
The Missing Million helps social prescribers identify early signs of isolation among older adults — before crisis point — using weak signals already held across care and community systems.
"The people most at risk are often the least visible."
The problem
A missed appointment. A bereavement quietly noted in one system. A prescription left unfilled. Each looks ordinary on its own. Together they describe a person slipping out of view — months before anyone is alerted.
Older adults in England report often feeling lonely
Age UK, 2024
Higher mortality risk associated with chronic isolation
Holt-Lunstad meta-analysis
Average gap between first weak signal and care system flag
Lambeth pilot data
Of cases where prescription gaps preceded social withdrawal
The Missing Million model
How The Missing Million works
The Missing Million reads weak signals already held across primary care, community and council systems — missed appointments, bereavement, living alone, reduced prescription pickup, declining engagement.
Transparent, explainable risk scoring surfaces residents most likely to disengage — with every contributing factor visible and traceable to its source.
Outreach guidance helps social prescribers make earlier, more sensitive human contact — informed by context, never replacing judgement.
A glance inside
The Missing Million is built for the rhythm of real outreach work. A single clear priority list. Explainable scores. Sensitivity guidance for first contact. No alarms. No noise.
Launch the appTrust & ethics
The Missing Million supports human judgement. It does not replace it. Every score is explainable, every signal traceable, every outreach decision made by a person.
Every recommendation is reviewed by a social prescriber before any action is taken.
Each risk score breaks down into named, weighted factors traceable to their data source.
No data leaves your network. No external sharing. No third-party model training.
The Missing Million prioritises outreach. It makes no clinical judgement and replaces no clinical pathway.
Practitioners can dismiss, deprioritise or annotate any flag — and the system learns from it.
Opt-out by default for excluded categories. Bias audits on every model release.
Outcomes