1. Information Sharing: Understanding Your Requirements Mark Golledge Programme Lead – Health and Care Informatics Local Government Association Monday 19 th January 2014

2. Outline 1.Background 2.Definitions & Terminology 3.Purposes and Benefits 4.Data Sets and Data Requirements 5.Group Activity Caldicott Principles Justify the purpose(s) Don’t use personal confidential data unless it is absolutely necessary Use the minimum necessary personal confidential data Access to personal confidential data should be on a strict need-to-know basis Everyone with access to personal confidential data should be aware of their responsibilities Comply with the law The duty to share information can be important as the duty to protect patient confidentiality

3. Some caveats… We have 30 minutes – this is not going to be enough time to cover the level of detail we want to. Therefore to supplement this we will be making available a more detailed report for you to review and edit post this event; The presentation is based on the pro-forma DH received from localities and follow up conversations – WELC, South Tyneside, Leeds, NW London, Greenwich, Central Cheshire, Worcestershire, York City (Monitor work), Liverpool (Monitor work) and Manchester (Monitor work); As you’d expect the purposes / approaches are not identical for each locality. We want to test our understanding and your commonality and therefore think about practically how we help move this forward; One caveat that we know this presentation will not be 100% accurate – part of what we will be doing in the group sessions is testing this against your requirements; Finally, part of today is also about helping explore alternative solutions – Section 251 is only one approach. The afternoon discussions will hopefully challenge some of your / our thinking about what is available;

4. Definitions Overarching Purposes (specific purposes within these are covered on the next slide): 1.Population Segmentation: The grouping of the population into specified categories. This may be into what kind of care they receive, how much it costs and how often they may need it. 4 different approaches to population segmentation: a). Utilisation Risk (Risk Stratification for Commissioning) – the grouping of the population based on how likely they are to receive services (using predictive models); b). Age and Condition – the grouping of the population generally based on age and then by condition (often the preferred route for international integrated care); c). Social and Demographic Factors d). Behaviour 2.Risk Stratification for Case Finding: The targeting of specific high risk individuals in need of preventative care interventions, such as the support of a multi-disciplinary team (not direct care as it will not be all individuals in need of preventative care or treatment); 3.Caseload Matching: The matching of caseloads (not individual by individual) between Integrated Care Teams to support the delivery of integrated care; 4.Electronic Care Record Linkage: The linkage (not transfer) of electronic care records across care settings to support care by Practitioners (“Integrated Digital Care Records”);

5. Purposes and Benefits PurposeDefinitionBenefit 1. Population Segmentation: By utilisation Risk, Age and Condition, Social & Demographic, Behaviour a. Create population segmentation models across registered and resident population that identify care needs for local population groups Grouping of the population into groups depending on conditions, disease profiles or service usage as well as lifestyle factors (e.g. deprivation, smoking) which also enhances the understanding of cost. Supports strategic planning and service planning activity including the Joint Strategic Needs Assessment enabling system wide commissioning. Also helps to understand what differentiates groups. b. Develop and manage (via invoice validation) new payment approaches across health & social care (e.g. capitated budgets, year of care) Development of new payment mechanisms that pay providers for the majority / all care for a target population or particular condition. Based on costing a care pathways and aggregating them. Includes invoice validation & passing of specific details to providers / prime provider Patients should benefit from receiving better coordinated care as it incentivises providers to work together in innovative ways delivering better value for money. c. Conduct evaluation of the effectiveness and utilisation of integration delivery by providers Assess the impact of integrated care against a range of metrics monitoring the changes in the system. This helps understand interventions relative to future outcomes. May include patient feedback (this aspect: consent). Assesses whether the commissioned services are having the desired effect – monitoring outcomes.

6. Purposes and Benefits PurposeDefinitionBenefit 1. Population Segmentation: By utilisation Risk, Age and Condition, Social & Demographic, Behaviour d. Map the density of pathologies, impairments, functions, services or events across a locality (not yet covered by Southend app) Undertaking visual mapping across a specified locality to understand the density of specific conditions, care needs or lifestyle factors. Enables a focus of commissioning on particular areas delivering enhanced value for money or understanding wider implications on conditions etc. (for example housing condition). e. Monitoring outcomes for particular cohorts: care home residents (not covered by Southend app) Address matching to identify care home residents who have greater needs than peers in their own homes. This would typically assess care home stays and outcomes. Enables effective care given to those in a particular care setting – through analysis of patterns such as emergency healthcare access rates, utilisation of services & mortality rates. f. Monitoring outcomes for particular services: hospital mortality (not covered by Southend app) Linking of hospital (acute) and mortality data to better understand the links between service delivery and mortality. Enables assessment of service delivery of providers and considers what can be done to reduce levels of mortality.

7. Purposes and Benefits PurposeDefinitionBenefit 2. Risk Stratification for Case Finding a. Identify high risk / cost individuals whose care may need to be reviewed by an MDT Targeting high risk individuals in need of preventative care interventions (direct care starts after re-identification – qualified social workers). Enables a focus on particularly high cost / high risk patients so that a joined up approach can be taken to their care. 3. Caseload Matching (not covered by Southend application) a. Caseload Matching: Integrated Teams The matching of caseloads to allow an integrated response to care delivery. This is specifically to support care coordination and case management. Is this not the same as risk stratification for case finding or are we assuming not an MDT & qualified social workers? 4. Electronic Care Record Linkage (not transfer) (not covered by Southend application) a. Integrated Digital Care Records (not directly commissioning) Sharing of electronic records across multiple care settings to support joined up patient care by practitioners. Generally undertaken using middle- ware that draws key information from records into a single portal. Enables practitioners to make a holistic assessment based on knowledge of care and treatment provided across settings. Typically this will also allow patients to make decisions about their care via care planning & patient portals.

8. Questions for you to consider…. We will come back to these questions at the end but for you to consider: 1.Have we missed any specific purposes relevant for you? 2.Have we described these purposes in the right way – have we been specific enough? 3.Have we grouped these purposes appropriately? 4.Is the terminology correct – is there a common understanding here? 5.Are the purposes appropriately justified – have we described the benefits appropriately?

9. Data Sets and Data Requirements Required Data Sets and Identifiers Please note specific fields / exclusions within these datasets has not been covered here (this will need to be followed up on separately – some of the returns made include this). Please note this excludes PDS matching in a Local Authority for Social Care Data (this activity is presumed to have been undertaken where social care data is being used. *covered by Southend application (dataset) Purpose / Uses Datasets Required Identifiers Required by Processor Identifiers Required by “Restricted Users” Identifiers used in published output 1a. Create population segmentation models that identify care needs for local population groups Primary care dataset* SUS dataset* Adult Social Care dataset* MHMDS dataset Community dataset CHC (local) Ambulance (local) OOH (local) NHS Number (or common pseudonymn for linkage) Gender Ethnicity Identifiers changed: DoB to age Postcode to LSOA Gender Ethnicity Identifiers changed: Common pseudonymn DoB to age Postcode to LSOA Published at aggregated level without identifiers 1b. Develop and manage payment approaches across health and social care Primary care dataset* SUS (Acute) dataset* Adult Social Care dataset* MHMDS dataset Community dataset CHC (local) NHS Number Identifiers changed: DoB to age Postcode to LSOA NHS Number (for invoice validation purposes & to pass onto prime provider / providers) Identifiers changed: DoB to age Postcode to LSOA Outputs published at an aggregated level For invoice validation purposes NHS number required to ensure care isn’t paid for twice

10. Data Sets and Data Requirements Purpose / UsesDatasets Required Identifiers Required by Processor Identifiers Required by “Restricted Users” Identifiers used in published output 1c. Conduct evaluation of integrated delivery by providers Primary care dataset* SUS dataset* Adult Social Care dataset* MHMDS dataset Community dataset CHC (local) NHS Number (or common pseudonymn for linkage) Gender Ethnicity Identifiers changed: DoB to age Postcode to LSOA Gender Ethnicity Identifiers changed: Common pseudonymn DoB to age Postcode to LSOA Published at aggregated level without identifiers 1d. Map the density of pathologies, impairments, functions, services or events across a locality GP dataset SUS dataset Adult Social Care dataset Identifiers changed: DoB to age Postcode to LSOA Identifiers changed: DoB to age Postcode to LSOA Published at aggregated level without identifiers 1e. Monitor outcomes for particular cohorts – care home residents & children in care Adult Social Care dataset (care home) Children in Care dataset SUS dataset Full address: residential & nursing home Identifiers changed: DoB to age NHS Number (or common pseudonymn for linkage) Full address: residential & nursing home Identifiers changed: DoB to age (or common pseudonymn for linkage) Published at aggregated level without identifiers (but small number limitations) 1f. Monitor outcomes for particular services – hospital mortality SUS dataset Mortality dataset NHS Number (or common pseudonymn for linkage) Identifiers changed: Age, Postcode to LSOA Identifiers changed: Common pseudonymn Age Postcode to LSOA Published at aggregated level without identifiers

11. Data Sets and Data Requirements Purpose / UsesDatasets Required Identifiers Required by Processor Identifiers Required by “Restricted Users” Identifiers used in published output 2a. Identify high risk / high cost individuals whose care may need to be reviewed by an MDT (Nb: Social care staff never see health records without consent) Primary care dataset* SUS dataset* Adult Social Care dataset* MHMDS dataset Community dataset CHC (local) NHS Number Social Service User ID Local Service Provider ID Gender Ethnicity Identifiers changed: DoB to age Postcode to LSOA Restricted user here means MDT: NHS Number Social Service User ID Local Service Provider ID Gender Ethnicity Identifiers changed: DoB to age Postcode to LSOA Not applicable 3a. Caseload matching: Integrated Care Teams Primary care dataset SUS dataset Adult Social Care dataset MHMDS dataset Community dataset CHC (local) NHS Number (or common pseudonymn for linkage) Gender Ethnicity Identifiers changed: DoB to age Postcode to LSOA Gender Ethnicity Identifiers changed: Common pseudonymn DoB to age Postcode to LSOA ?? How is it being used – is this MDTs? 4a. Integrated Digital Care Records Not covered here – to be picked up by Integrated Digital Care Record (IDCR) Work-Stream

12. Questions for you to consider…. We will come back to these questions at the end but for you to consider: 1.Are the datasets identified needed for the activity being carried out – can we justify their inclusion? Are there any critical datasets missing or are there any that can be removed? 2.Are the identifiers required by the data processor the correct ones – can we justify their inclusion and are we minimising them appropriately? 3.Are the identifiers required by the “Restricted User” (by which we mean those who have limited access) the right ones? 4.Are the identifiers to be used in the published outputs the right ones? 5.Extraction period?

13. Group Activities What we want you to do in each of your groups: 1.Work through each of the purposes that have been defined and answer the first block of questions relating to purposes; Please mark which Pioneer site this is relevant to (we want to understand whether or not these purposes are common) 2. For each of the purposes you have specified, work through the second block of questions relating to datasets; Please mark which Pioneer site this is relevant to (we want to understand whether or not these purposes are common) We will amend and circulate these slides based on discussions today.

14. Appendix: A reminder….. Datasets specified in Risk Stratification Section 251: GP data SUS data Does not include social care data unless there is a legal basis Datasets specified in Commissioning Section 251 (but only to Stage 1 Accredited Safe Havens): Admitted Patient Care Elective Admission List Outpatients Future Outpatients Accident & Emergency Community Care Commissioning data sets (SUS or HES) Payment by Results data sets from SUS Independent sector activity Breastfeeding at delivery status National Cancer Waiting Times Paediatric critical care data set Pathology data set Radiology data set ASI measures for stroke treatment Referrals data Choose and Book referrals data National and Local Ambulance Data Sets Urgent Care Data Sets (inc walk-in centres, out of hours, Ambulance) Community Health data set Continuing Healthcare data set Home equipment loans Chronic Disease self-management programme