Artificial intelligence in medicine in Uruguay

Clinical documentation challenges in Uruguay

• Integrate tools without creating parallel repositories disconnected from the HCEN.
• Maintain semantic quality and traceability among providers.
• Ensure legal basis, limited access, and clinical review of each document.

These challenges are not solved with more text. They require useful information, defined owners, and a review process that corresponds to actual practice.

The HCEN exchanges information; it does not replace the provider's systems

The National Electronic Health Record allows consultation of clinical information shared among providers, but each institution continues to produce and safeguard documentation in its own systems. This distinction is essential when evaluating AI: a draft can support local work without automatically becoming a document available in the NEHR.

The organization must identify the legal basis for processing, access profiles, traceability, and the publication or exchange mechanism. It must also check whether data leaves the country, which sub-processors are involved, and how rectification is exercised. Law 18.331 and the Salud.uy ecosystem provide a more mature framework than in other markets, but they do not eliminate the need for institutional governance.

In practice, it is advisable to test outpatient consultation, emergency care, chronic follow-up, and telemedicine separately. Each workflow produces different documents and permissions. The useful metric is not how many notes the AI generates, but how many are correctly reviewed, incorporated, and available for continuity of care without duplication.

What to evaluate before adopting clinical AI

An evaluation must check interoperability, provider responsibilities, the legal basis for data processing, service location, access control, and how the reviewed result is incorporated into the case file.

• Integrate tools without creating parallel repositories disconnected from the HCEN.
• Maintain semantic quality and traceability among providers.
• Ensure legal basis, limited access, and clinical review of each document.

Expand the context in Medical AI by country, AI for Doctors, Clinic software, security and privacy, and compare with Argentina and Paraguay.

How to evaluate clinical AI in a Uruguayan institution

A pilot should start in a service with repetitive documentation and clear review criteria. In addition to measuring time and quality, it is advisable to check how the responsible professional is identified, how the result is incorporated into the institutional system, and what information can be circulated through the National Electronic Health Record. The AI tool supports the work; it does not replace the provider's governance or the rules of the medical record.

Public sources for further reading

• IMPO: Law 18.331 ↗
• Agesic: HCEN ↗

Informative content prepared on September 12, 2026. Use this page as initial guidance. Before deciding, confirm the current regulations and policies of your organization.