公开(公告)号：US11545248B2

公开(公告)日：2023-01-03

申请号：US17367253

申请日：2021-07-02

Applicant: Express Scripts Strategic Development, Inc.

Inventor： Balakrishnan Nambirajan ,  Garret L. Anderson ,  Heather L. Durosko ,  Angela Gorbett

IPC: G16H20/10 ,  G06F16/901 ,  G06F17/18 ,  G06N20/00

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.

公开(公告)号：US20210335470A1

公开(公告)日：2021-10-28

申请号：US17367253

申请日：2021-07-02

Applicant: Express Scripts Strategic Development, Inc.

Inventor： Balakrishnan Nambirajan ,  Garret L. Anderson ,  Heather L. Durosko ,  Angela Gorbett

IPC: G16H20/10 ,  G06F16/901 ,  G06F17/18 ,  G06N20/00

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.

公开(公告)号：US11056222B1

公开(公告)日：2021-07-06

申请号：US16388047

申请日：2019-04-18

Applicant: Express Scripts Strategic Development, Inc.

Inventor： Balakrishnan Nambirajan ,  Garret L. Anderson ,  Heather L. Durosko ,  Angela Gorbett

IPC: G16H20/10 ,  G06F16/901 ,  G06F17/18 ,  G06N20/00

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.