Better Care Fund Series 1 — Article 3 of 3

VCSE Commissioning Analytics Series — Article 7 of 18 | Better Care Fund Series 1 — Article 3 of 3

Step 1: Map Your Service to the BCF Metric It Affects | Better Care Fund Series 1 — Article 3 of 3

Better Care Fund VCSE data analytics is the structured approach to collecting, connecting, and presenting evidence that demonstrates a VCSE organisation contribution to the BCF three headline metrics in a form that local authority commissioners, ICBs, and Health and Wellbeing Boards can use as credible performance evidence.

The starting point for any BCF data strategy is a precise mapping of the service to the specific headline metric it affects. A falls prevention programme primarily affects non-elective admissions (metric one), but it also affects long-term care admissions (metric three) by maintaining older adults physical confidence and independence at home. A hospital discharge support service primarily affects delayed discharges (metric two), but successful discharge to home also contributes to metric three. A carers support service primarily affects metric three by enabling informal carers to sustain their caring role, but also indirectly reduces the carer own risk of emergency admission.

Understanding this mapping is essential because it determines which data you need to collect, which benchmarks you compare against, and which local goals you frame your evidence around. Ask the commissioning local authority or ICB which BCF metric their HWB has set goals against for the service area your VCSE operates in.

Step 2: Build Longitudinal Tracking for Every Service User

BCF outcomes evidence cannot be produced from point-in-time data. All three headline metrics require evidence about what happened to people over time — whether admissions were avoided, whether discharge was sustained without re-admission, whether independence was maintained in the community for six or twelve months. This requires longitudinal individual tracking from the moment of referral through to a defined follow-up period after closure.

The longitudinal tracking infrastructure for a VCSE BCF evidence system records, at minimum: the date of referral and referral source; the date of first contact; baseline assessment data including relevant wellbeing, independence, or falls risk scores at point of intake; the dates and content of each service contact; outcome assessment data at defined follow-up intervals; the closure date and reason; and whether the person experienced a hospital admission, residential care placement, or significant deterioration event during or after the service period.

Charitylog and Lamplight both support this level of longitudinal data capture, but the fields need to be specifically configured to the BCF evidence requirements rather than left as default setup. Quematics conducts a data configuration audit as part of every BCF analytics project to ensure the source system is capturing everything the evidence strategy requires.

Step 3: Choose Validated Outcome Measures Aligned to BCF Domains

Validated outcome measures are the evidence backbone of BCF reporting because they provide quantified, comparable data that commissioners can benchmark against other providers and against population norms. For BCF evidence, the most relevant validated measures are those that capture independence, wellbeing, and functional capacity over time.

For VCSEs working with older adults, the most useful measures include: the EQ-5D for health-related quality of life, which is used across NHS and social care settings; WEMWBS for mental wellbeing, particularly relevant for carers services and social prescribing; the Barthel Index or the Falls Risk Assessment Tool (FRAT) for physical function and falls risk; and the Caregiver Strain Index for carers services. Agreement with the commissioner on which measure to use should happen at contract design stage, so that baseline and follow-up data collection is built into service delivery from the outset.

Step 4: Build the Analytical Layer That Turns Data into BCF Evidence

Once longitudinal tracking and validated outcome measurement are in place, the analytical layer transforms this raw data into BCF-quality evidence. The three key analytical outputs are population comparison, trend analysis, and service pathway evidence.

Population comparison answers the question: do the people your service supports have better outcomes than equivalent people who did not receive your service? Trend analysis answers the question: are outcomes improving over time as the service matures? A Power BI dashboard showing outcome score change over four or six rolling quarters is far more compelling BCF evidence than a single-period outcome report. Service pathway evidence answers the question: does your service connect well to the rest of the system? This includes referral source data demonstrating integration, waiting time data demonstrating responsive access, and onward referral data demonstrating appropriate step-up or step-down coordination.

Frequently Asked Questions

What is a BCF data strategy for VCSEs?

A BCF data strategy for VCSEs is the structured plan for collecting, connecting, and presenting evidence of a VCSE contribution to Better Care Fund headline metrics in a form that commissioners and Health and Wellbeing Boards can use as credible performance evidence.

What validated outcome measures work best for BCF evidence?

The most useful validated measures include EQ-5D for health-related quality of life, WEMWBS for mental wellbeing, the Barthel Index or FRAT for physical function and falls risk, and the Caregiver Strain Index for carers services. The choice should be agreed with the commissioner at contract design stage.

How do VCSEs produce population comparison evidence for BCF reporting?

Population comparison uses published NHS England or DHSC population health benchmarks, or data linkage with the ICB or local authority where data sharing agreements are in place, to show whether VCSE service users have better outcomes than equivalent population groups.

How long should VCSEs track service users after closure for BCF evidence?

BCF outcomes evidence is strongest when it covers at least six months post-closure. For services affecting long-term care admissions, twelve-month follow-up tracking is the most credible evidence standard. The specific follow-up period should be agreed in the contract schedule.

How does Quematics build BCF analytics for VCSEs?

As part of our VCSE commissioning analytics service, Quematics audits and configures the VCSE case management system for BCF evidence requirements, connects it to a Power BI analytics layer, and builds population comparison and trend analysis outputs that translate service user data into BCF-quality evidence reports.

To discuss how Quematics can build a BCF data strategy and analytics infrastructure for your VCSE, visit our data analytics for charities page or our Power BI consultancy page, or contact us for a free 30-minute data review.