# Dascena

**Canonical:** https://apis.io/providers/dascena/  
**Website:** https://forgeglobal.com/dascena_stock/  
**APIs profiled:** 0

Dascena was an Oakland, California health-technology company that built machine-learning diagnostic and clinical decision support algorithms for hospitals, most notably InSight, a sepsis prediction model that scored electronic health record vitals and labs in real time to flag patients at risk hours before onset, plus FDA breakthrough-designated models for acute kidney injury and gastrointestinal bleeding. The algorithms were delivered as an embedded integration inside a customer hospital's EHR under a services and laboratory agreement rather than as a public developer API, so the company never operated a developer portal, published a machine-readable contract, or shipped client SDKs. CirrusDx acquired the Dascena Labs laboratory business effective 5 August 2022 and the company identity now trades as DBA CirrusDx; the dascena.com domain no longer resolves.

## Kin Score — 3.9 / 100 (minimal)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 3.9).

| Facet | Score |
|---|---|
| Discoverability | 46.3 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 0.0 |

Regulatory layer — **Health**: 0.0 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Tags

Company, Health Care, Artificial Intelligence, Machine Learning, Diagnostics, Clinical Decision Support, Sepsis, Acquired

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/dascena/). Scores are computed from the provider's own public artifacts under a published rubric.