Found (Found Health)

Found (Found Health) — A longitudinal real-world obesity-treatment cohort with linked behavioral engagement telemetry and clinically validated outcomes — the byproduct of operating a subscription weight-loss clinic rather than a collected study. Each member accrues a self-logged weight and BMI time series, habit and behavior-logging events, provider and health-coach check-in cadence, community-group participation, and educational-content exposure, all joined to a medication record covering which agent was prescribed, dose-escalation trajectory over time, tolerability and continuation. The pub…

Found (Found Health) offers (Alternative, Fundamental, Reference) — 66,094 members in the analyzed cohort alone, each contributing a multi-point outcome series at 3, 6 and 12 months plus irregular self-logged weight entries, habit and engagement events, encounters and a dose-escalation record; the cumulative base of 250,000+ members implies a panel several times larger than the published cohort. Because weight is self-logged on a near-daily cadence for engaged members, event volume is far larger than member count — plausibly tens of millions of logged observations, though the company does not publish an event count..

Real-world evidence for obesity drug effectiveness and persistence outside trial populations, the single most requested and least available evidence class in the GLP-1 market; GLP-1 discontinuation and adherence forecasting, since payers face enormous ongoing spend and the biggest open question is who stays on therapy; comparative-effectiveness work across agent classes, supported by the finding that non-GLP-1 medications also drove significant loss; payer coverage-policy, step-therapy and prior-authorization design with outcomes-based criteria; weight-regain and maintenance modeling, which the company identifies as the hard problem; combination-therapy design quantifying the marginal value of behavioral support on top of pharmacotherapy, valuable to manufacturers and digital-health competitors; obesity-medicine trial recruitment and control-arm enrichment, given a large characterized cohort with known response patterns; and consumer-health model training, where continuous self-logged weight series joined to engagement events is a rare labeled time-series corpus.