1. Enhanced SPARRA Predictive Model & SPARRA Patient Alerts Risk prediction and service development Kathleen McGuire – Long Term Conditions Manager Ehealth LTC Workshop November 2011

2. Aim Integrated systems and communications Expand the cohort of patients for whom a risk score can be calculated over and above the current SPARRA “All Ages” (Version 2) algorithm Improve the predictive power of the algorithm Provide the board with a risk prediction tool which will identify patients for referral to Community Wards

3. Scope Feasibility of a model which included GP/Primary Care, Social Care, Accident and Emergency and Prescribing data. Any other potentially useful sources which may serve as a predictor for emergency hospitalisation, including falls and IoRN. Producing a linked data set Improved data links to and from Primary and Secondary Care

4. Deliverables Data extract specification Predictive risk model (with technical report and recommendations) Reporting and implementation scoping requirements (report) Prototype reporting tool (with user manual) Final report (with conclusions and recommendations) Post project evaluation (report )

5. Lessons learned will inform the national development of SPARRA, predictive risk modelling, related tools GP SCI Gateway referral message integrated into ADASTRA

6. How we have taken forward Appointed a Data Analyst Appointed a Project Manager Gained strategic organisational commitment- eHealth programme Gained buy in by utilising other national SPARRA developments & improvements Integrated the project with service development of Community Hubs Expansion of current LES

7. SPARRA Prediction & Tools SPARRA Accident & Emergency Patients/Carers Social Services Nursing Homes ADOC LOTS LES Information Tool Navigator I SPARRA

8. Community Hubs HUB SECONDARY CARE CARERS (Kinship / Professional) SOCIAL SERVICES Chronically ill Patient Acutely ill Patient Multiple/Complex Social-needs Patient Enhanced SPARRA CPM PRIMARY CARE TEAM Intermediate Care & Enablement Teams AHPs Pharmacy OT Specialist Nurse Geriatric ANPs Community Wards Social Care Liaison Practice Nurse District Nurse SPOCSPOC GP AYRSHIRE HOSPICE ADOC NHS 24

9. What we have learned so far Project needs to be integrated with other development Requires stakeholder buy in Differing views around data specification Quality and coding of data Informed consent and data sharing

10. What we have learned so far Time, expertise and partnership required IT systems used in out of hours setting suffer from poor demographics and duplicates Integrating Primary Care systems with the out of hours service requires a primary data cleansing task

11. Our wish To use the principles of risk adjustment to evaluate the pathways of complex community- based interventions to reduce avoidable hospitalisation, eg testing the cost effectiveness of Community Wards and Telehealth To link large datasets at an individual level pseudonymously through our partnership arrangements and relationships Predict future costs of health and social care

12. Our wish To exploit new Clinical Portal technology to help distribute electronic information to the point of care. Successful procurement of a new community wide IT system (currently in progress) to support collection of data and distribution.

13. Requirements & Next Steps National Support and continuation CHI Seeding, time & expertise Integrated IT systems within and across organisations Go live with model 1 st April Extend roll out and testing of CPM Further integrate SPARRA & IRF