NHS Digital Data Release Register - reformatted
NHS Hampshire And Isle Of Wight ICB - 10r projects
116 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
NHS Portsmouth CCG - RS — NIC-412777-Z2J9N
Opt outs honoured: (Excuses: Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2021-12 – 2024-12
Access method: Frequent Adhoc Flow
Data-controller type: NHS HAMPSHIRE AND ISLE OF WIGHT ICB - 10R
Sublicensing allowed: No
Datasets:
- SUS for Commissioners
Type of data: Identifiable
Objectives:
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS North of England Commissioning Support Unit & Cerner Limited.
Expected Benefits:
RISK STRATIFICATION
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. 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.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention.
3. 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.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes
6. Enables GPs to better target mental health care intervention
All of the above lead to improved patient experience and health outcomes through more effective commissioning of services.
Outputs:
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by Personnel (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patients clinician on their own systems for the purpose of direct care with a legitimate relationship.
ONWARD SHARING:
There is no requirement for the analytical teams to re-identify patients, but in the development of cohorts of patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification for that direct care purpose.
These instances of re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.
The following are typical (generic) examples of instances where a CCG might want to use the re-identification process:
A&E High Attendance usage
The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.
Polypharmacy re-IDs
CCG's can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.
The Re-identification process for direct care is as follows:
1. The CCG identifies a patient cohort to be re-identified for the purpose of direct care.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSUs Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestors relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timings, requesters identity etc) or via an automated system. For automated systems, steps 1 -3 wouldnt apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without more further checks.
4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
5. DSCROs retain an audit trail of all re-id requests
6. National Data opt outs are not applied for the purpose of direct care
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.
SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied -
For the purpose of Risk Stratification:
Patients who are normally registered and/or resident within the NHS Portsmouth CCG region (including historical activity where the patient was previously registered or resident in another commissioner
A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting
Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).
Amazon Web Services Limited provide Cloud Services for Cerner Limited and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Microsoft Limited provide Cloud Services for NHS North of England Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Pulsant and IT Professional Services Ltd do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Risk Stratification - Data Processor 1 & 2 - NHS North of England Commissioning Support Unit & Cerner Limited
1. Identifiable SUS+ data is transferred to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to NHS North of England Commissioning Support Unit, who securely pass the SUS+ data to Cerner Limited.
3. Identifiable GP Data is securely sent from the GP system to Cerner Limited.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Cerner Limited has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level
DSfC - NHS Portsmouth CCG IV, RS, Comm — NIC-54764-N1C1J
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))
Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(7), Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-08 – 2022-08 2017.06 — 2017.05.
Access method: Ongoing, Frequent adhoc flow, Frequent Adhoc Flow, One-Off
Data-controller type: NHS PORTSMOUTH CCG, NHS HAMPSHIRE AND ISLE OF WIGHT ICB - 10R
Sublicensing allowed: No
AGD/predecessor discussions: IGARD_Minutes_11_January_2018.pdf, igard_minutes_14_december_2017.pdf, igardminutes-15thoctober2020final.pdf, IGARD_Minutes_31.08.17.pdf, IGARD Minutes - 26 January 2023 final.pdf, IGARD Minutes - 29 July 2021 - FINAL.pdf
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 - Emergency Care
- Local Provider Data - Mental Health
- 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
- Local Provider Data - Demand for Service
- Local Provider Data - Diagnostic Services
- Local Provider Data - Other not elsewhere classified
- Maternity Services Dataset
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
- Population Data-Local Provider Flows
- Mental Health-Local Provider Flows
- Maternity Services Data Set
- Emergency Care-Local Provider Flows
- Diagnostic Imaging Dataset
- Community-Local Provider Flows
- Children and Young People Health
- Ambulance-Local Provider Flows
- Acute-Local Provider Flows
- Community Services Data Set
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Demand for Service-Local Provider Flows
- Diagnostic Services-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- SUS (Accident & Emergency, Inpatient and Outpatient data)
- Local Provider Data - Acute, Ambulance, Community, Emergency Care, Mental Health, Population Data
- Personal Demographic Service
Type of data: Anonymised - ICO Code Compliant, Identifiable
Objectives:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not.
Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a) (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care
Pseudonymised – 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.
Pseudonymised – 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 pseudonymised 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.
Yielded Benefits:
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
Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. 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.
2. 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.
3. 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.
4. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.
Pseudonymised – SUS and Local Flows
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
j. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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.
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.
j. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
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
Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners pseudonymised at patient level
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
Pseudonymised – SUS and Local Flows
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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
Processing:
South Collaborative DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
Invoice Validation
1. SUS Data is sent from the SUS Repository to South Collaborative DSCRO.
2. South Collaborative DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the South Central and West CSU.
3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area via the NHS Digital Spine System.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.
Risk Stratification
1. Identifiable SUS data is sent from the SUS Repository to South Collaborative Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South Collaborative DSCRO and the data identifiable at the level of NHS number is transferred securely to South Central and West CSU, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to South Central and West CSU.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. South Central and West CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once South Central and West CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level
Pseudonymised – SUS and Local Flows
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. South Collaborative DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South Central and West CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Aggregation of required data for CCG management use can be completed by the CSU or the CCG as instructed 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 Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) receives a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South Collaborative DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields and analysis.
3. South Central and West CSU then pass the processed, pseudonymised and linked data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use can be completed by the CSU or the CCG
6. 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. External aggregated reports only with small number suppression can be shared with CCG Stakeholders where contractual arrangements are in place.