Anticipating patient needs associated with toileting

A method, comprising:

• training a machine-learned model, using one or more sets of training data, to identify relationships between patient conditions and patient preferences;
• receiving, by a processor, information indicating a condition associated with a patient;
• receiving, by the processor, information indicating one or more preferences of the patient associated with toileting events;
• receiving, by the processor and from a second electronic device, an indication of an event associated with the patient, wherein the indication of the event comprises administration of a medication to the patient that affects a frequency of urine output or bowel movements;
• determining, by the trained machine-learned model, a first toilet need schedule for the patient based at least in part on the condition and the one or more preferences, the first toilet need schedule corresponding to a time period;
• providing, by the processor and to a third electronic device, a notification associated with the first toilet need schedule, the notification indicating a prediction of a toilet need of the patient;
• and
• determining, by the trained machine-learned model, a second toilet need schedule for the patient based at least in part on the condition, the one or more preferences, and the event, the second toilet need schedule corresponding to the time period and being different than the first toilet need schedule wherein the second toilet need schedule is based at least in part on a rule corresponding to toileting times associated with the medication that overrides the first toilet need schedule based on the prediction received from the machine-learned model.

A system, comprising:

• a processor;
• a first electronic device in communication with the processor via a network;
• a first sensor, separate from the first electronic device, in communication with the processor;
• a second sensor, separate from the first electronic device, in communication with the processor;
• and
• one or more computer-readable media storing instructions that, when executed by the processor, cause the processor to perform operations comprising:
• receiving first information from the first electronic device, via the network, indicating a condition associated with a patient;
• receiving second information from the first sensor indicating an event associated with the patient;
• determining, by a machine-learned model, a first toilet need schedule for the patient based at least in part on the first information and the second information, the first toilet need schedule corresponding to a time period;
• generating, based on the first toilet need schedule, a notification indicating a predicted toilet need of the patient;
• providing the notification to a second electronic device via the network;
• receiving third information from the second sensor;
• determining, by the processor, that the third information is associated with a toilet event;
• generating a second notification indicating the toilet event;
• and
• providing the second notification to a third electronic device via the network.