System and method for computerized synthesis of simulated health data

A computerized method, comprising:

• creating, by a computing device, a state transition machine based upon data representing a clinical pathway that represents a sequence of health related events, wherein:
• a state of the state transition machine represents a health related event;
• and
• a probability of transitioning from a first state to a second state is based on a health attribute;
• generating a synthetic health data set comprised of a synthetic electronic health record (EHR) for each synthetic person in a synthetic population, wherein a select synthetic EHR for an associated synthetic person is generated by calculating health related events that follow corresponding states of the state transition machine for each time step in a synthetic life of that associated synthetic person, and wherein the health related events are determined at least in part by health attributes associated with that synthetic person at each time step;
• calculating, by the computing device, a similarity score by comparing the generated synthetic health data set to an actual health data set including an actual EHR;
• and
• tuning, by the computing device, at least one of the data representing the clinical pathway or the state transition machine, based on the computed similarity score indicating similarity falling below a threshold similarity, to create updated clinical pathways for use in the state transition machine.

A computer-implemented system comprising:

• a processor coupled to memory, where the processor reads out instructions in the memory to implement a model discovery agent, the model discovery agent comprising:
• a state transition machine that is based upon data representing a clinical pathway that represents a sequence of health related events, wherein:
• a state of the state transition machine represents a health related event;
• and
• a probability of transitioning from a first state to a second state is based on a health attribute;
• and
• a model evaluator, the model evaluator programmed to:
• generate a synthetic health data set comprised of a synthetic electronic health record (EHR) for each synthetic person in a synthetic population, wherein a select synthetic EHR for an associated synthetic person is generated by calculating health related events that follow corresponding states of the state transition machine for each time step in a synthetic life of that associated synthetic person, and wherein the health related events are determined at least in part by health attributes associated with that synthetic person at each time step;
• calculate a similarity score by comparing the generated synthetic health data set to an actual health data set including an actual EHR;
• and
• tune at least one of the data model or the state transition machine, based on the computed similarity score indicating similarity falling below a threshold similarity, by:
• determining probabilities based on the health related event from the actual health data set to infer a probability that a particular synthetic life will transition according to a corresponding clinical pathway;
• and
• selecting a distribution probability based on interpreting the data model from the inferred probability to create updated clinical pathways for use in the state transition machine.

A computerized method, comprising:

• repeatedly performing, until a similarity score indicating similarity satisfies a threshold similarity:
• creating, by a computing device, a state transition machine based upon data representing a clinical pathway that represents a sequence of health related events, wherein:
• a state of the state transition machine represents a health related event;
• and
• a probability of transitioning from a first state to a second state is based on a health attribute;
• generating a synthetic health data set comprised of a synthetic electronic health record (EHR) for each synthetic person in a synthetic population, wherein a select synthetic EHR for an associated synthetic person is generated by calculating health related events that follow corresponding states of the state transition machine for each time step in a synthetic life of that associated synthetic person, and wherein the health related events are determined at least in part by health attributes associated with that synthetic person at each time step;
• calculating, by the computing device, a new similarity score by comparing the generated synthetic health data set to an actual health data set including an actual EHR;
• and
• tuning, by the computing device, at least one of the data model or the state transition machine, based on the newly computed similarity score indicating similarity falling below the threshold similarity, to create updated clinical pathways for use in the state transition machine.