US 2022/0189600 A1 · Unsupervised Learning And Prediction Of Lines Of Therapy From High-Dimensional Longitudinal Medications Data

Abstract

In one aspect, the present disclosure provides a method for labeling one or more medications concurrently administered to a patient as a line of therapy. The method includes identifying medical records of the patient from a plurality of digital records, creating, from the subset of medical records, a plurality of treatment intervals including at least one medication administered to the patient and a time interval, associating medications of the one or more treatments with a respective treatment interval when the administration of the medication falls within the time interval, refining the time interval of a respective treatment interval when a treatment of the one or more treatments falls outside the time interval but within an extension period, identifying one or more potential lines of therapy from the plurality of treatment intervals, and labeling the potential line of therapy having the highest maximum likelihood estimation as the line of therapy.

Claims20

Dependent claims

A method for identifying personalized care recommendations for a patient from one or more lines of therapy identified by an artificial intelligence engine from patient records of a cohort of patients, comprising:

receiving medical record data related to the patient;
identifying one or more lines of therapy derived from the patient records of the cohort of patients, the one or more lines of therapy identified by the artificial intelligence engine deriving a plurality of curated fields from the patient records, identifying a subset of the curated fields reflecting medical histories of the cohort of patients with respect to one or more disease state diagnoses, one or more patient care events occurring after the disease state diagnoses, and one or more time intervals corresponding to the patient care events,
storing the identified one or more lines of therapy in a datastore;
identifying one or more of the stored lines of therapy as being relevant to a disease state of the patient;
evaluating responses to the one or more patient care events corresponding to the relevant lines of therapy;
and
generating and transmitting a report to a user, the report comprising one or more personalized care recommendations based on the identified one or more relevant lines of therapy and the evaluated responses to the one or more patient care events, the personalized care recommendations including an identification of one or more patient care events to apply to the patient.

4 more elements

A system for identifying personalized care recommendations for a patient from one or more lines of therapy identified by an artificial intelligence engine from patient records of a cohort of patients, comprising:

at least one computer having at least one processor programmed to:
receive medical record data related to the patient;
identify one or more lines of therapy derived from the patient records of the cohort of patients, the one or more lines of therapy identified by the artificial intelligence engine deriving a plurality of curated fields from the patient records, identifying a subset of the curated fields reflecting medical histories of the cohort of patients with respect to one or more disease state diagnoses, one or more patient care events occurring after the disease state diagnoses, and one or more time intervals corresponding to the patient care events,
store the identified one or more lines of therapy in a datastore;
identify one or more of the stored lines of therapy as being relevant to a disease state of the patient;
evaluate responses to the one or more patient care events corresponding to the relevant lines of therapy;
and
generate and transmit a report to a user, the report comprising one or more personalized care recommendations based on the identified one or more relevant lines of therapy and the evaluated responses to the one or more patient care events, the personalized care recommendations including an identification of one or more patient care events to apply to the patient.

5 more elements

A computer program product for identifying personalized care recommendations for a patient from one or more lines of therapy identified by an artificial intelligence engine from patient records of a cohort of patients, comprises instructions that, when executed by a processor, cause the processor to:

receive medical record data related to the patient;
identify one or more lines of therapy derived from the patient records of the cohort of patients, the one or more lines of therapy identified by the artificial intelligence engine deriving a plurality of curated fields from the patient records, identifying a subset of the curated fields reflecting medical histories of the cohort of patients with respect to one or more disease state diagnoses, one or more patient care events occurring after the disease state diagnoses, and one or more time intervals corresponding to the patient care events,
store the identified one or more lines of therapy in a datastore;
identify one or more of the stored lines of therapy as being relevant to a disease state of the patient;
evaluate responses to the one or more patient care events corresponding to the relevant lines of therapy;
and
generate and transmit a report to a user, the report comprising one or more personalized care recommendations based on the identified one or more relevant lines of therapy and the evaluated responses to the one or more patient care events, the personalized care recommendations including an identification of one or more patient care events to apply to the patient.

4 more elements

Dependencies are inferred from the claim text.

Unsupervised Learning And Prediction Of Lines Of Therapy From High-Dimensional Longitudinal Medications Data

Life of this patent

Unsupervised Learning And Prediction Of Lines Of Therapy From High-Dimensional Longitudinal Medications Data

Life of this patent

Abstract

Claims20