ICU planning no longer rebuilds states per question: one frozen patient world model drives admission, care and discharge simulations
ICU resource planning has long relied on compact state-transition models hand-specified for a single policy question, so a new question means redefining states. A patient world model trained on MIMIC-IV and then frozen encodes irregular electronic health records as state-event sequences, returns predictions at any interval the simulator requests, and connects through scenario-specific mappings to shared bed and staff queues. Across admission, care-dispatch and discharge simulations it agrees with task-fitted Markov and semi-Markov comparators on directional responses to capacity and dispatch policies, and reproduces the dispatch gains obtained by replaying observed trajectories.