Multiple resource planning system
View Patent ↗A system for managing remote doctor medical request workflow may include a workflow module that optimizes assignments of medical requests to remote doctors based on parameterized doctor and scheduling information and may further include a forecasting module that predicts the hospital credentials, state licenses or doctors needed to fulfill a projected volume of future medical requests. In one embodiment, radiologists are parameterized and then matched with requests for radiological readings based on information extracted from DICOM image headers and merged with associated information contained in a medical work order. In this embodiment, the radiologists are parameterized based on their locations, schedules, hospital credentials, state licensing, compensation metrics, and performance metrics and incoming requests for review of CT scans and the like are filtered based on the parameterized radiologist information to identify one or more radiologists who are to fulfill the medical request.
1. A system for generating an optimized assignment schedule for a future time period, the system comprising:
at least one processor;
at least one memory operably coupled to the processor:,
a data module operable with the at least one processor and at least one memory and configured to provide data associated with previous radiological reading requests submitted by a plurality of medical facilities at a plurality of different locations;
a prediction generator operable with the processor and memory and configured to generate an optimized assignment schedule based upon the future time period, the prediction generator configured for:
identifying a volume of previous radiological reading requests associated with each location, the volume relating to a prior time period;
identifying a volume of future radiological reading requests expected to be received from the medical facilities during the future time period, the future time period being the same length as the prior time period;
identifying one or more assignment parameters selected from the group consisting of doctor work schedules, expected licensing approvals, expected credentialing approvals, medical facility preferences for certain doctors, doctor contract terms, doctor compensation metrics, historical doctor performance metrics, and additional medical facilities to be serviced during the future time period;
identifying, within the doctor work schedules, a list of scheduled doctors associated with the future time period;
identifying an optimized assignment schedule, including:
(a) assigning each of the volume of future radiological reading requests to one of the scheduled doctors; and
(b) creating a proposed assignment schedule based upon the assignments;
wherein identifying the optimized assignment schedule is repeated for a plurality of iterations, each iteration including a different combination of doctors and radiological reading requests.
2. The system of claim 1 , the prediction generator further configured for storing the optimized assignment schedule.
3. The system of claim 1 , further comprising a workflow module configured for:
determining, at the beginning of the future time period, whether a list of available doctors matches the scheduled doctors and a list of connected medical facilities matches the plurality of medical facilities; and
assigning one or more current radiological reading requests using the optimized assignment schedule based upon the determination.
4. The system of claim 3 , wherein assigning each of the volume of future radiological reading requests includes ranking, at the workflow module, the list of scheduled doctors, the ranking comprising:
determining a pending assignment volume for each in the list of scheduled doctors and applying a volume weight for doctors having low pending order volumes;
determining the radiological reading request quota for each in the list of scheduled doctors and applying a quota weight for doctors currently below quota;
combining the volume weight and the quota weight for each in the list of scheduled doctors into a total weight value; and
identifying a selected doctor based upon the total weight value.
5. The system of claim 1 , wherein the prior time period includes a same day or days of the week, a same month, or a same season as the future time period.
6. The system of claim 1 , the prediction generator further configured for identifying a projected shortfall of radiological reading requests necessary to meet a threshold number of radiological reading requests per each of the scheduled doctors, the threshold number included within the doctor contract terms.
7. The system of claim 1 , wherein the volume of future radiological reading requests is determined in part on the volume of previous radiological reading requests weighted by a calculated growth factor.
8. The system of claim 1 , wherein the volume of future radiological reading requests is determined in part on a number of contractually obligated radiological reading requests per medical facility.
9. The system of claim 1 , the prediction generator further configured for determining, based on the optimized assignment schedule, a number of licenses, credentials, or doctors needed to fulfill the future radiological reading requests.
10. The system of claim 9 , the prediction generator further configured for providing a hiring recommendation or a credentialing recommendation based upon the number of unassigned radiological reading requests.
11. The system of claim 9 , further comprising providing a delay recommendation regarding an addition of a new medical facility or an addition of a new doctor.
12. The system of claim 1 , wherein assigning the volume of future radiological reading requests includes allocating a predicted receipt time to each of the future radiological reading requests on a bell curve model.
13. The system of claim 1 , wherein identifying a volume of future radiological reading requests expected to be received from the medical facilities during the future time period comprises:
calculating an average number of radiological reading requests received from two or more medical facilities during the prior time period, and
applying the average number to predict the volume of future radiological reading requests expected to be received from the additional medical facilities.
14. The system of claim 1 , wherein identifying the optimized assignment schedule further includes identifying a lowest number of unassigned radiological requests, by determining a number of unassigned radiological reading requests associated with each proposed assignment schedule.