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公开(公告)号:US20200227147A1
公开(公告)日:2020-07-16
申请号:US16738549
申请日:2020-01-09
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor: Nicholas J. Raddatz , Dominick R. Rocco
Abstract: A computer implemented method includes receiving text-based clinical documentation corresponding to a patient treated at a healthcare facility, converting the text-based clinical documentation to create a machine compatible converted input having multiple features, providing the converted input to a trained machine learning model that has been trained based on a training set of historical converted clinical documentation by the first entity, and receiving a prediction from the trained machine learning model, wherein the prediction corresponds to at least one of a predicted diagnostic related group (DRG) code or a set of predictions comprising a predicted principal diagnosis code for provision to a DRG calculator to determine the DRG code.
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公开(公告)号:US20200227175A1
公开(公告)日:2020-07-16
申请号:US16738442
申请日:2020-01-09
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor: Julie A. Salomon , Julie L. Imburgia , Jeffrey S. Seese , Nicholas J. Raddatz , Dominick R. Rocco
IPC: G16H50/70 , G16H10/60 , G16H50/20 , G16H70/20 , G16H70/60 , G06F40/253 , G06F40/284 , G06F40/295
Abstract: A computer implemented method includes receiving text-based clinical documentation corresponding to a patient treated at a healthcare facility, converting the text-based clinical documentation to create a machine compatible converted input having multiple features, providing the converted input to a trained machine learning model that has been trained based on a training set of historical converted clinical documentation by the first entity, receiving a prediction from the trained machine learning model, wherein the prediction corresponds to at least one of a predicted diagnostic related group (DRG) code or a set of predictions comprising a predicted principal diagnosis code for provision to a DRG calculator to determine the DRG code, and assign a priority score at least partially based on the prediction.
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