1. Making the Financial Case for Navigators
Ian Wilson
WY-FI Learning Event
27th April 2017

2. Purpose of this strand of work
Test and quantify how WY-FI has led to reduced cost to the public purse by preventing unplanned use of services such as A&E or frequent arrest/ trial
Central to securing commissioning and system change so that multiple needs can be met in a co-ordinated way
Follows a Cost Benefit Analysis framework: comparison of costs and benefits (cost savings to the public purse)
Four stages:
individual service user analysis (last year)
cohort analysis (this year)
building up the evidence base (ongoing)
understanding savings (next year onwards)

3. Individual service user analysis
Sampling – 30 service users with different levels of: risk, WYFI time and Homelessness Star and Chaos Index scores
Detailed journey mapping of actual service costs before and after:
12 months before notification
case finding
pre-navigation
12 months in navigator caseload
Apply to comprehensive service user level information on: inputs, activity, outcome change and service use

4. Individual service user analysis: an example

5. Cohort analysis
Detailed service use data by 345 WY-FI beneficiaries in their first year on the project
Considered 18 areas of service use. Includes CJS, NHS, Police, LA, Landlords
Calculate savings to the public purse = usage X unit costs (from the Cabinet Office/New Economy Cost Calculator database)
Scaled up savings to show the results for all 1,050 of WY-FI beneficiaries – bearing in mind that the savings to the public purse shown are only for one year’s worth of engagement for each of them.

6. Cohort analysis: headline results by event type
£9.846 million
savings per
annum
based on
1,050 service
users

7. Cohort analysis: differences by area
LA cost savings vary by number of service users, initial service use and change (reduction) in service use
Leeds has largest reductions (26 per cent of total) but also accounts for the largest number of service users (26 per cent)
Relative to its numbers of service users Kirklees had largest cost savings - large reductions in Inpatient
Calderdale and Wakefield had relatively lower cost savings - service users had 'relatively' lower service usage in baseline period

8. Next Steps Continue to build the evidence base:
detailed data for more service users
longer time horizon - up to 4 years
Exploratory analysis to understand difference and what works for whom:
by local authority
by activity
relating progression on Chaos index and HOS

9. Discussion
Do these savings match your experience on the ground? Are we missing anything?
What can help us to understand where the largest savings can be made?
How can funds be redistributed within the system to support continuation?