OPTIMIZING PATIENT PLACEMENT AND SEQUENCING IN A DYNAMIC MEDICAL SYSTEM USING A COMPLEX HEURISTIC WITH EMBEDDED MACHINE LEARNING

OPTIMIZING PATIENT PLACEMENT AND SEQUENCING IN A DYNAMIC MEDICAL SYSTEM USING A COMPLEX HEURISTIC WITH EMBEDDED MACHINE LEARNING

Techniques are described for optimizing patient placement and sequencing in dynamic medical environment. In various embodiments, a method includes receiving current state information regarding a current state of a medical facility system in real-time, including operating conditions data regarding cu...

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Bibliographische Detailangaben
Hauptverfasser: Thomas, Bex George, Day, Andrew
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Zusammenfassung:Techniques are described for optimizing patient placement and sequencing in dynamic medical environment. In various embodiments, a method includes receiving current state information regarding a current state of a medical facility system in real-time, including operating conditions data regarding current operating conditions of the medical facility system and patient case data regarding active patient cases and pending patient cases of the medical facility system. The method further includes forecasting future state information for the medical facility system based on the current state information using a machine learning framework, including forecasted timeline information regarding future timing of workflow events of the active patient cases and pending patient cases. The method further includes employing a heuristic-based optimization mechanism to determine optimal reactive solutions regarding patient sequencing, patient placement and resource allocation based on the current state information, the future state information, defined rules of the medical care facility system, and one or more defined optimization criteria.