The easiest way to understand HealthTeky is to stop thinking of it as software and start thinking of it as staff — a team that never goes off shift, never forgets the interaction check, and never gets to make the decision. Each role below is a way of talking about features that actually ship; the links go to what implements it.
Dictate the consultation. It returns a structured SOAP draft with the orders and prescriptions extracted, each one safety-checked and queued for the doctor to sign. The doctor signs; it never does.
Every set of vitals recorded anywhere in the hospital is scored on NEWS2 as it is saved, ranked into a worklist of who needs attention first, and escalated with an SBAR handover when it crosses the line.
Allergy, interaction, duplication, renal dosing, pregnancy and age checks at the point of prescribing, again at dispensing, plus an antimicrobial stewardship round on what should be narrowed or stopped.
Symptom text in, acuity out, with the exact phrase that caused it. Pre-visit history taken in the patient's own language that stops dead on a red flag, and an ED board running ESI in its published order.
Deterioration trends, sepsis screening and Hour-1 bundle timers, so the three in the morning handover is a screen rather than a memory.
Bed board and discharge blockers surfaced early, a drafted discharge summary in the patient's language, and post-discharge check-ins scored green, amber or red with free text read for red flags.
Syndromic surveillance asking whether today looks unusual and where, control rates per disease register, and the care gaps a headline number hides.
Documentation gaps that cause denials, surfaced while the patient is still in front of you, with ICD-10 suggestions a coder confirms.
Every AI action and every refusal written to a hash-chained trail, replayable against the rules as they stood that day, and assembled into the evidence pack an accreditation visit asks for.
The Guardian sorts each action into one of these levels before it runs. The level decides whether a human must sign, and who is allowed to. This is not a setting a hospital can switch off to go faster.
21 action types are governed this way, across 13 staff roles. Every refusal is recorded as carefully as every action.
It can draft a prescription, check it against allergy, interaction, renal function and pregnancy, and put it in a queue. A doctor signs it. If no one signs, nothing happens.
Permissions are checked per action, not per screen. A multi-step plan requires every permission its steps need — not the one belonging to the biggest step.
Each action is written to a hash-chained trail with the inputs it saw and the rules in force that day, so a question asked two years later has an answer.
We will run the AI Nurse against a week of your real observations on a training tenant, and show you what it would have escalated and when.
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