Use cases · Primary care · Hospital ward · Specialist clinic
Referral letters and clinical documents
Referral letters, discharge summaries, medical reports and common forms take time to write, and incomplete ones cause delays or get sent back. From the history and records, TESSA drafts each document with what the reader needs, such as the reason for referral, relevant history, test results, medicines and allergies. The doctor reviews, edits and signs it.
At a glance
- Does
- Summarisation
- Setting
- Primary care, Hospital ward, Specialist clinic
- Specialty
- Any specialty
- Who
- Clinician-side
Also searched as
referral letter · discharge summary · medical report writing · AI medical documentation
Questions
What does TESSA do in referral letters and clinical documents?
Referral letters, discharge summaries, medical reports and common forms take time to write, and incomplete ones cause delays or get sent back. From the history and records, TESSA drafts each document with what the reader needs, such as the reason for referral, relevant history, test results, medicines and allergies. The doctor reviews, edits and signs it. It does this through summarisation.
Does TESSA diagnose the patient?
No, TESSA never gives a patient a diagnosis. It collects and collates the information the patient provides, asks probing questions and performs risk assessment; a clinician reviews the summary and decides, and no diagnosis, summary or management plan reaches the patient until the clinician signs.
What happens if the patient mentions a warning sign?
Warning or worrying signs that require immediate attention or action go straight to the care team without alarming the patient. For time-critical presentations, TESSA supports the clinician only and is not currently intended for patient use.
How is patient information protected?
The patient surface runs on session codes, not names, and each institution's data is kept apart with a full audit trail. Our own Anonesia by TINYHealth is a proprietary software and code that removes PIIs, e.g. names, ID numbers and contact details from text before it reaches an AI model.
How do we start with this use case?
Each new use case is built and validated with clinical teams, on your own pathways and guidance. Book a meeting with us to start.
