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Projeto urgente

Clinical AI assistant for chat-based telemedicine

28/02/2026 às 09:12

Descrição do Projeto:

Clinical AI Assistant for Chat-Based Telemedicine (Human-in-the-loop)

Context
We are a telemedicine provider running chat-based clinical appointments (including mental health/psychiatry). We want to build a clinician-assist AI workflow powered by the OpenAI API to improve speed, consistency, and documentation quality — while preserving physician oversight and strong privacy controls.

1) Objective

Build an AI assistant that supports clinicians during chat appointments by:

• collecting structured information (intake / triage / anamnesis),

• producing clinician-facing summaries,

• drafting patient-facing explanations and follow-up instructions,

• drafting a structured clinical note / medical record,

• routing emergencies / red flags appropriately.

Key principle: This is decision-support, not autonomous care. The clinician must explicitly approve critical steps and any patient-facing medical guidance.

2) Non-Negotiable Requirements

A) Human-in-the-loop “stage gating”

Implement the appointment workflow as a state machine with explicit clinician approval gates:

• The assistant must never advance stages automatically.

• Only clinician actions (button click / clinician-only command) move the workflow forward.

• Patient messages must never authorize progression.

B) 3-phase workflow (high level)

We use a three-phase structure (details shared after NDA):

• Triage support — generate a small set of targeted follow-up questions

• Clinical analysis + draft plan — clinician-facing assessment + patient-friendly draft guidance

• Medical record draft — objective, technical documentation (EHR-style)

C) Safety & escalation

Implement “hard-stop” escalation logic for red flags (examples: suicidality/self-harm intent, severe acute symptoms). The system must interrupt the normal flow and route to urgent guidance + clinician escalation.

D) Privacy-first development (no PHI exposure)

We want the system designed so that:

• No real patient PHI is used during development/testing.

• Testing uses synthetic and/or properly de-identified data only.

• Implement a PHI/PII minimization & redaction layer before any OpenAI API call.

• Provide guidance for best-available OpenAI API privacy posture (e.g., retention-minimization options depending on eligibility).

3) Technical Expectations

Must be able to:

• Integrate with the OpenAI API and enforce structured JSON outputs (schema validation)

• Build workflow orchestration (state machine, transitions, retries, fallbacks)

• Implement prompt-injection resistance patterns and hallucination containment

• Provide auditability (who approved what, when) without leaking PHI

• Build a simple clinician review UI (or integrate with an existing dashboard) for approve/edit/reject/escalate

Nice to have:

• Experience with WhatsApp/chat systems and webhook-based integrations

• Healthcare security mindset (LGPD/HIPAA-like design patterns)

4) MVP Deliverables

• Architecture + security/privacy notes

• State machine implementation (3 phases + gating)

• JSON schemas per phase + validation

• PHI redaction/minimization gateway

• Working MVP demonstrating:
• triage question generation
• clinician approval gate
• escalation flow for red flags
• clinician-facing summary + patient-facing draft text (as draft, clinician-reviewed)
• medical record draft

• Synthetic test suite (including red-flag cases)

• Documentation for clinicians/operators

5) Acceptance Criteria (Objective)

• Outputs consistently pass schema validation

• Red-flag scenarios trigger escalation in 100% of test cases

• Workflow cannot progress without clinician approval

• No PHI required in dev/test environment

• Clear audit trail for approvals/edits

6) What to include in your application

Please send:

1–3 examples of shipped LLM/agent systems (preferably with integrations)

Proposed stack + workflow approach (short)

How you’ll implement privacy-first development and PHI minimization

Quote for a paid pilot (first stage + approval + escalation)

Confidential details (exact prompts, templates, phrasing standards, integration endpoints, internal policies) will be shared only with shortlisted candidates after NDA.

Atividades do cliente nesse projeto:

Última visualização: ontem às 15:33

Última interação: 28/02/2026 às 14:52

Informações adicionais

Categoria: Web, Mobile & Software
Subcategoria: Criação & Integração com IA
Orçamento: Aberto
Nível de experiência: Especialista
Visibilidade: Público
Propostas: 9
Interessados: 10
Valor Mínimo: R$ 50,00

Cliente

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Propostas (9)
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