DSfC - NHS East and North Hertfordshire CCG - IV & Comm
NHS Hertfordshire and West Essex ICB · Sub ICB Location
Listed under NHS Central East Integrated Care Board.
Expired The latest version ended on 28 March 2024. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-55679-K9X4J
- Latest version
- v7.2
- Term of latest version
- 29 March 2021 to 28 March 2024
- Start date
- Before 1 October 2019
- Data controller
- Sole Data Controller
- Commercial purposes
- No
- Sublicensing
- No
- Files released to date
- 0
Why the data was released
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by NHS East and North Hertfordshire CCG
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population
Provide intelligence about the safety and effectiveness of medicines.
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.
Processing for commissioning will be conducted by Outcomes Based Healthcare Limited, MedeAnalytics International Ltd, Optum Health Solutions (UK) Ltd and NHS East and North Hertfordshire CCG.
MedeAnalytics
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics International Ltd's Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics International Ltd system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics International Ltd.
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors or the national data opt-out, as the records are no longer identifiable when they leave the protected NHS Digital environment.
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).
Optum Health Solutions UK Ltd - NHS England Wave 2 PHM project
NHS East and North Hertfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The Optum Health Solutions (UK) Ltd involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor the this project will be removed from this agreement by amendment.
Outcomes Based Healthcare Limited
Outcomes Based Healthcare Limited (OBH) will use pseudonymised data to support the measurement of outcomes. This includes development of outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of NHS East and North Hertfordshire CCG to Herefordshire Community Trust (HCT). This will enable near real-time outcome measurement for specific population segments, where the entire East and North Hertfordshire registered population is accounted for (including those who are currently using HCT services and those who may require services in the future), providing a whole population view.
The following pseudonymised, linked datasets are required:
• Secondary Uses Service (SUS)
• Community Data (received by MedeAnalytics directly from providers)
Processing activities
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)
ONWARD SHARING:
Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.
Segregation
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
Data Minimisation
Data Minimisation in relation to the data sets listed within section 3 are listed below. This also includes the purpose on which they would be applied -
For the purpose of Commissioning:
• Patients who are normally registered and/or resident within NHS East and North Hertfordshire CCG (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS East and North Hertfordshire CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS East and North Hertfordshire CCG - this is only for commissioning and relates to both national and local flows.
For the purpose of Invoice Validation:
• CCG of residence and/or registration.
Microsoft Limited supply provide Cloud Services for Outcomes Based Healthcare and Optum Health Solutions (UK) 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.
Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as processors. 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.
Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF also receive backing data from the provider.
4. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, it will be 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. 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.
5. 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.
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – MedeAnalytics International Ltd
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS). Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data) data only is securely transferred from the DSCRO to MedeAnalytics International Ltd.
2. MedeAnalytics International Ltd add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
2. 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]
3. On arrival at Medeanalytics International Limited, one of the Medeanalytics International Limited operational staff then transfers the data from the secure landing zone to the ETL process. The Extract Transform Load (ETL) process then loads the data into the Medeanalytics International Limited system, where it is linked.
4. Allowed linkage is between the data sets contained within point 1 and the following data that is pseudonymised at source using a pseudonymisation tool:
o Social Care data
o GP Practice data
o Community data
o Mental Health data
5. MedeAnalytics International Ltd provides analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management.
d. Undertake data quality and validation checks.
e. Thoroughly investigate the needs of the population.
f. Understand cohorts of residents who are at risk.
g. Conduct health needs assessments.
6. Access is fully controlled by Role Based Access Control (RBAC), signed off by Caldicott Guardians/SIROs.
7. CCGs use the workflow features provided by the Medeanalytics International Limited Contract Validation Module to check recorded activity against contracts, and facilitate contract discussions with providers
8. CCG users use online features of the Medeanalytics International Limited system to produce reports, charts and dashboards to analyse the data for the purposes listed.
9. Aggregation of required data for CCG management use will be completed by MedeAnalytics International Ltd or the CCG as instructed by the CCG.
10. MedeAnalytics pass Pseudonymised SUS, Local Provider Data, Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS), GP Primary Care Data and Social Care Data to Optum Health Solutions (UK) Ltd.
11. Optum Health Solutions (UK) Ltd analyse the data and pass the data to the CCG.
12. 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 as set out within the NHS Digital guidance applicable to each data set.
Segregation
Data is held within the MedeAnalytics International Ltd system, and is segregated according to contract.
Only MedeAnalytics International Ltd operational staff (currently 4 individuals operating under full time MedeAnalytics International Ltd employment contracts) have access to data prior to loading into the main system.
All staff at MedeAnalytics International Ltd undertake compulsory IG Toolkit training every year.
All MedeAnalytics International Ltd 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 (RBAC).
Access to data is provided through the MedeAnalytics International Ltd 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.
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.
Only GP Practice users 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 CCG/SIRO approved– within the CCG).
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.
Data Processor 2 - Optum Health Solutions (UK) Ltd
1) Pseudonymised SUS, Local Provider Data, Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS), GP Primary Care Data and Social Care Data is securely transferred from MedeAnalytics to Optum Health Solutions (UK) Ltd.
2) Optum Health Solutions (UK) Ltd provide analysis to:
- Whole population segmentation to assess population health needs;
- Prospective risk scoring for individuals to indicate the likelihood of future adverse events;
- Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk;
- Longitudinal analysis of intersegmental drift, identifying individuals who move between complexity classifications and the drivers of these transitions;
- The production of individual level theographs to identify gaps in care.
3) Allowed linkage is between the datasets contained within point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
4) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to NHS East and North Hertfordshire CCG.
5) Aggregation of required data for NHS East and North Hertfordshire CCG management use will be completed by Optum Health Solutions (UK) Ltd or NHS East and North Hertfordshire CCG as instructed by the CCG.
6) Patient level data will not be shared outside of NHS East and North Hertfordshire 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 as set out within NHS Digital guidance applicable to each data set.
7) Optum Health Solutions (UK) Ltd will only be in receipt of data and only permitted to act as a Data Processor for the period specified in the contract with NHS East and North Hertfordshire CCG.
Data Processor 3 - NHS East and North Hertfordshire CCG
Commissioning – Pseudonymised – Local Flows
Management of services for non-contracted activities
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Diagnostic Service
e. Primary Care Services
Data quality management and pseudonymisation is completed within the DSCRO is then disseminated as follows:
2. DSCRO then remove national identifiers to Pseudonymise the data
3. CCG staff then download the processed, Pseudonymised data from the DSCRO. 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 Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.
Data held by Optum Health Solutions (UK) Ltd for the purpose of the NHS England Wave 2 PHM project will be destroyed within 6 months of the completion of the project and permissions as a data processor will be removed from this agreement by amendment.
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Pseudonymised SUS and Community Data (received directly by providers) are transferred from MedeAnalytics to OBH , based on data specifications that includes only that information required for the outcomes selected by Herefordshire Community Trust (HCT) via secure File Transfer Protocol to OBH.
2. Under instruction from the CCG (via a data processing agreement), OBH provide analysis to HCT and additional providers/commissioners as required through the online OBH Outcomes Platform tool. This includes:
a. data quality and validation checks
b. population segmentation analytics
c. understand patient journeys for pathway and service re-design, as well as recording the end results of care through outcome measurement
d. statistical process control
e. aggregate commissioning intelligence reports with small number suppression to named users in HCT.
OBH will not have access to the pseudonymisation tool or encryption key, which allows data to be pseudonymised, therefore is unable to re-identify the data. Only aggregated data with small numbers suppressed will be shared outside of the Data Controller / Processors.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for 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.
9. 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
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system.
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
Data Processor 1 - MedeAnalytics
Reports, charts and dashboards providing insights into:
1) Comparators of CCG performance with similar CCG's as set out by a specific range of care quality and performance measure 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, including:
- Patients at highest risk of admission;
- Most expensive patients (top 15%);
- Frail and elderly;
- Patients that are currently in hospital;
- Patients with the most referrals to secondary care;
- Patients with the most emergency activity;
- Patients with the most expensive prescriptions;
- Patients recently moving from one care setting to another;
- Patients discharged from hospital;
- Patients discharged from the community.
5) Understanding impacts and interdependency of care services.
Data Processor 2 – Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Outcomes Platform access via secure login (available to named individuals in HCT and providers/commissioners as required only) provided:
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables visualisation of baselines using historical data for each outcome, and for users to set improvement trajectories
ii. Monitoring of outcomes on a monthly basis for the period of the contract between OBH and HCT
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Secure access to aggregated intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Expected measurable benefits
INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.
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. Financial and 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.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to 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.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources.
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
Data Processor 1 - MedeAnalytics
All of the above lead to improved patient experience through more effective commissioning of services. Users of the same MedeAnalytics service have feedback that:
Showing the number of benchmarked A&E admissions (and A&E attendances in the next analysis) from specific local geographical locations in a heat map, will enable the CCG and 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:
- Deliver the best outcomes for their patients;
- 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.
Data Processor 4 - Outcomes Based Healthcare (OBH)
1. Population segmentation and outcome measurement across the entire population produces data that looks at the end results of care, burden of disease and complications, and their severity, as well as system activity metrics, and a better understanding of the population through grouping people by need. Including analysis showing impact of deprivation on outcomes and quality of care
2. Outcomes data across the entire population will support decision making around service transformation, integrated care, care planning, care coordination, and service delivery, with the focus on improving the outcomes
3. Outcomes data supports quality process improvement within care pathways
4. Access to stakeholders across the entire health system, including commissioners and providers to have a single, transparent view of outcomes data
5. Refocuses health system providers (including health and social care providers) to work in a more integrated way to reduce the burden of disease
6. Enables commissioners and providers to compare whether their longer-term targets and improvement trajectories set for each outcome, have been met. Whilst allowing providers to focus their efforts on improving these outcomes, for specific population groups, over a period of years.
Benefits reported so far
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. In particular, the data will allow improved population segmentation analysis, including an analysis of activity and cost across multiple care settings, to support more targeted care and QIPP.
Invoice validation
The invoice validation process is undertaken on a monthly basis and now forms part of the CCG’s business as usual. This includes a monthly validation and reconciliation process to ensure that all payments are accurate and agreed with providers. In addition the information is used to monitor performance and produce in-depth analysis of areas of over or under performance.
Commissioning
A range of activity and financial reports are produced on a monthly or quarterly basis, including the following:
Local analysis has been undertaken to support the development of QIPP schemes where national benchmarking has identified areas where the CCG is an outlier, this includes opportunities identified through NHS RightCare. This local analysis has underpinned the development of new QIPP schemes for 2019/20.
The CCG has worked with the Herts County Council Public Health Intelligence team to produce national indicators at locality or GP practice level, where appropriate. This has included analysis by locality of avoidable emergency admissions.
Comprehensive analysis to support the commissioning and planning round for 2019/20 and ensuring consistency between provider contract plans and national activity and planning requirements. This includes identifying and understanding gaps where different definitions are used, for example local definitions for diagnostic tests and non-consultant led outpatient activity.
Regular performance and locality information packs produced to identify areas of under-performance and locality variations in activity rates and performance.
Practice level reports showing financial performance against budget produced on a monthly basis. Initial analysis to support population segmentation, including multiple long term conditions, across the CCG by GP practice and locality. This will be an on-going development to support the local population health management strategy.
Datasets on the latest version
Legal basis for provision: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| Acute-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Ambulance-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Children and Young People Health | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Civil Registration - Births | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Civil Registrations of Death | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Community Services Data Set (CSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Community-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Demand for Service-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Diagnostic Imaging Data Set (DID) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Diagnostic Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| e-Referral Service for Commissioning | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Emergency Care-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Experience, Quality and Outcomes-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Improving Access to Psychological Therapies (IAPT) v1.5 | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Maternity Services Data Set | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Medicines dispensed in Primary Care (NHSBSA data) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health and Learning Disabilities Data Set (MHLDDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health Minimum Data Set (MHMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health Services Data Set (MHSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| National Diabetes Audit | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Patient Reported Outcome Measures (PROMs) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Personal Demographic Service | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Population Data-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Primary Care Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Public Health and Screening Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Summary Hospital-level Mortality Indicator (SHMI) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| SUS for Commissioners | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| SUS for Commissioners | Identifiable | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
Files released
Files released counts only files released externally by DARS. Access granted in NHS England's own systems, such as its Secure Data Environment, is not included.
No files recorded as released under this agreement.
Version history
The register lists each renewal of this agreement as a separate row. This site has 5 versions — earlier versions existed before this site's records begin.
DARS-NIC-55679-K9X4J-v7.2 29 March 2021 to 28 March 2024
- Title
- DSfC - NHS East and North Hertfordshire CCG - IV & Comm
- Commercial
- No
- Sublicensing
- No
- Datasets
- 31
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-55679-K9X4J-v6.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-03-29 | |
| End date | 2024-03-28 |
Unchanged: Objective for processing, Processing activities, Expected output, Expected measurable benefits, Benefits reported.
DARS-NIC-55679-K9X4J-v6.2 10 March 2021 to 31 May 2021
- Title
- DSfC - NHS East and North Hertfordshire CCG - IV & Comm
- Commercial
- No
- Sublicensing
- No
- Datasets
- 31
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-55679-K9X4J-v5.4
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-03-10 | |
| End date | 2021-05-31 | |
| Acute-Local Provider Flows: sensitivity | Sensitive | |
| Acute-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Ambulance-Local Provider Flows: sensitivity | Sensitive | |
| Ambulance-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Children and Young People Health: sensitivity | Sensitive | |
| Children and Young People Health: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Civil Registration - Births: sensitivity | Sensitive | |
| Civil Registration - Births: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Civil Registrations of Death: sensitivity | Sensitive | |
| Civil Registrations of Death: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Community Services Data Set (CSDS): sensitivity | Sensitive | |
| Community Services Data Set (CSDS): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Community-Local Provider Flows: sensitivity | Sensitive | |
| Community-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Demand for Service-Local Provider Flows: sensitivity | Sensitive | |
| Demand for Service-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Diagnostic Imaging Data Set (DID): sensitivity | Sensitive | |
| Diagnostic Imaging Data Set (DID): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Diagnostic Services-Local Provider Flows: sensitivity | Sensitive | |
| Diagnostic Services-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Emergency Care-Local Provider Flows: sensitivity | Sensitive | |
| Emergency Care-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Experience, Quality and Outcomes-Local Provider Flows: sensitivity | Sensitive | |
| Experience, Quality and Outcomes-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Improving Access to Psychological Therapies Data Set_v1.5: sensitivity | Sensitive | |
| Improving Access to Psychological Therapies Data Set_v1.5: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Maternity Services Data Set v1.5: sensitivity | Sensitive | |
| Maternity Services Data Set v1.5: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Mental Health Minimum Data Set (MHMDS): sensitivity | Sensitive | |
| Mental Health Minimum Data Set (MHMDS): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Mental Health Services Data Set (MHSDS): sensitivity | Sensitive | |
| Mental Health Services Data Set (MHSDS): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): sensitivity | Sensitive | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Mental Health-Local Provider Flows: sensitivity | Sensitive | |
| Mental Health-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): sensitivity | Sensitive | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| National Diabetes Audit: sensitivity | Sensitive | |
| National Diabetes Audit: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: sensitivity | Sensitive | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Patient Reported Outcome Measures (PROMs): sensitivity | Sensitive | |
| Patient Reported Outcome Measures (PROMs): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Personal Demographic Service: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Population Data-Local Provider Flows: sensitivity | Sensitive | |
| Population Data-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Primary Care Services-Local Provider Flows: sensitivity | Sensitive | |
| Primary Care Services-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Public Health and Screening Services-Local Provider Flows: sensitivity | Sensitive | |
| Public Health and Screening Services-Local Provider Flows: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| SUS for Commissioners: sensitivity | Sensitive | |
| SUS for Commissioners: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| Summary Hospital-level Mortality Indicator (SHMI): common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) | |
| e-Referral Service for Commissioning: sensitivity | Sensitive | |
| e-Referral Service for Commissioning: common law duty of confidentiality | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
Datasets: + Medicines dispensed in Primary Care (NHSBSA data)
Objective for processing
[2 paragraphs unchanged]
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is
are
able to ensure that the activity claimed for each patient is their
[45 words unchanged]
of backing-data sets (data from providers) and will not be used further.
[36 paragraphs unchanged]
- Medicines Dispensed in Primary Care (NHSBSA Data)
[15 paragraphs unchanged]
Provide intelligence about the safety and effectiveness of medicines.
[13 paragraphs unchanged]
Processing activities
[69 paragraphs unchanged]
19. Medicines Dispensed in Primary Care (NHSBSA Data)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[44 words unchanged]
(NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service
(PDS) and
(PDS),
Summary Hospital-level Mortality Indicator (SHMI)
and Medicines Dispensed in Primary Care (NHSBSA Data)
data only is securely transferred from the DSCRO to MedeAnalytics International Ltd.
[27 paragraphs unchanged]
10. MedeAnalytics pass Pseudonymised SUS, Local Provider Data,
Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS),
GP Primary Care Data and Social Care Data to Optum Health Solutions (UK) Ltd.
[18 paragraphs unchanged]
1) Pseudonymised SUS, Local Provider Data,
Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS),
GP Primary Care Data and Social Care Data is securely transferred from MedeAnalytics to Optum Health Solutions (UK) Ltd.
[37 paragraphs unchanged]
Expected output
[53 paragraphs unchanged]
25. Investigate mortality outcomes for
trusts
trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system.
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
[30 paragraphs unchanged]
Expected measurable benefits
[53 paragraphs unchanged]
26. Allow focused commissioning support based on factual data rather than assumed and projected
sources
sources.
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
[15 paragraphs unchanged]
6. Enables commissioners and providers to compare whether their longer-term targets and
[16 words unchanged]
on improving these outcomes, for specific population groups, over a period of
years
years.
Unchanged: Benefits reported.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by NHS East and North Hertfordshire CCG
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population
Provide intelligence about the safety and effectiveness of medicines.
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.
Processing for commissioning will be conducted by Outcomes Based Healthcare Limited, MedeAnalytics International Ltd, Optum Health Solutions (UK) Ltd and NHS East and North Hertfordshire CCG.
MedeAnalytics
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics International Ltd's Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics International Ltd system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics International Ltd.
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors or the national data opt-out, as the records are no longer identifiable when they leave the protected NHS Digital environment.
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).
Optum Health Solutions UK Ltd - NHS England Wave 2 PHM project
NHS East and North Hertfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The Optum Health Solutions (UK) Ltd involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor the this project will be removed from this agreement by amendment.
Outcomes Based Healthcare Limited
Outcomes Based Healthcare Limited (OBH) will use pseudonymised data to support the measurement of outcomes. This includes development of outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of NHS East and North Hertfordshire CCG to Herefordshire Community Trust (HCT). This will enable near real-time outcome measurement for specific population segments, where the entire East and North Hertfordshire registered population is accounted for (including those who are currently using HCT services and those who may require services in the future), providing a whole population view.
The following pseudonymised, linked datasets are required:
• Secondary Uses Service (SUS)
• Community Data (received by MedeAnalytics directly from providers)
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for 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.
9. 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
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system.
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
Data Processor 1 - MedeAnalytics
Reports, charts and dashboards providing insights into:
1) Comparators of CCG performance with similar CCG's as set out by a specific range of care quality and performance measure 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, including:
- Patients at highest risk of admission;
- Most expensive patients (top 15%);
- Frail and elderly;
- Patients that are currently in hospital;
- Patients with the most referrals to secondary care;
- Patients with the most emergency activity;
- Patients with the most expensive prescriptions;
- Patients recently moving from one care setting to another;
- Patients discharged from hospital;
- Patients discharged from the community.
5) Understanding impacts and interdependency of care services.
Data Processor 2 – Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Outcomes Platform access via secure login (available to named individuals in HCT and providers/commissioners as required only) provided:
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables visualisation of baselines using historical data for each outcome, and for users to set improvement trajectories
ii. Monitoring of outcomes on a monthly basis for the period of the contract between OBH and HCT
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Secure access to aggregated intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Benefits reported
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. In particular, the data will allow improved population segmentation analysis, including an analysis of activity and cost across multiple care settings, to support more targeted care and QIPP.
Invoice validation
The invoice validation process is undertaken on a monthly basis and now forms part of the CCG’s business as usual. This includes a monthly validation and reconciliation process to ensure that all payments are accurate and agreed with providers. In addition the information is used to monitor performance and produce in-depth analysis of areas of over or under performance.
Commissioning
A range of activity and financial reports are produced on a monthly or quarterly basis, including the following:
Local analysis has been undertaken to support the development of QIPP schemes where national benchmarking has identified areas where the CCG is an outlier, this includes opportunities identified through NHS RightCare. This local analysis has underpinned the development of new QIPP schemes for 2019/20.
The CCG has worked with the Herts County Council Public Health Intelligence team to produce national indicators at locality or GP practice level, where appropriate. This has included analysis by locality of avoidable emergency admissions.
Comprehensive analysis to support the commissioning and planning round for 2019/20 and ensuring consistency between provider contract plans and national activity and planning requirements. This includes identifying and understanding gaps where different definitions are used, for example local definitions for diagnostic tests and non-consultant led outpatient activity.
Regular performance and locality information packs produced to identify areas of under-performance and locality variations in activity rates and performance.
Practice level reports showing financial performance against budget produced on a monthly basis. Initial analysis to support population segmentation, including multiple long term conditions, across the CCG by GP practice and locality. This will be an on-going development to support the local population health management strategy.
DARS-NIC-55679-K9X4J-v5.4 15 December 2020 to 14 December 2023
- Title
- DSfC - NHS East and North Hertfordshire CCG - IV & Comm
- Commercial
- No
- Sublicensing
- No
- Datasets
- 30
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-55679-K9X4J-v4.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-12-15 | |
| End date | 2023-12-14 | |
| Acute-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Ambulance-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Children and Young People Health: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registration - Births: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registrations of Death: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community Services Data Set (CSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Demand for Service-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Imaging Data Set (DID): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Emergency Care-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Experience, Quality and Outcomes-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Improving Access to Psychological Therapies Data Set_v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Maternity Services Data Set v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Minimum Data Set (MHMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Services Data Set (MHSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Diabetes Audit: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Patient Reported Outcome Measures (PROMs): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Population Data-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Primary Care Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Public Health and Screening Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| SUS for Commissioners: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. |
Datasets: + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI); + e-Referral Service for Commissioning
Objective for processing
[36 paragraphs unchanged] - e-Referral Service (eRS) - Personal Demographics Service (PDS) - Summary Hospital-level Mortality Indicator (SHMI) [12 paragraphs unchanged] Patient stratification and predictive modelling - to identify specific cohorts of patients at risk of requiring hospital admission and other avoidable factors such [7 words unchanged] executed against linked de-identified data, and identification of future service delivery models Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand. Support measuring the health, mortality or care needs of the total local population [1 paragraph unchanged] Processing for commissioning will be conducted by Outcomes Based Healthcare Limited, MedeAnalytics International Ltd, Optum Health Solutions (UK) Ltd and NHS East and North Hertfordshire CCG. MedeAnalytics [3 paragraphs unchanged] Optum Health Solutions UK Ltd - NHS England Wave 2 PHM project [1 paragraph unchanged] Outcomes Based Healthcare Limited Outcomes Based Healthcare Limited (OBH) will use pseudonymised data to support the measurement of outcomes. This includes development of outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of NHS East and North Hertfordshire CCG to Herefordshire Community Trust (HCT). This will enable near real-time outcome measurement for specific population segments, where the entire East and North Hertfordshire registered population is accounted for (including those who are currently using HCT services and those who may require services in the future), providing a whole population view. The following pseudonymised, linked datasets are required: • Secondary Uses Service (SUS) • Community Data (received by MedeAnalytics directly from providers)
Processing activities
PROCESSING CONDITIONS:
[23 paragraphs unchanged]
Microsoft Limited supply provide Cloud Services for Outcomes Based Healthcare and Optum Health Solutions (UK) 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.
Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as processors. 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.
[40 paragraphs unchanged]
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[32 words unchanged]
Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit
(NDA) and
(NDA),
Patient Reported Outcome Measures
(PROMs)
(PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data
only is securely transferred from the DSCRO to MedeAnalytics International Ltd.
[45 paragraphs unchanged]
Data Processor 2 -
Optum Health Solutions (UK) Ltd
Commissioning - Data Processor
[12 paragraphs unchanged]
Data Processor 3 -
NHS East and North Hertfordshire CCG
[14 paragraphs unchanged]
In addition to the dissemination of Cancer Waiting Times Data via the
[26 words unchanged]
a need to process the data for the purposes described in this
agreement.”
agreement.
[1 paragraph unchanged]
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Pseudonymised SUS and Community Data (received directly by providers) are transferred from MedeAnalytics to OBH , based on data specifications that includes only that information required for the outcomes selected by Herefordshire Community Trust (HCT) via secure File Transfer Protocol to OBH.
2. Under instruction from the CCG (via a data processing agreement), OBH provide analysis to HCT and additional providers/commissioners as required through the online OBH Outcomes Platform tool. This includes:
a. data quality and validation checks
b. population segmentation analytics
c. understand patient journeys for pathway and service re-design, as well as recording the end results of care through outcome measurement
d. statistical process control
e. aggregate commissioning intelligence reports with small number suppression to named users in HCT.
OBH will not have access to the pseudonymisation tool or encryption key, which allows data to be pseudonymised, therefore is unable to re-identify the data. Only aggregated data with small numbers suppressed will be shared outside of the Data Controller / Processors.
Expected output
[26 paragraphs unchanged]
8. GP Practice level dashboard
reports include high flyers.
reports.
[5 paragraphs unchanged]
o
Most expensive patients
High cost activity uses
(top 15%)
[14 paragraphs unchanged]
Analytic Insights
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts
Data Processor 1 - MedeAnalytics
[16 paragraphs unchanged]
Data Processor 2 –
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
[2 paragraphs unchanged]
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Outcomes Platform access via secure login (available to named individuals in HCT and providers/commissioners as required only) provided:
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables visualisation of baselines using historical data for each outcome, and for users to set improvement trajectories
ii. Monitoring of outcomes on a monthly basis for the period of the contract between OBH and HCT
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Secure access to aggregated intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Expected measurable benefits
[39 paragraphs unchanged]
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
contracts.
[5 paragraphs unchanged]
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to 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.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
Data Processor 1 - MedeAnalytics
[8 paragraphs unchanged]
Data Processor 4 - Outcomes Based Healthcare (OBH)
1. Population segmentation and outcome measurement across the entire population produces data that looks at the end results of care, burden of disease and complications, and their severity, as well as system activity metrics, and a better understanding of the population through grouping people by need. Including analysis showing impact of deprivation on outcomes and quality of care
2. Outcomes data across the entire population will support decision making around service transformation, integrated care, care planning, care coordination, and service delivery, with the focus on improving the outcomes
3. Outcomes data supports quality process improvement within care pathways
4. Access to stakeholders across the entire health system, including commissioners and providers to have a single, transparent view of outcomes data
5. Refocuses health system providers (including health and social care providers) to work in a more integrated way to reduce the burden of disease
6. Enables commissioners and providers to compare whether their longer-term targets and improvement trajectories set for each outcome, have been met. Whilst allowing providers to focus their efforts on improving these outcomes, for specific population groups, over a period of years
Unchanged: Benefits reported.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by NHS East and North Hertfordshire CCG
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population
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.
Processing for commissioning will be conducted by Outcomes Based Healthcare Limited, MedeAnalytics International Ltd, Optum Health Solutions (UK) Ltd and NHS East and North Hertfordshire CCG.
MedeAnalytics
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics International Ltd's Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics International Ltd system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics International Ltd.
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors or the national data opt-out, as the records are no longer identifiable when they leave the protected NHS Digital environment.
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).
Optum Health Solutions UK Ltd - NHS England Wave 2 PHM project
NHS East and North Hertfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The Optum Health Solutions (UK) Ltd involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor the this project will be removed from this agreement by amendment.
Outcomes Based Healthcare Limited
Outcomes Based Healthcare Limited (OBH) will use pseudonymised data to support the measurement of outcomes. This includes development of outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of NHS East and North Hertfordshire CCG to Herefordshire Community Trust (HCT). This will enable near real-time outcome measurement for specific population segments, where the entire East and North Hertfordshire registered population is accounted for (including those who are currently using HCT services and those who may require services in the future), providing a whole population view.
The following pseudonymised, linked datasets are required:
• Secondary Uses Service (SUS)
• Community Data (received by MedeAnalytics directly from providers)
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for 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.
9. 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
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts
Data Processor 1 - MedeAnalytics
Reports, charts and dashboards providing insights into:
1) Comparators of CCG performance with similar CCG's as set out by a specific range of care quality and performance measure 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, including:
- Patients at highest risk of admission;
- Most expensive patients (top 15%);
- Frail and elderly;
- Patients that are currently in hospital;
- Patients with the most referrals to secondary care;
- Patients with the most emergency activity;
- Patients with the most expensive prescriptions;
- Patients recently moving from one care setting to another;
- Patients discharged from hospital;
- Patients discharged from the community.
5) Understanding impacts and interdependency of care services.
Data Processor 2 – Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Data Processor 4 – Outcomes Based Healthcare (OBH)
1. Outcomes Platform access via secure login (available to named individuals in HCT and providers/commissioners as required only) provided:
a. Aggregated monthly values for each outcome (with small number suppression, including any values under 5).
i. This enables visualisation of baselines using historical data for each outcome, and for users to set improvement trajectories
ii. Monitoring of outcomes on a monthly basis for the period of the contract between OBH and HCT
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Population segment insights related to outcomes
e. Information schedule describing the outcomes to be monitored, the technical description, and annual baseline data for each outcome.
2. Secure access to aggregated intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Benefits reported
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. In particular, the data will allow improved population segmentation analysis, including an analysis of activity and cost across multiple care settings, to support more targeted care and QIPP.
Invoice validation
The invoice validation process is undertaken on a monthly basis and now forms part of the CCG’s business as usual. This includes a monthly validation and reconciliation process to ensure that all payments are accurate and agreed with providers. In addition the information is used to monitor performance and produce in-depth analysis of areas of over or under performance.
Commissioning
A range of activity and financial reports are produced on a monthly or quarterly basis, including the following:
Local analysis has been undertaken to support the development of QIPP schemes where national benchmarking has identified areas where the CCG is an outlier, this includes opportunities identified through NHS RightCare. This local analysis has underpinned the development of new QIPP schemes for 2019/20.
The CCG has worked with the Herts County Council Public Health Intelligence team to produce national indicators at locality or GP practice level, where appropriate. This has included analysis by locality of avoidable emergency admissions.
Comprehensive analysis to support the commissioning and planning round for 2019/20 and ensuring consistency between provider contract plans and national activity and planning requirements. This includes identifying and understanding gaps where different definitions are used, for example local definitions for diagnostic tests and non-consultant led outpatient activity.
Regular performance and locality information packs produced to identify areas of under-performance and locality variations in activity rates and performance.
Practice level reports showing financial performance against budget produced on a monthly basis. Initial analysis to support population segmentation, including multiple long term conditions, across the CCG by GP practice and locality. This will be an on-going development to support the local population health management strategy.
DARS-NIC-55679-K9X4J-v4.3 1 February 2020 to 31 January 2023
- Title
- DSfC - NHS East and North Hertfordshire CCG - IV & Comm
- Commercial
- No
- Sublicensing
- No
- Datasets
- 27
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-55679-K9X4J-v3.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-02-01 | |
| End date | 2023-01-31 |
Objective for processing
[50 paragraphs unchanged]
Processing for commissioning will be conducted by MedeAnalytics International
Ltd, Optum Health Solutions (UK)
Ltd
and NHS East and North Hertfordshire CCG.
[1 paragraph unchanged]
Further, as national identifiers are removed by NHS Digital before transmission, thus
[47 words unchanged]
in context, there is no need to remove records for type 2
objectors,
objectors or the national data opt-out,
as the records are no longer identifiable when they leave the protected NHS Digital environment.
[1 paragraph unchanged]
NHS England Wave 2 PHM project
NHS East and North Hertfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The Optum Health Solutions (UK) Ltd involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor the this project will be removed from this agreement by amendment.
Processing activities
[16 paragraphs unchanged]
• Patients who are normally registered and/or resident within
the commissioner
NHS East and North Hertfordshire CCG
(including historical activity where the patient was previously registered or resident in another commissioner).
[1 paragraph unchanged]
• Patients treated by a provider where
the commissioner
NHS East and North Hertfordshire CCG
is the host/co-ordinating commissioner and/or has the primary responsibility for the provider
[8 words unchanged]
is only for commissioning and relates to both national and local flows.
[1 paragraph unchanged]
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of
the commissioner
NHS East and North Hertfordshire CCG
- this is only for commissioning and relates to both national and local flows.
[55 paragraphs unchanged]
4. Allowed linkage is between the data sets contained within point 1 and the following data that is pseudonymised at source using
the MedeAnalytics International Ltd
a
pseudonymisation tool:
[16 paragraphs unchanged]
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. External aggregated reports only with small number suppression can be shared as set out within the NHS Digital guidance applicable to each data set.
10. MedeAnalytics pass Pseudonymised SUS, Local Provider Data, GP Primary Care Data and Social Care Data to Optum Health Solutions (UK) Ltd.
11. Optum Health Solutions (UK) Ltd analyse the data and pass the data to the CCG.
12. 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 as set out within the NHS Digital guidance applicable to each data set.
[8 paragraphs unchanged]
All accesses are
audited
audited.
[6 paragraphs unchanged]
Optum Health Solutions (UK) Ltd
Commissioning - Data Processor
1) Pseudonymised SUS, Local Provider Data, GP Primary Care Data and Social Care Data is securely transferred from MedeAnalytics to Optum Health Solutions (UK) Ltd.
2) Optum Health Solutions (UK) Ltd provide analysis to:
- Whole population segmentation to assess population health needs;
- Prospective risk scoring for individuals to indicate the likelihood of future adverse events;
- Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk;
- Longitudinal analysis of intersegmental drift, identifying individuals who move between complexity classifications and the drivers of these transitions;
- The production of individual level theographs to identify gaps in care.
3) Allowed linkage is between the datasets contained within point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
4) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to NHS East and North Hertfordshire CCG.
5) Aggregation of required data for NHS East and North Hertfordshire CCG management use will be completed by Optum Health Solutions (UK) Ltd or NHS East and North Hertfordshire CCG as instructed by the CCG.
6) Patient level data will not be shared outside of NHS East and North Hertfordshire 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 as set out within NHS Digital guidance applicable to each data set.
7) Optum Health Solutions (UK) Ltd will only be in receipt of data and only permitted to act as a Data Processor for the period specified in the contract with NHS East and North Hertfordshire CCG.
NHS East and North Hertfordshire CCG
[15 paragraphs unchanged]
Data held by Optum Health Solutions (UK) Ltd for the purpose of the NHS England Wave 2 PHM project will be destroyed within 6 months of the completion of the project and permissions as a data processor will be removed from this agreement by amendment.
Expected output
[47 paragraphs unchanged] Analytic Insights Reports, charts and dashboards providing insights into: 1) Comparators of CCG performance with similar CCG's as set out by a specific range of care quality and performance measure 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, including: - Patients at highest risk of admission; - Most expensive patients (top 15%); - Frail and elderly; - Patients that are currently in hospital; - Patients with the most referrals to secondary care; - Patients with the most emergency activity; - Patients with the most expensive prescriptions; - Patients recently moving from one care setting to another; - Patients discharged from hospital; - Patients discharged from the community. 5) Understanding impacts and interdependency of care services. Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes. Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Expected measurable benefits
[45 paragraphs unchanged] All of the above lead to improved patient experience through more effective commissioning of services. Users of the same MedeAnalytics service have feedback that: Showing the number of benchmarked A&E admissions (and A&E attendances in the next analysis) from specific local geographical locations in a heat map, will enable the CCG and 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: - Deliver the best outcomes for their patients; - 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.
Unchanged: Benefits reported.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by NHS East and North Hertfordshire CCG
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Ltd, Optum Health Solutions (UK) Ltd and NHS East and North Hertfordshire CCG.
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics International Ltd's Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics International Ltd system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics International Ltd.
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors or the national data opt-out, as the records are no longer identifiable when they leave the protected NHS Digital environment.
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).
NHS England Wave 2 PHM project
NHS East and North Hertfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The Optum Health Solutions (UK) Ltd involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor the this project will be removed from this agreement by amendment.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for 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.
9. 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
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Analytic Insights
Reports, charts and dashboards providing insights into:
1) Comparators of CCG performance with similar CCG's as set out by a specific range of care quality and performance measure 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, including:
- Patients at highest risk of admission;
- Most expensive patients (top 15%);
- Frail and elderly;
- Patients that are currently in hospital;
- Patients with the most referrals to secondary care;
- Patients with the most emergency activity;
- Patients with the most expensive prescriptions;
- Patients recently moving from one care setting to another;
- Patients discharged from hospital;
- Patients discharged from the community.
5) Understanding impacts and interdependency of care services.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Benefits reported
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. In particular, the data will allow improved population segmentation analysis, including an analysis of activity and cost across multiple care settings, to support more targeted care and QIPP.
Invoice validation
The invoice validation process is undertaken on a monthly basis and now forms part of the CCG’s business as usual. This includes a monthly validation and reconciliation process to ensure that all payments are accurate and agreed with providers. In addition the information is used to monitor performance and produce in-depth analysis of areas of over or under performance.
Commissioning
A range of activity and financial reports are produced on a monthly or quarterly basis, including the following:
Local analysis has been undertaken to support the development of QIPP schemes where national benchmarking has identified areas where the CCG is an outlier, this includes opportunities identified through NHS RightCare. This local analysis has underpinned the development of new QIPP schemes for 2019/20.
The CCG has worked with the Herts County Council Public Health Intelligence team to produce national indicators at locality or GP practice level, where appropriate. This has included analysis by locality of avoidable emergency admissions.
Comprehensive analysis to support the commissioning and planning round for 2019/20 and ensuring consistency between provider contract plans and national activity and planning requirements. This includes identifying and understanding gaps where different definitions are used, for example local definitions for diagnostic tests and non-consultant led outpatient activity.
Regular performance and locality information packs produced to identify areas of under-performance and locality variations in activity rates and performance.
Practice level reports showing financial performance against budget produced on a monthly basis. Initial analysis to support population segmentation, including multiple long term conditions, across the CCG by GP practice and locality. This will be an on-going development to support the local population health management strategy.
DARS-NIC-55679-K9X4J-v3.2 1 October 2019 to 30 September 2022
- Title
- DSfC - NHS East and North Hertfordshire CCG - IV & Comm
- Commercial
- No
- Sublicensing
- No
- Datasets
- 27
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners; SUS for Commissioners
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation with be conducted by NHS East and North Hertfordshire CCG
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Ltd
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics International Ltd's Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics International Ltd system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics International Ltd.
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors, as the records are no longer identifiable when they leave the protected NHS Digital environment.
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 output
Invoice Validation
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
Commissioning
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for 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.
9. 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
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Benefits reported
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. In particular, the data will allow improved population segmentation analysis, including an analysis of activity and cost across multiple care settings, to support more targeted care and QIPP.
Invoice validation
The invoice validation process is undertaken on a monthly basis and now forms part of the CCG’s business as usual. This includes a monthly validation and reconciliation process to ensure that all payments are accurate and agreed with providers. In addition the information is used to monitor performance and produce in-depth analysis of areas of over or under performance.
Commissioning
A range of activity and financial reports are produced on a monthly or quarterly basis, including the following:
Local analysis has been undertaken to support the development of QIPP schemes where national benchmarking has identified areas where the CCG is an outlier, this includes opportunities identified through NHS RightCare. This local analysis has underpinned the development of new QIPP schemes for 2019/20.
The CCG has worked with the Herts County Council Public Health Intelligence team to produce national indicators at locality or GP practice level, where appropriate. This has included analysis by locality of avoidable emergency admissions.
Comprehensive analysis to support the commissioning and planning round for 2019/20 and ensuring consistency between provider contract plans and national activity and planning requirements. This includes identifying and understanding gaps where different definitions are used, for example local definitions for diagnostic tests and non-consultant led outpatient activity.
Regular performance and locality information packs produced to identify areas of under-performance and locality variations in activity rates and performance.
Practice level reports showing financial performance against budget produced on a monthly basis. Initial analysis to support population segmentation, including multiple long term conditions, across the CCG by GP practice and locality. This will be an on-going development to support the local population health management strategy.
Register history
When this agreement appeared in, or was edited in, each monthly edition of the register. Built by comparing every edition this site holds, the earliest of which is July 2021.
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July 2021 —
already listed in the earliest edition this site holds, so it may be older. 5 versions: DARS-NIC-55679-K9X4J-v3.2, DARS-NIC-55679-K9X4J-v4.3, DARS-NIC-55679-K9X4J-v5.4, DARS-NIC-55679-K9X4J-v6.2, DARS-NIC-55679-K9X4J-v7.2
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October 2022
Succeeded Applicant organisation: NHS East and North Hertfordshire CCG succeeded by NHS Hertfordshire and West Essex ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS East and North Hertfordshire CCG succeeded by NHS Hertfordshire and West Essex ICB from 1 July 2022, according to NHS ODS. Not counted as a change.
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December 2022
Register-wide edit DARS-NIC-55679-K9X4J-v3.2, DARS-NIC-55679-K9X4J-v4.3 — Datasets: legal basis: “
s261(1) and” taken out. Made to 639 agreements in this edition, so it is reported once, on the changes page, and not counted as an amendment of this agreement.
Cite this page
NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-55679-K9X4J, “DSfC - NHS East and North Hertfordshire CCG - IV & Comm”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-55679-k9x4j/ (accessed [date]).
This address stays the same, but the page is rebuilt with each monthly edition, so the citation names the edition it shows. Every edition's data is kept in the facts store.
Source: datausesregister_september2026.xlsx, September 2026 edition of the NHS England Data Uses Register. Search that workbook for DARS-NIC-55679-K9X4J to see the original rows.