000 more people having their physical health needs met by increasing early detection and expanding access to evidence-based physical care assessment and intervention each year. • Ensure people with SMI can access evidence based Individual Placements and Support (IPS) • Ensuring that at least 60% of people with first episode psychosis starting treatment with a NICE-recommended package of care with a specialist early intervention in psychosis (EIP) service within two weeks of referral. • Support a comprehensive programme of work to increase access to high quality care that prevents avoidable admissions and supports recovery for people who have severe mental health problems and significant risk or safety issues in the least restrictive setting as close to home as possible. • Improve the quality of services commissioned, the case-mix of patients in treatment, population needs, the differences in success of treatment and care at practice, CCG, provider level and other geographies (e.g. regions) as well as the impact on other parts of the healthcare system, e.g. A&E. • Improve outcomes and tackle inequalities of people with MH problems. • Provide insight into suicide by looking at those with prior mental health problems, the severity and length of the problems and how many of those committing suicide also had wider physical health problems to help reduce the number of people taking their own by lives. • Enable the robust quality and performance planning and monitoring at a local and national level. • Make availability of home treatment visible in every part of England as an alternative to hospital • Check provision of all-age mental health liaison services to meet the national commitment that at least 50% will meet the service standard MHSDS data has also been expanded to include extensive information on people with learning disability and/or autism. The annual learning disability provider census, which ran from 2013-15 has been stood down, and all relevant content is now included within MHSDS. In addition, the content of the commissioner-based Assuring Transformation (AT) data collection has been included within MHSDS, with a goal to stand down AT when MHSDS data quality and completeness reach acceptable levels. Both the census and AT cover only inpatient care. There is currently no other data set which gives details of specialist community and outpatient services used by people with learning disability and/or autism. NHS England therefore needs to be able to monitor the quality and completeness of Mental Health data, so that the data can become the single, definitive source of information about people with learning disability and/or autism using NHS-funded services. As there is a requirement for further segmentation beyond the existing Data Quality reporting by NHS Digital, patient-level data is required. This is also true for other elements of Mental Health data (e.g. early intervention in psychosis) where NHS England have set-up aggregate data collections from providers until the quality of MHSDS can be improved. This increases burden and causes confusion. Detailed patient-level data is also required to compare Assuring Transformation and MHSDS inpatient data. This is necessary to identify under- and over-reporting in MHSDS (compared to AT) and to identify where patient records are inconsistent across the two data sets. Assuring Transformation is currently being used to monitor inpatient trajectories as part of the three-year national transformation plan ‘Building the right support’. If the monitoring data set switches to MHSDS before the end of this three-year period, NHS England needs to have absolute confidence that the two data sets are comparable and compatible. IAPT: The Improving Access to Psychological Therapies (IAPT) programme began in 2008 and has transformed treatment of adult anxiety disorders and depression in England. Over 900,000 people now access IAPT services each year, and the Five Year Forward View for Mental Health committed to expanding services further alongside improving quality. IAPT services provide evidence based treatments for people with anxiety and depression (implementing NICE guidelines). The use of IAPT data will support the following priorities for service development: • Expanding services so that at least 1.5m adults access care each year by 2020/21. This means that IAPT services nationally will move from seeing around 15% of all people with anxiety and depression each year to 25%, and all areas will have more IAPT services. • Focusing on people with long term conditions. Two thirds of people with a common mental health problem also have a long term physical health problem, greatly increasing the cost of their care by an average of 45% more than those without a mental health problem. By integrating IAPT services with physical health services the NHS can provide better support to this group of people and achieve better outcomes. • Supporting people to find or stay in work. Good work contributes to good mental health, and IAPT services can better contribute to improved employment outcomes. • Improving quality and people’s experience of services. Improving the numbers of people who recover, reducing geographic variation between services, and reducing inequalities in access and outcomes for particular population groups are all important aspects of the development of IAPT services. In addition, there is a strong policy need to understand the linkage between physical and mental health. Physical and mental health are closely linked – people with severe and prolonged mental illness are at risk of dying on average 15 to 20 years earlier than other people – one of the greatest health inequalities in England. Two thirds of these deaths are from avoidable physical illnesses, including heart disease and cancer, many caused by smoking. In addition, people with long term physical illnesses suffer more complications if they also develop mental health problems. To better understand the relationship between physical and mental health, NHS England intend to link SUS, Mental Health data and IAPT record level data that has been anonymised in accordance with the ICO Anonymisation Code of Practice using a consistent pseudonym which has been derived for commissioning purposes. This is an area where the evidence is currently relatively weak. Linking SUS, Mental Health and IAPT data will ensure commissioners can understand full patient pathways for their patients and plan their care, for example NHS England cannot currently answer questions such as whether patients with MH issues are at a higher risk of particular outcomes (e.g. admissions, readmissions, increased lengths of stay).Therefore linking data is an important requirement. 111 Data: The 111 data is required to ensure that NHS England can meet its statutory duties (as per NHS Act 2006 and the Health and Social Care Act 2012 s13N,s23) and to meet the requirements of the Five Year Forward View. It is essential that a national view of services is available to NHS England’s analysts. NHS England has a duty to ensure health services are provided in an integrated way. When exercising its functions, NHS England must do so with a view to securing that health services are provided in an integrated way where it considers that doing so would: (a) Improve the quality of services, including outcomes; (b) Reduce inequalities in access; (c) Reduce inequalities in outcomes. 44 lead CCGs already have a contract in place for 111 services and there are currently different models for how 111 services are commissioned and integrated within a locality. By collecting 111 data centrally at a national level, local best practice can be identified through benchmarking and provide the evidence to better understand the most effective model for integration of the various services associated with urgent and emergency care. In order to do this, NHS England requires CCGs to continue to collect data from their local services and provide specific metrics for Urgent & Emergency Care (UEC) so that this is also available in the national UEC Dashboard that North of England Commissioning Support Unit will collate for NHS England nationally. These metrics are in pseudonymised, record level form (data anonymised in accordance with the ICO Code of Practice). The national UEC Dashboard will enable both CCGs and NHS England to have a consistent way of reviewing UEC services, which will be captured in all CCG DSAs (in addition to this NHS England agreement). It will also provide a consistent method for pathway analysis, so that CCGs can compare and contrast their performance with other UEC models across the country. Linkage through to their own local reporting will further allow them to better understand their local pathways. Specific purposes for this data include: 1. Proactive assurance of CCG-commissioned 111 services – including contract management, performance management, needs and inequalities analysis, benchmarking, service review and development, planning, budgets and allocations and general commissioning assurance activities 2. Data quality analysis and data quality management, to ensure data processing has been carried out effectively 3. Better understanding of the effectiveness of changes to the operating model for urgent and emergency care (UEC), such as increasing the level of clinical input within 111 services as triage and sign-posting of patients that contact the service; to do this, NHS England will need to be able to understand the pathways that patients follow post contact with the 111 service in order to provide an evidence base for changes to these services. 4. Identification of quality differences nationally between different providers and opportunities to improve the efficiency of 111 services. The proposed approach is the provision of a single national system, white-labelled and provided locally to CCGs. The RAIDR-111 dashboard is an innovative BI tool specifically developed by NECS to support the UEC system. RAIDR-111 will deliver a single yet comprehensive view of the Integrated Urgent Care system nationally, meeting the needs of many differing audiences – NHSE, STPs, A&E Delivery Boards, and CCGs. The dashboard needs to combine 111 call outcome data with the linked secondary care SUS pseudonymised (anonymised in accordance with the ICO Code of Practice) record level data, showing A&E attendance and treatment received. The dashboard provides a single version of the truth accessible and drillable at national, regional, STP, and CCG level – all able to be aggregated up and down, at the fingertips of the users, as per the CCG’s DSA. North of England DSCRO will link the local 111 data with a number of fields from national A&E SUS data in order to generate the dataset required to populate the urgent care dashboard. This linked 111/SUS A&E data set will be shared with Arden and GEM DSCRO in order to have the consistent pseudonym applied and subsequent upload to the tNR. This will enable the urgent care dashboard to be populated, which will allow NHS England to understand and benchmark urgent care patient flows and service provision. Further linkage with other tNR data sets is needed in order to fully understand the activities, pathways and outcomes of patients that enter the system via the 111 service. These data sets will include wider SUS data (APC, OP, A&E), IAPT and the mental health data sets (MHMDS, MHLDDS, MHSDS).