Change Healthcare Holdings, LLC

Optum, Inc.

Feili Yu

Bo Han

Wenji Zhang

Lei Qi

Changsung Moon

Alex Londeree

Carol Cheng

Feng Yi

Fan Zhou

Chenda Deng

Lynne Miller Padilla

Kolette Suzanne Cotropia

Ian Gilbert

A method includes receiving a record containing clinical information associated with a patient; and automatically processing the record using a multi-stage Artificial Intelligence (AI) engine to generate at least one suggested code for one or more portions of the clinical information; wherein the multi-stage AI engine comprises: a first module configured to identify content highlights within the one or more portions of the clinical information and associate the content highlights with candidate codes, respectively; and a second module configured to remove ones of the content highlights and/or ones of the candidate codes that have been identified and/or associated in error to generate corrected content highlights that are associated with the corrected candidate codes, respectively.

Methods, systems, and computer program products for automatically processing a clinical record for a patient using an artificial intelligence (AI) engine to identify content highlights and suggest codes therefor

A method includes receiving input information associated with a health record of a patient, the input information comprising information associated with a plurality of input variables; embedding the information associated with the plurality of variable to generate a plurality of input variable vectors, respectively; aggregating the plurality of input variable vectors to generate a patient health record vector; generating, using a knowledge graph, a first ranking of a plurality of subsets of criteria used for determining an appropriateness of a care plan for the patient based on the patient health record vector; generating, using an artificial intelligence engine, a second ranking of the plurality of subsets of the criteria used for determining the appropriateness of the care plan for the patient based on the patient health record vector; and generating a final ranking of the plurality of subsets of the criteria used for determining the appropriateness of the care plan for the patient based on the first ranking and the second ranking.

Methods, systems, and computer program products for selecting criteria subsets for performing a medical necessity review for a patient care plan

A method includes receiving a record containing first clinical information associated with a first patient; and automatically processing the record using a multi-stage Artificial Intelligence (AI) engine to generate at least one suggested code for one or more portions of the first clinical information; wherein the multi-stage AI engine comprises: a first module configured to detect whether the first clinical information includes any information associated with a second patient or whether the record contains second clinical information associated with a second patient; a second module configured to partition the first clinical information based on encounter; a third module configured to identify the one or more portions of the first clinical information; or a fourth module configured to identify content highlights within the one or more portions of the first clinical information and associate the content highlights with candidate codes, respectively.

Decision support system using an artificial intelligence (AI) framework for suggesting codes for a clinical record for a patient and related methods and computer program products

A method includes receiving input information associated with an examination order for a patient, the input information comprising first information associated with a plurality of variables and second information associated with a free-text query for the examination order; embedding the plurality of variables to generate a plurality of input variable vectors, respectively; embedding the free-text query for the order to generate a free-text query vector; aggregating the plurality of input variable vectors with the free-text query vector to generate an examination order vector; and determining, using an artificial intelligence engine, a medical indication corresponding to the examination order based on the examination order vector.

Medical indication determination using heterogeneous data in a clinical decision support system

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Shoreline, WA, United States of America

Feili Yu