CPC G16H 40/20 (2018.01) [G06Q 10/067 (2013.01); G16H 10/60 (2018.01)] | 16 Claims |
1. A care pathway management apparatus comprising a processor configured to:
process patient data for a healthcare facility to compute a clinical response time for one or more patients of the healthcare facility;
model tasks for one or more protocols associated with a care pathway for one or more patients in a cohort grouping and an associated time to execute the modeled tasks, the processor to prescribe a task for a resource in a current time to reduce at least one of a future adverse clinical condition or a future excess response time for one or more patients;
identify a first patient record associated with a first care pathway;
identify a second patient record that is not on the first care pathway but should be on the first care pathway;
generate and display a graphical user interface including information regarding the first patient record associated with the first care pathway and the second patient record that should be associated with the first care pathway, wherein the first patient record and associated first care pathway information are displayed in a first area of the graphical user interface and the second patient record in a second area of the graphical user interface, wherein, when the second patient record is confirmed in the second area, the processor is to trigger a notification to evaluate the second patient record;
facilitate interaction, via the graphical user interface, with the first patient record and the second patient record;
trigger an alert based on feedback from a system monitor when the first patient record is not in compliance with at least one of a task order or a clinical state of the first care pathway, the alert comprising probabilistic alert information based on a defect state; and
automatically update the first patient record and a system configuration using a probability for clinical metrics for the first care pathway, wherein the probability is based on an acceleration of change within a rolling window of time series data from one or more sensing components, the time series data comprising historical data for a first clinical metric and a predicted second clinical metric at a future time.
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