Parallel Sessions: Pathways & Prediction Shaping the Future: Intelligence for Health and Social Care Integration A Gathering Parallel Sessions: Pathways & Prediction

Pathways & Prediction Background What’s Available What’s Next Pathways Risk Prediction Table Top Discussion Feedback and Questions

Pathways & Prediction Background

Local Intelligence Support Team How We Are Helping Now Source Local Intelligence Support Team Scottish Government funded initiatives Support Integration Authorities with Strategic Planning by; Providing data and analytical support Help to evaluate services, through providing evidence for change Help to transform data into evidence for action

£ Integrated Data CHI Partnership Access Via secure platform Linked Health and Social care file at an individual service user level (Aggregated Activity & Costs) Intermediate Care SIMD Outpatients A&E Deaths Inpatients Community Hospitals @ Home Day cases SPARRA Social Care Prescribing Housing and Homeless Age/gender Partnership Access Via secure platform £ Linked File 5

Pathways & Prediction What’s Available Now

Information Available Now High level Resource overview – expenditure by year, partnership, region and age group; benchmarking; trends Single dataset Inpatients and Day Cases, A&E, Social Care –expenditure by year, partnership, region, GP practice, specialty and age group (activity and costs) Linked High Resource Individuals, Long Term Conditions, Delayed Discharges , End of Life Care

Pathways & Prediction What’s Next

What’s Next Source Dashboards Other Data Sets Information Governance Social Care Community Health – District Nursing Locality based data Third and Independent Sector Other Data Sets Homelessness and Housing Intermediate Care Information Governance ISA Pathways and Prediction

What’s Next Supporting integration information needs across Scotland Joint Needs Assessment Current Service Utilisation Pathways & Prediction Scenario Planning Systems Dynamics LIST Mapping Source

My Hub

Pathways and Prediction Pathways & Prediction Pathways and Prediction

Partnerships to use these models to Pathways Aims Provide partnerships with models reflecting flow through and between H&SC services Number of people, measures of activity, costs and outcomes By population Partnerships to use these models to Evaluate current care pathways Establish alternative models Support engagement with service managers, clinicians etc Leading to changes in service models and (dis)investment decisions Monitor and evaluate impact of change

Process mining / ProM Process mining for knowledge discovery Compliance may come later Develop process models from admin/clinical data ProM: open source process mining platform Fuzzy miner For less structured processes Conflicting behaviours Avoid spaghetti models Use abstraction and aggregation techniques

Geriatric Pathway

Classification – Service use Tested clustering algorithms Black box; dependent on format of data in (not objective) Manual audit of records identified common types of service use Patient classified based on majority expenditure Potential for more detailed complex hierarchy

Classification – Population Consider key patient characteristics of age, living status, clinical complexity Bridges to Health model (Lynn et al. 2007; US Health Dept.) influential Separate population into groups of distinct health priorities and measures of optimisation Population segments must be limited to allow sensible integrated services to be developed for each Entire population included Segment populations should have sufficiently similar healthcare needs, but different enough from other segments Modified and applied in British Colombia in form of the Blue Matrix

Classification – Population Highest care needs Lowest care needs Towards last years of life Living with chronic conditions and disabilities Getting better Staying healthy End of Life Frailty High complex chronic conditions Maternity and healthy newborns Mental health Substance use Medium complex chronic conditions Low complex chronic conditions Child and youth non-chronic conditions Adult non-chronic conditions Healthy Non-user

Process mining development Apply wider range of populations to test robustness of fuzzy miner algorithm Evaluating process mining software solutions Seek to integrate with Source Home care, district nursing and other datasets will introduce further complexity as well as value Vary hospital detail as required Think about timeframe (12 months too short in some cases)

Integrate classification matrix within Source (using Tableau) Enabling use Partnership X Integrate classification matrix within Source (using Tableau) Seeking partners to pilot pathway mapping Pilot GP cluster tool

Predicting other outcomes Risk Prediction Modernise SPARRA New machine learning methods New national data Local models Focus on preventable admissions Predicting other outcomes Delayed discharge High resource users Care home admission

What’s Next Supporting integration information needs across Scotland Joint Needs Assessment Current Service Utilisation Pathways & Prediction Scenario Planning System Dynamic LIST Mapping Source

Pathways & Prediction Table top Discussion

Table top Discussion WHAT DO YOU THINK ABOUT THE POPULATION CLASSIFICATION AND PATHWAY DEVELOPMENTS? HOW WOULD YOU MAKE USE OF THE POPULATION CLASSIFICATION AND PATHWAY MAPPING OUTPUTS LOCALLY? WHAT ADDITIONAL DATA, STATISTICS, VISULISATION IS REQUIRED? ARE YOU ALREADY DEVELOPING PATHWAY ANALYSIS LOCALLY? IF YES HOW ARE YOU USING THIS LOCALLY? THE ISD HEALTH AND SOCIAL CARE TEAM ARE LOOKING TO WORK WITH PARTNERSHIPS TO FURTHER DEVELOP THE PATHWAY ANALYSIS. ARE YOU INTERESTED IN BEING A ‘PILOT’ SITE AND WORK WITH US? DO YOU HAVE ANY OTHER IDEAS OR SUGGESTIONS TO HELP INFORM THE PATHWAYS DEVELOPMENT?

Feedback and Questions Pathways & Prediction Feedback and Questions