Patient data mining for cardiology screening

• US 8,280,750 B2
• Filed: 05/14/2010
• Issued: 10/02/2012
• Est. Priority Date: 11/02/2001
• Status: Expired due to Term

• Current Assignee: Cerner Health Services Incorporated (Oracle Corporation)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Krishnan, Sriram, Rao, R. Bharat
• Primary Examiner(s): Mallari, Patricia
• Assistant Examiner(s): Weston, Tiffany
• Application Number:
  US12/780,012
• Publication Number:
  US 20100222646A1
• Time in Patent Office: 872 Days
• Field of Search: 600/481, 600/300, 600/301, 705/2, 705/3, 707/999.1, 707/E17.117
• US Class Current: 705/2
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/60 relating to pathologies
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics

Abstract

A system and method for screening for coronary heart disease is provided. The method includes the steps of retrieving a test for assessing risk of coronary heart disease, the test including a plurality of data fields relating to coronary risk factors; accessing a database to populate the data fields with information of an individual patient; and calculating a risk assessment of the individual patient developing coronary heart disease. A system includes a first database including a plurality of structured computerized patient records; a second database including a knowledge base relating to coronary heart disease, the second database including at least one test for determining coronary heart disease risk; and a processor for retrieving the at least one test from the second database, populating the at least one test with patient information retrieved from the first database and calculating a risk assessment for at least one patient.

Claims

1. A coronary heart disease screening system comprising:

a first database including a plurality of structured computerized patient records mined, at least in part, form an unstructured data source using probabilistic inference, a first of the structured computerized patient records having patient information for a plurality of coronary risk factors for a patient;

a second database including a knowledge base relating to coronary heart disease, the second database including at least one test for determining coronary heart disease risk wherein the at least one test includes a plurality of data fields relating to the coronary risk factors; and

a processor for retrieving the at least one test from the second database, populating the data fields of the at least one test with patient information retrieved from the first database and calculating a risk assessment for the patient.

2. The system as in claim 1, wherein the first database is compiled by data mining information relating to the coronary risk factors from structured and unstructured data sources.

3. The system as in claim 1, further comprising an assessment module for determining whether the patient has a low risk, intermediate risk or high risk of developing coronary heart disease based on the calculated risk assessment.

4. The system as in claim 3, wherein if the individual patient is determined to be an intermediate risk, the processor is adapted to stratify the risk assessment by data mining information measuring atherosclerotic burden from the structured computerized patient record of the patient.

5. The system as in claim 1, further comprising a patient management module for recommending lifestyle changes to the patient based on the calculated risk assessment.

6. The system as in claim 5, wherein the patient management module tracks the patient over a period of time and recalculates the risk assessment of the patient.

7. The system as in claim 1, further comprising a patient management module for recommending therapies to the patient based on the calculated risk assessment.

8. The system as in claim 7, wherein the patient management module tracks the patient over a period of time and recalculating the risk assessment of the patient.

9. The system as in claim 1, further comprising a sensitivity module for analyzing the coronary risks factors of the patient to determine which factor will have the greatest effect in influencing the risk assessment.

10. The system as in claim 9, further comprising a modeling module for generating a model of a coronary heart disease patient to simulate effects of different variables, the model being employed by the sensitivity module.

11. The system as in claim 1, further comprising an imaging module for extracting patient information from images and storing the patient information in the structured computerized patient record.

12. The system as in claim 1, wherein the processor determines a time for a follow-up assessment based on the calculated assessment.

13. The system as in claim 1, wherein the processor determines if at least one of the plurality of data fields is not populated and recommends a test to be conducted to populate the at least one data field.

14. The system as in claim 9, wherein the processor determines a time for a follow-up assessment based on the determined risk factor.

15. The system as in claim 9, wherein the processor determines if at least one of the plurality of data fields is not populated and recommends a test to be conducted if the at least one data field is the determined risk factor.

16. The system as in claim 1, wherein at least one of the plurality of structured patient records include information obtained from mining unstructured data.

17. The system of claim 1, wherein the plurality of structured patient records include probabilistic information for the patient information of the coronary risk factors.

18. The systems of claim 1, wherein all the patient information needed to calculate the risk assessment is not included in the plurality of structured patient records.

19. The system of claim 8, wherein missing information is mined probabilistically and the risk assessment is adjusted to include the probabilistic patient information in the risk assessment.

20. The system of claim 19, wherein the risk assessment is computed automatically at periodic intervals from the patient record.

21. The system of claim 20, wherein the processor notifies if there is a significant change in the patient'"'"'s risk assessment.

22. The system of claim 21, wherein the processor notifies if sufficient time has lapsed such that it is possible the patient'"'"'s risk assessment has significantly changed.

23. The system of claim 1 wherein the processor is configured to recommend tests, therapies, lifestyle changes, or combinations thereof as a function of analysis of the populated data field and a medical guideline.

24. The system of claim 1 wherein the processor is configured to assist in following a guideline.