Patent ID: 11955213
Assignee: IODINE SOFTWARE, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A system, comprising:
a processor;
a non-transitory computer-readable medium; and
instructions stored on the non-transitory computer-readable medium and translatable by the processor for:
responsive to new data arriving at a data store, processing entities of interest extracted from the new data into concepts specific to a patient;
automatically summarizing the concepts specific to the patient into concept groups, the concept groups indicative of medical conditions of the patient documented at time points during the patient's stay at a facility;
providing the concept groups to non-time-sensitive models and time-sensitive models;
wherein, on a per medical condition basis, a non-time-sensitive machine learning engine applies the non-time-sensitive models to the concept groups across all the medical conditions of the patient and generates an output containing a list of documented medical conditions that the patient likely has during the patient's stay; and
wherein, on a per medical condition basis, a time-sensitive machine learning engine applies the time-sensitive models to the concept groups across the medical conditions of the patient documented within a time period and generates an output containing a running total of documented medical conditions that the patient likely has sufficiently documented during the time period;
comparing the output from the non-time-sensitive machine learning engine and the output from the time-sensitive machine learning engine to identify any medical condition of the patient that is identified by the non-time-sensitive machine learning engine as having been documented during the patient's stay, but that is not identified by the time-sensitive machine learning engine as having been sufficiently documented during the time period, indicating that a documentation drop-off (DDO) has occurred; and
generating a notification that the DDO has occurred.