US 2020/0005941 A1Published application

Medical adverse event prediction, reporting, and prevention

AssigneeThe Johns Hopkins University

InventorsSuchi SARIA, Hossein SOLEIMANI

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Abstract

Disclosed are techniques for predicting, reporting, and preventing medical adverse events, such as septicemia. The techniques may be implemented in a client-server arrangement, where the clients are present on medical professionals' smart phone, for example. The disclosed techniques' ability to detect impending medical adverse events utilizes two innovations. First, some embodiments include a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the disclosed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, some embodiments utilize an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model.

Claims20

Dependent claims

A method of predicting an impending medical adverse event, the method comprising:

obtaining a global plurality of test results, the global plurality of test results comprising, for each of a plurality of patients, and each of a plurality of test types, a plurality of patient test results obtained over a first time interval;
scaling up, by at least one an electronic processor, a model of at least a portion of the global plurality of test results, whereby a longitudinal event model comprising at least on random variable is obtained;
determining, by at least one electronic processor, for each of the plurality of patients, and from the longitudinal event model, a hazard function comprising at least one random variable, wherein each hazard function indicates a chance that an adverse event occurs for a respective patient at a given time conditioned on information that the respective patient has not incurred an adverse event up until the given time;
generating, by at least one electronic processor, for each of the plurality of patients, a joint model comprising the longitudinal event model and a time-to-event model generated from the hazard functions, each joint model indicating a chance of an adverse event occurring within a given time interval;
obtaining, for a new patient, and each of a plurality of test types, a plurality of new patient test results obtained over a second time interval;
applying, by at least one electronic processor, the joint model to the plurality of new patient test results obtained of the second time interval;
obtaining, from the joint model, an indication that the new patient is likely to experience an impending medical adverse event within a third time interval;
and
sending an electronic message to a care provider of the new patient indicating that the new patient is likely to experience an impending medical adverse event.

6 more elements

A system for predicting an impending medical adverse event, the system comprising at least one mobile device and at least one electronic server computer communicatively coupled to at least one electronic processor and to the at least one mobile device, wherein the at least one electronic processor executes instructions to perform operations comprising:

obtaining a global plurality of test results, the global plurality of test results comprising, for each of a plurality of patients, and each of a plurality of test types, a plurality of patient test results obtained over a first time interval;
scaling up, by at least one an electronic processor, a model of at least a portion of the global plurality of test results, whereby a longitudinal event model comprising at least on random variable is obtained;
determining, by at least one electronic processor, for each of the plurality of patients, and from the longitudinal event model, a hazard function comprising at least one random variable, wherein each hazard function indicates a chance that an adverse event occurs for a respective patient at a given time conditioned on information that the respective patient has not incurred an adverse event up until the given time;
generating, by at least one electronic processor, for each of the plurality of patients, a joint model comprising the longitudinal event model and a time-to-event model generated from the hazard functions, each joint model indicating a chance of an adverse event occurring within a given time interval;
obtaining, for a new patient, and each of a plurality of test types, a plurality of new patient test results obtained over a second time interval;
applying, by at least one electronic processor, the joint model to the plurality of new patient test results obtained over the second time interval;
obtaining, from the joint model, an indication that the new patient is likely to experience an impending medical adverse event within a third time interval;
and
sending an electronic message to the mobile device indicating that the new patient is likely to experience an impending medical adverse event.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/489,971Filed 1 Mar 2018
Priority: 2 Mar 2017
Published: 2 Jan 2020
Term ends: Not estimatedThe source records don’t support an estimate.

Classification6 codes

G06Q 10/04
Administration; Management: forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or…
G16H 50/20
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…
G16H 10/20
ICT specially adapted for the handling or processing of patient-related medical or healthcare data: for electronic clinical trials or questionnaires
G16H 50/70
ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or…: for…