Health plans are now measured on whether they act on their members' social needs, not just screen for them. Screening is the easy half. This report models where the harder half breaks down, and how a neighborhood coffee network gives a plan a concrete, trackable place to intervene.
Every step from screening to a documented intervention loses people. The measure, and the money, lives at the bottom of the funnel, exactly where open-loop referrals break down. The lighter bars model what a ready intervention destination recovers.
Modeled and illustrative. Hover any stage for its counts.
Not every quality measure is in reach of a coffee shop. These are the ones where social connection is a plausible, literature-backed lever. The projected point gains are modeled and directional; the pilot exists to size them for real.
SNS-E screens food, housing, and transportation. Social isolation, which the U.S. Surgeon General called an epidemic, isn't its own screened domain yet, and its Z-codes (living alone, lack of social support) are documented on around 1% of encounters.
So plans have a recognized need, growing pressure to address it, and no off-the-shelf intervention built for it. That gap is the opportunity: Double Cup is a low-cost, community-based destination purpose-built for connection, that logs what it does.
A referral only counts if the plan can see it happened. Double Cup is designed to complete the loop, turning a positive screen into a logged, documentable intervention the measure can credit.
This is the difference between a resource list and an intervention: the plan can watch the 30-day window close. Documentation is aggregate and consented. The Club recognizes generosity and participation, never a diagnosis.
The metrics above only mean something if the capture is real. Three tiers, ordered by how much cooperation each needs: what Double Cup logs itself, what it attributes through a referral exchange, and what only the plan's claims can confirm.
Every Connector check-in and Double Cup redemption is a timestamped, consented participation event. That event is the intervention record: proof a social-need signal was acted on, exportable to the plan's care system.
The Connector's structured note attaches the specific driver. A Z-code needs a documented risk or unmet need, not merely the circumstance, which the note is designed to supply.
So the plan's care team can document and bill the outreach that routed the member here. The PIN codes explicitly cover behavioral-health conditions.
Standards-based, so it reads as interoperable data to a plan rather than a bespoke feed.
Two directions: where a member came from, and where the Connector sends them onward. Both are captured with shared identifiers, so nothing rests on memory or self-report.
Each channel issues its own signed short-code or link, recorded on enrollment and every redemption. Every participant carries who sent them.
The Connector's "refer onward" opens a referral the receiving org acknowledges and closes, over a community information exchange. This confirms the handoff; the kept clinical visit is confirmed in Tier 3.
A consented match of plan member ID to Double Cup participant ID. This single link is what makes Tier 3 possible; without it, nothing connects to outcomes.
The only tier that can see a BH clinic visit or a utilization change. Claims never flow into Double Cup. Double Cup sends exposure only, and the plan matches it against its own claims in a governed environment.
Nothing clinical: only who was exposed and when.
Index date = a member's first Double Cup intervention. Exposed members are compared to a propensity-matched cohort the plan pulls, or to the stepped-wedge rollout of the pilot itself. Reporting stays aggregate and de-identified under a BAA / limited data set.
Read top to bottom, this is also a build order. Tiers 1 and 2 are process metrics a pilot can stand up on day one. Tier 3 is the outcome question, and standing up its consent flow and data-sharing agreement is the pilot's real job, which is why every outcome figure in this report is still labeled modeled.
The same data that flags who to screen also shows where the referable, equity-weighted population concentrates, and therefore where a Connector shop earns its keep. Both views below are illustrative, modeled on a Minnesota-shaped cohort.
A Claude-powered API earns its place in the parts of this system that turn on language and judgment, and stays out of the parts that must be auditable or private. That discipline is the point.
Unstructured text into structure, real-time Connector guidance, referral reasoning, and plain-language synthesis. Language and judgment, always with a human in the loop.
Risk scoring, dormancy prediction, and outcome attribution. Calibrated, auditable, and owned separately, so a number a plan audits is never "the AI decided."
A Claude assistant inside the Connector's app that turns the "notice, invite, refer" training into live support during a real interaction. It works from the public local-resource directory and only what the Connector chooses to share in the moment, never the member's record.
Converts a Connector's free-text note into the Z-codes, service codes, and FHIR resources from Panel 04, with a human confirming. Zero-retention: nothing stored or trained on.
Reasons over a messy, non-uniform resource graph to rank the best clinic or service for an expressed need, with rationale, feeding the closed-loop referral in Tier 2.
Writes the coffee-shop, sponsor, and health-plan narrative on top of the aggregate dashboards, refreshed on demand. A human signs off before anything reaches a payer.
Kept clear of PHI by design. The intelligence layer works from the public resource directory, de-identified aggregates, and what a Connector shares in the moment. It never touches the identity crosswalk or the plan's claims; Tier 3 stays in a governed environment with no model access, and where any member text is processed it runs under a zero-retention BAA with a human confirming the output. The auditable risk and attribution models stay separate, so "the AI decided" never enters a payer conversation.