Guía del evaluador
Todos en este mercado dicen ser los mejores. Casi nadie define la medida. Esta página lo hace: cinco preguntas que separan un sistema clínico de una demo — las mismas cinco que un hospital, un pagador o un ministerio puede plantear a cualquier proveedor, incluidos nosotros.
Por qué «el mejor» suena hueco
Las clasificaciones se ganan con preguntas estáticas de examen — viñetas limpias, una única respuesta correcta, cero consecuencias. La medicina desplegada es interrumpida, ambigua y sujeta a responsabilidad. El argumento, con datos: WP-002, The Flawed Yardstick (EN).
Un modelo «acertado en el 95 % de media» que se equivoca con seguridad en una disección aórtica no es un sistema del 95 % — es un riesgo legal. Lo que cuenta: el peor caso de falsedad afirmada con confianza — y casi ningún proveedor da esa cifra.
Una demo responde preguntas. Un sistema carga con responsabilidad: inicia sesión en el EHR, reescribe bajo la firma del médico, sobrevive a la caída de la red y deja una pista de auditoría utilizable ante un tribunal.
La medida
Purchasing checklist
The market is flooded with transcription tools claiming to be clinical AI. Before integrating any system into your workflow, ask the vendor these four questions.
What happens when the microphone misses a critical word? Standard LLM-based scribes are probabilistic—they predict the most likely next word, meaning they will confidently invent a clinical finding rather than admit they missed it. DeepSensi is deterministic under uncertainty. The LIMBO protocol forces the system to declare 'I don't know' and flag the missing variable. Ask the vendor for their formally derived worst-case bound on confidently asserted falsehoods. If they answer with an 'average accuracy score', they do not have a safety bound.
Do you store patient data, and is privacy guaranteed by architecture or just by policy? A signed BAA is a legal shield for the vendor, not a technical safeguard for your patients. DeepSensi operates on a Zero-PHI architecture. Personal identifiers are stripped at the edge before any reasoning occurs. We do not need your patients' names to diagnose them. Ensure your vendor enforces privacy mathematically in their code, not just in their terms of service.
Does your system just take notes, or does it actively defend my license? An AI scribe that merely transcribes audio is a missed opportunity. DeepSensi’s ACS Scribe listens to the encounter and simultaneously runs a real-time, 37-specialist Differential Diagnosis (DDx) in the background. It doesn't just write the SOAP note; it highlights the one critical diagnosis you might be missing and calculates a SIL-4-grade confidence score, acting as an active clinical safety net.
If the AI makes an error, who takes the blame? Today, the answer is always the physician. DeepSensi alters this reality by providing a court-grade, cryptographically sealed evidentiary ledger for every single assertion the system makes. You can point to the exact node, rule, or piece of evidence that led to a conclusion. Ask your scribe vendor if their system provides a tamper-evident audit trail that you could take to court.
FAQ
Doctrina: publicamos la prueba, el estándar y la auditoría. No publicamos el plano. Documentación científica en inglés; atendemos consultas en español.