Patent ID: 11929164
Assignee: UNIVERSITY OF SOUTH ALABAMA
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system for managing patient load comprising,
a computing device having a user interface,
wherein said user interface is configured to display at least one displayable indicia that indicates a risk level,
wherein said risk level represents a chance an individual has of committing a medical related error while providing healthcare services to a plurality of patients based on workload data,
wherein said workload data includes data representing one or more working conditions experienced by said individual over a period of time,

a processor operably connected to said computing device,
a scanning device operably connected to said processor and configured to read barcodes containing workload data associated with said plurality of patients,
wherein said scanning device transmits said workload data contained within said barcodes to said processor,

a database operably connected to said processor and configured to store said workload data within a workload profile of said individual,
wherein said workload profile is associated with said individual,

a power supply, and
a non-transitory computer-readable medium coupled to said processor and having instructions stored thereon, which, when executed by said processor, cause said processor to perform operations comprising:
receiving said workload data associated with said individual,
retrieving near miss data associated with said individual, said near miss data including data representing one or more instances of an averted medical error over said period of time,
calculating at least one threshold limit for each of said one or more working conditions based on said workload data and said near miss data,
retrieving said workload data from said scanning device,
adding said workload data from said scanning device to current workload data, said current workload data including data representing said one or more working conditions experienced by said individual in real time,
comparing said current workload data to said at least one threshold limit, and
generating said at least one displayable indicia for display in said user interface to indicate said risk level of said individual.