Less retyping, more time for patients.

Booking that writes into the scheduling system and the record, with confirmations, preparation instructions and reminders sent automatically.

Patients answer at home, the answers are scored before the visit, and the doctor opens a summary in the record.

One plan for staff, rooms, devices and laboratory runs, with the constraints of each.

Letters and reports drafted from the record, checked, edited and signed by the doctor.

Values read into the record as drafts, each with its source line. A draft value is not shown as a final result and feeds no rule or alert until staff confirm it.

Follow up questionnaires at set intervals, with the results returned to the record and shown per procedure.

Dashboards and reports across sites, fed from the systems already in use.

An integration layer to the HIS, LIS and PACS you run, with access by role and logging, under GDPR or HIPAA.

A chat assistant answers from the institution's approved content, such as preparation, opening hours and directions, tells the patient that it is an AI and hands over to a person when needed.

An assistant books, moves and cancels appointments in the scheduling system, with every booking action logged. How it identifies the patient, and what it may change or tell after that, is fixed in the specification.

PROMs such as EQ-5D or the Oxford knee score, used under the licence each instrument requires, sent at set intervals after a procedure, scored, and the results shown per procedure, and per surgeon only with the case mix and the number of cases beside each figure.

Questionnaires and home measurements after discharge, with values over a threshold flagged. Alerts on measured values can make software a medical device, so the intended purpose (what the manufacturer states the software is for) is fixed in the specification before an alert is sent to the responsible nurse. Thresholds, delay and behaviour when a link fails are verified before use.

Referrals read, sorted by specialty and suggested urgency, and missing information requested. A named clinician confirms the suggested urgency before the appointment is set. Alerting and urgency sorting can make software a medical device, so the intended purpose is fixed in the specification first.

Incoming documents classified, indexed to the right patient and filed into the record, with uncertain cases sent to staff.

Patients likely to miss an appointment get an extra reminder, and freed slots are offered to the waiting list.

Preparation and discharge instructions translated by AI and checked by staff before they are sent.

Staff ask in plain language, and the answer cites the institution's own protocol and its version.

A summary per patient drafted from the record for the handover, checked by the nurse.

Questions about volumes, waiting times and capacity answered from read only data, with the query shown.