NHS Digital Data Release Register - reformatted

NHS Herts Valley Ccg projects

Project 1

78 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 NHS Herts Valley Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Herts Valley Ccg may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

Project 1 — NIC-55752-D6X5Y

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, N

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

Children and Young People's Health Services Data Set
Improving Access to Psychological Therapies Data Set
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 - Population Data
Local Provider Data - Primary Care
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
Local Provider Data - Mental Health
Local Provider Data - Other not elsewhere classified
Maternity Services Dataset
SUS for Commissioners
Public Health and Screening Services-Local Provider Flows
Primary Care Services-Local Provider Flows
Population Data-Local Provider Flows
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Mental Health-Local Provider Flows
Maternity Services Data Set
Experience, Quality and Outcomes-Local Provider Flows
Emergency Care-Local Provider Flows
Diagnostic Services-Local Provider Flows
Diagnostic Imaging Dataset
Demand for Service-Local Provider Flows
Community-Local Provider Flows
Children and Young People Health
Ambulance-Local Provider Flows
Acute-Local Provider Flows
SUS (Accident & Emergency, Inpatient and Outpatient data)
Local Provider Data - Ambulance, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Population Data, Public Health & Screening services
Local Provider Data - Acute, Ambulance, Community, Diagnostic Services, Emergency Care, Primary Care

Objectives:

Invoice Validation – Identifiable
As an approved Controlled Environment for Finance (CEfF), the CCG receives SUS data Identifiable at the level of NHS number according to S.251 CAG 7-07(a)(b)(c)/2013. The data is required for the purpose of invoice validation. The NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF.
Data within the CCG CEfF is used for Invoice Validation purposes, in accordance with CAG 7-07(a)(b)(c)/2013. As an approved Controlled Environment for Finance (CEfF), the CCG receives Identifiable SUS data for the purpose of invoice validation. The data is used to confirm the accuracy of backing data sets and will not be shared outside the CEfF.
Staff within the CEfF may refer to other resources and data in other computer systems (such as the MedeAnalytics service) while performing invoice validation, but no data flows between the systems, or outside the CEfF.
Commissioning – Pseudonymised - SUS
This flow is required for the activity known as Contract Validation which is part of General Commissioning. The description here represents a separate Pseudonymised flow that includes records for all patients (including Type 2 Objectors) so the CCG can manage challenges against 100% of their commissioning records. Local patient identifiers are needed to facilitate contractual discussions between providers and commissioners. Contract Validation is a separate model that runs in a completely isolated environment that has no connection to other data sources.
Commissioning – Identifiable – SUS, Local Provider Flows, Mental Health Datasets, Maternity, IAPT, CYPHS and DIDS
NHS numbers are required to leave NHS Digital in accordance with CAG 2-03(a)/2013, to be transferred to the CCG ASH secure landing zone operated by MedeAnalytics. Identifiable data arriving in the secure landing zone is then Pseudonymised, so that it can be loaded into the MedeAnalytics commissioning service to enable linking with Pseudonymised data from other sources (listed in this application) that have been Pseudonymised using the same process.
SUS and Local Flows
To use Pseudonymised data to provide intelligence to support commissioning of health services. The Pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple Pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
These Pseudonymise data sets are used to provide accurate multi-provider pathway analysis.
Mental Health, Maternity, IAPT, CYPHS and DIDS
To use Pseudonymised data for the following datasets to provide intelligence to support commissioning of health services:
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
The Pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple de-identified linked datasets.
No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
Where analysis of pseudonymised patient records show that the associated patients could benefit from clinical interventions, GP Practice users who have legitimate relationships with the patients will be able to re-identify the patient records so that they can provide the interventions (direct care).

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. 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.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
All of the above lead to improved patient experience through more effective commissioning of services.
The introduction of integrated hubs is still underway, but the selection of pilot sites was informed by these analyses, MedeAnalytics will be used to evaluate the ongoing benefits of the hubs. Users fed back that:
Showing the number of benchmarked A&E admissions (and A&E attendances in the next analysis) from specific west Herts geographical locations in a heat map, will enable us and our providers to direct our finite health and social care (public health) resources more efficiently and effectively.
Users can better understand variation in their system, and make comparisons between populations and organisations in a fair and meaningful way with a greater understanding of what normal is. This will support routine opportunity analyses that they carry out in order to best target resources and best understand which activities have had a genuine benefit, and helped reduce costs to the system.
In addition, the platform provides access to comprehensive supporting information that commissioning organisations such as Clinical Commissioning Groups use to ensure that the services they commission are: * deliver the best outcomes for their patients * designed to cater for and meet the needs of the population they are responsible for;
* monitor condition prevalence within the population * identify health inequalities and work with local organisations and agencies to remove them
Also for Acute Trusts and other care providers it provides access to comprehensive supporting information that helps to: * ensure that the services they provide are of high quality, efficient and effective; * plan and re-engineer services to meet the changing requirements and developments in technology;
Direct measurement of the benefits associated with an enabling self-service system such as this is challenging, however, proxies can be provided through use metrics (number of individual users and frequency of use) as well as examples of decisions made by customers in the management and delivery of their services that have been supported by reports / information from the Mede tool

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
Commissioning
General reporting
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
Analytics Insights
Reports, charts and dashboards providing insights into:
1. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
2. Data Quality and Validation measures allowing data quality checks on the submitted data
3. Contract Management and Modelling
4. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
5. Understanding impacts and interdependency of care services

Processing:

North East London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
Invoice Validation – Identifiable - SUS
1. Identifiable SUS Data is obtained from the SUS Repository by North East London (NEL) Data Services for Commissioners Regional Office (DSCRO).
2. NEL DSCRO then pushes a one-way data flow of data Identifiable at the level of NHS number according to S.251 CAG 7-07(a)(b)(c)/2013 SUS data into North East London CSU Transfer Service.
3. The CSU lands the data only.
4. NEL CSU then securely transfers the Identifiable SUS data directly to the Controlled Environment for Finance (CEfF) located in the CCG.
5. The CEfF conduct the following processing activities for invoice validation purposes:
a. Checking the individual is registered to the Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Backing information is received from providers directly into the CCG CEfF. Once received, it is checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. Are in relation to a patient registered with the CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
6. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved

Segregation
Data for this purpose is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CCG CEfF staff are able to access data in the CEfF from the transfer service, and only CCG CEfF staff operate the invoice validation process within the CCG’s CEfF. Data flows directly in to the CEfF from NHS Digital (via the CSU) and from the providers – it does not flow through other processors.
Commissioning – Pseudonymised – SUS
Contract Validation
1. North & East London (NEL) Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS data Identifiable by NHS number for the CCG from the SUS Repository.
2. NEL DSCRO then remove national identifiers to Pseudonymise the data
3. NEL DSCRO then pushes a one-way data flow of Pseudonymised data into North East London CSU Transfer Service.
4. The CSU lands the data only.
5. NEL CSU then pass the processed, Pseudonymised data provided under DSCRO contracts to the CCGs data processor, MedeAnalytics where it is received, stored and processed
6. Records contain no national identifiers, but do contain the following local identifiers: [Local Patient Identifier], [Hospital Provider Spell No], [Unique CDS Identifier], [Attendance Identifier], and [A&E Attendance Number]
7. On arrival at MedeAnalytics, one of the MedeAnalytics operational staff (currently 4 individuals) then transfers the data from the secure landing zone to the ETL process. The ETL process then loads the data into the MedeAnalytics Contract Validation Module’s database.
8. Access is fully controlled by RBAC, signed off by Caldicott Guardians/SIROs.
9. CCGs use the workflow features provided by the MedeAnalytics Contract Validation Module to check recorded activity against contracts, and facilitate contract discussions with providers
10. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement
Segregation
This data is processed separately by the DSCRO, and sent as a separate feed into the CSU Transfer Service. CSU staff use dedicated credentials to upload Pseudonymised data to a separate dedicated area within the MedeAnalytics secure landing zone.
The MedeAnalytics Contract Validation module is built using different technology than the rest of the service – it runs inside Mongo DB, on a different virtual server than the rest of the service, and does not connect to any other data sources.
Users login to the Contract Validation service using different usernames and passwords. The same username and password cannot be used for other MedeAnalytics services, which run on different technology.
Commissioning – Pseudonymised – Local Flows
Management of services for non-contracted activities
1. North & East London (NEL) Data Services for Commissioners Regional Office (DSCRO) obtains Identifiable local provider data for the CCG directly from Providers.
2. NEL DSCRO then remove national identifiers to Pseudonymise it.
3. CCG staff then download the processed, Pseudonymised data from the NEL CSU transfer service, and will then delete the data from the transfer service. The CCG analyse the data to see patient journeys for pathways or service design, re-design and commissioning.
4. Aggregation of required data for CCG management use will be completed by the CCG.
5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreements
6. CCG staff then log in to the CSU transfer service and download the data to the CCG’s systems outside the CEfF. CSU staff then delete the data from the transfer service.

Commissioning – Identifiable – SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDS General Commissioning
Type 2 objections will be applied to Identifiable data before it leaves the DSCRO
1. North & East London (NEL) DSCRO – part of NHS Digital –
a. Obtain Identifiable SUS data from the SUS Repository at NHS Digital.
b. Obtain Identifiable local provider data directly from Providers (as per Data Services for Commissioners Directions 2015).
c. Obtain Identifiable MHMDS, MHLDDS, MHMDS, MSDS, IAPT, CYPHS and DIDS data from Exeter.
2. Data quality management and standardisation of the data is completed by the DSCRO.
3. NEL DSCRO then remove records for all patients who have registered type 2 objections
4. Records contain one national identifier [NHS number], and the following local identifiers: [Local Patient Identifier], [Unique CDS Identifier], [Hospital Provider Spell No], [Attendance Identifier], [A&E Attendance Number]. These local identifiers are required to manage duplicates and monitor QIPP schemes.
5. The DSCRO then securely transfers the following to the CSU:
a. The SUS data Identifiable at the level of NHS number
b. The Local Provider data Identifiable at the level of NHS number
c. The MHMDS, MHLDDS, MHMDS, MSDS, IAPT, CYPHS and DIDS data Identifiable at the level of NHS number
6. The CSU lands the data only.
7. Data is then transferred to the MedeAnalytics secure landing zone where it is Pseudonymised using the MedeAnalytics Pseudonymisation at Source tool.
8. Pseudonymised data is then transferred from the MedeAnalytics secure landing zone to the MedeAnalytics General Commissioning service, where it is joined with historical data and other health and care data sets provided in direct support of NHS contracts, that have been Pseudonymised using the same process, and with the same keys.
9. Access is fully controlled by RBAC, signed off by Caldicott Guardians/SIROs.
10. CCG users login to the MedeAnalytics Software-as-a-Service environment, and use online reports, charts and dashboards to analyse the data for the purposes listed.
11. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement
Segregation
Data is held within the MedeAnalytics system, and is segregated according to contract.
Only MedeAnalytics operational staff (currently 4 individuals operating under MedeAnalytics employment contracts) have access to data prior to loading into the main system.
All staff at MedeAnalytics undertake compulsory IG Toolkit training every year.
All MedeAnalytics staff understand their responsibilities with regard to receiving, storage, processing and handling of data, and contractual sanctions that can result in disciplinary actions including dismissal for contraventions are included in employee contracts.
Specific processes are in place to setup new system users, all of which require Caldicott Guardian or SIRO sign-off in order to obtain user identities and passwords. Identities and passwords are restricted to specific subsets of data according to their Roles, so that a CCG user can only see data for their own CCG, and a GP user can only see data for their own GP Practice.
All access to data is managed under Roles-Based Access Controls
Access to data is provided through the MedeAnalytics front end interfaces, for on-line access; while it is reasonable and allowable for users to export the results displayed in reports, charts and dashboards, so that the results can be used in board presentations, reports and other management documents, bulk export of underlying linked data sets is not possible.
All accesses are audited
CCG staff are only able to access data pertinent to their own CCG
Only GP Practice are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC (which is CG/SIRO approved – within the CCG). GP Practice staff are only able to access data for patients registered to their own practice.
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service (operated by BMS) that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.