AI for productivity and precision in medical records
AI application created to transform clinical conversation into structured documentation, reducing the professional's administrative effort without replacing their clinical analysis or decision.

The challenge
During and after a consultation, healthcare professionals need to record clinical information, organize medical terms, structure history, and synthesize conduct. This administrative work consumes significant time and competes with the attention that should be directed toward interaction with the patient.
The solution developed
CISP1 developed an application capable of receiving the transcription of clinical interaction and converting the content into a structured record. The solution identifies relevant elements of the consultation, recognizes medical terminology, and organizes the content into a clinical synthesis suitable for the documentation flow.
The result is presented for the professional's review, preserving clinical responsibility and allowing the technology to act as a layer of productivity and record organization. The application structures the information for each field of the medical record and can connect to the electronic health record via APIs or other controlled integration mechanisms.
How the application works
- Listens to the conversation between doctor and patient, performs real-time transcription, correctly identifying medical terms, medication names, etc.
- Organizes relevant information, context, and medical terminology.
- Structures the content into medical record fields and produces a synthesis of the consultation.
- Makes the record available for review and validation by the professional.
- Integrates the validated content into the medical record flow, when provided for in the project.
Value for the operation
- Reduces documentation effort during and after the consultation.
- Increases standardization of clinical records.
- Preserves relevant information discussed throughout the care process.
- Allows the professional to direct more attention to patient interaction.
Capabilities applied
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