Practice interviewing the patient, not the textbook.

A textbook patient presents symptoms in order. A real patient minimizes chest pain because they don’t want to make a fuss, forgets the name of the blood thinner they take, and mentions the most important detail as an afterthought on the way out the door.

ctReadySim^™ lets nursing students and healthcare professionals practice the conversation itself: building rapport, asking questions that actually get answered, noticing what’s missing, and recognizing when a presentation is time-sensitive.

Patients who behave like patients

The AI-performed patient has a defined condition, history, and personality — but shares them the way real patients do. Sensitive information may only surface after trust is established. Low health literacy changes how questions must be phrased. An anxious patient may need reassurance before they can give a coherent history.

The scenario engine holds the clinical truth — what is actually wrong, what the patient knows, and what remains hidden — so the interview can be scored against what was discoverable, not against what the model improvised.

How performance is measured

Evaluation focuses on what the interview discovered and how: which findings were elicited, which were missed, whether questioning was systematic, and how the trainee communicated — with transcript evidence behind each result and trainer review over every score.

Medical and patient-interaction scenarios exist in the platform today, built around emergency medical guidecards. Programs can author additional scenarios around their own curricula, assessment frameworks, and terminology.