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

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

3. Pathways & Prediction
Background

4. 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

5. £ 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

6. Pathways & Prediction
What’s Available Now

7. 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

8. Pathways & Prediction
What’s Next

9. 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

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

11. My Hub

12. Pathways and Prediction
Pathways & Prediction
Pathways
and Prediction

13. 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

14. 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

15. Geriatric Pathway

17. 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

18. 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

19. 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

20. 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)

21. 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

22. 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

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

24. Pathways & Prediction
Table top Discussion

25. 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?

26. Feedback and Questions
Pathways & Prediction
Feedback and Questions