Dataset: Dead mental health startups, 2000-2026, coded on 18 fields
A new open-source dataset tracks 542 digital mental health startups that failed between 2000 and 2026. The data is categorized by business model, funding, and the specific reasons for each company's closure.
Why it matters
This dataset provides valuable insights into the viability of digital health business models and the challenges of scaling mental health technology.
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542 digital mental health organizations that left the market between 2000 and 2026 — shutdowns, bankruptcies, acquisitions, pivots and consolidations. Each coded on up to 18 fields: business model, who actually pays, funding raised, reason for leaving, clinical evidence, medical co-founder, revenue model, exit size, country, years of operation.
On top of that, four independent classification axes: what the product is ( product_type ), what kind of organization it was ( entity_type ), whether it replaced a clinician or wrapped around one ( care_mode ), and whether a human clinician was in the loop.
And one field that is not a category at all — key_mistake , a paragraph on what actually killed each company.
Every share in the report is computed from these rows. A worked example:
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