IP Library Granted Patent US 10,123,748
Granted Patent B2
US 10,123,748 · App. 14/527,824 · Granted Nov 13, 2018

Active patient risk prediction

Inventors: Hongfei Li (Briarcliff Manor, NY); Buyue Qian (Ossining, NY); Fei Wang (Briarcliff, NY); Xiang Wang (Santa Clara, CA)
Assignee: International Business Machines Corporation
A61B5/7275G06F19/00G16H50/30G16H50/70A61B5/055
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Quick Facts
Patent No.
US 10,123,748
App. No.
14/527,824
Granted
Nov 13, 2018
Kind
B2
Abstract

Electronic health records of a plurality of patients are received. A risk prediction model for a disease based on the electronic health records of the plurality of patients is created. An electronic health record of an original patient is received. A neighboring group of patients of the plurality of patients is identified, wherein the neighboring group of patients is two or more patients similar to the original patient. An ordering of the two or more patients of the neighboring group of patients is received, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient. The risk prediction model is updated based on the ordering of the two or more patients of the neighboring group of patients.

Claims (49)

1. A method for updating a patient risk prediction model, the method comprising:

receiving electronic health records of a plurality of patients;

creating, by one or more computer processors, a risk prediction model for a disease based on the electronic health records of the plurality of patients;

receiving, by one or more computer processors, an electronic health record of an original patient;

identifying, by one or more computer processors, a neighboring group of patients of the plurality of patients, wherein the neighboring group of patients is two or more patients similar to the original patient;

generating, by one or more computer processors, a question as to a relative ordering of the two or more patients of the neighboring group of patients with respect to the original patient;

receiving an answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient; and

updating, by one or more computer processors, the risk prediction model based on the answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients.

2. The method of claim 1 , further comprising:

estimating, by one or more computer processors, the risk that the original patient will suffer from the disease based upon the updated risk prediction model.

3. The method of claim 1 , wherein the ordering of the patients of the neighboring group of patients is a complete ordering including all patients of the neighboring group of patients or a partial ordering including at least one of the patients of the neighboring group of patients.

4. The method of claim 1 , wherein the risk prediction model for a disease based on the plurality of patients is selected from a group consisting of: constrained least square problem, a linear system of equations, or a quadratic program.

5. The method of claim 1 , wherein the risk prediction model is updated until a patient similarity converges in a constrained similarity process.

6. The method of claim 1 , wherein the risk prediction model is updated more than one time.

7. The method of claim 1 , wherein the electronic health record includes one or more of the following: demographics; medical history; medication and allergies; immunization status; laboratory test results; radiology images; vital signs; and personal statistics.

8. A computer program product for updating a patient risk prediction model, the computer program product comprising:

one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising:

program instructions to receive electronic health records of a plurality of patients;

program instructions to create a risk prediction model for a disease based on the electronic health records of the plurality of patients;

program instructions to receive an electronic health record of an original patient;

program instructions to identify a neighboring group of patients of the plurality of patients, wherein the neighboring group of patients is two or more patients similar to the original patient;

program instructions to generate a question as to a relative ordering of the two or more patients of the neighboring group of patients with respect to the original patient;

program instructions to receive an answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient; and

program instructions to update the risk prediction model based on the answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients.

9. The computer program product of claim 8 , further comprising program instructions, stored on the one or more computer readable storage media, to:

estimate the risk that the original patient will suffer from the disease based upon the updated risk prediction model.

10. The computer program product of claim 8 , wherein the ordering of the patients of the neighboring group of patients is a complete ordering including all patients of the neighboring group of patients or a partial ordering including at least one of the patients of the neighboring group of patients.

11. The computer program product of claim 8 , wherein the risk prediction model for a disease based on the plurality of patients is selected from a group consisting of: constrained least square problem, a linear system of equations, or a quadratic program.

12. The computer program product of claim 8 , wherein the risk prediction is updated until a patient similarity converges in a constrained similarity process.

13. The computer program product of claim 8 , wherein the risk prediction model is updated more than one time.

14. The computer program product of claim 8 , wherein the electronic health record includes one or more of the following: demographics; medical history; medication and allergies;

immunization status; laboratory test results; radiology images; vital signs; and personal statistics.

15. A computer system for updating a patient risk prediction model, the computer system comprising:

one or more computer processors;

one or more computer readable storage media; and

program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising:

program instructions to receive electronic health records of a plurality of patients;

program instructions to create a risk prediction model for a disease based on the electronic health records of the plurality of patients;

program instructions to receive an electronic health record of an original patient;

program instructions to identify a neighboring group of patients of the plurality of patients, wherein the neighboring group of patients is two or more patients similar to the original patient;

program instructions to generate a question as to a relative ordering of the two or more patients of the neighboring group of patients with respect to the original patient;

program instructions to receive an answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient; and

program instructions to update the risk prediction model based on the answer to the question as to the relative ordering of the two or more patients of the neighboring group of patients.

16. A computer system of claim 15 , further comprising program instructions, stored on the one or more computer readable storage media for execution by the at least one of the one or more computer processors, to:

estimate the risk that the original patient will suffer from the disease based upon the updated risk prediction model.

17. A computer system of claim 15 , wherein the ordering of the patients of the neighboring group of patients is a complete ordering including all patients of the neighboring group of patients or a partial ordering including at least one of the patients of the neighboring group of patients.

18. A computer system of claim 15 , wherein the risk prediction model for a disease based on the plurality of patients is selected from a group consisting of: constrained least square problem, a linear system of equations, or a quadratic program.

19. A computer system of claim 15 , wherein the risk prediction model is updated more than one time.

20. A computer system of claim 15 , wherein the electronic health record includes one or more of the following: demographics; medical history; medication and allergies; immunization status; laboratory test results; radiology images; vital signs; and personal statistics.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 30, 2014
From: LI, HONGFEI; QIAN, BUYUE; WANG, FEI; WANG, XIANG
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 034067/0515 →
Continuity (1)
Related Publication 20160120481A1 · May 5, 2016