Clinical Decision Support System

• US 20120232930A1
• Filed: 03/11/2012
• Published: 09/13/2012
• Est. Priority Date: 03/12/2011
• Status: Abandoned Application

• Current Assignee: Definiens AG (Astrazeneca PLC)
• Original Assignee: Definiens AG (Astrazeneca PLC)
• Inventors: Schmidt, Guenter, Rinecker, Markus, Binnig, Gerd, Schaepe, Arno, Heydler, Thomas
• Application Number:
  US13/417,268
• Publication Number:
  US 20120232930A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: A61B 6/502 for diagnosis of breast, i.e. mammography
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/30068 Mammography; Breast
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/40 Analysis of texture depth or shape recovery from texture G06T7/529
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A clinical decision support system performs a similarity search to determine the probable outcome of applying on a current patient those clinical actions that were performed on similar patients. The system analyzes stored electronic health records of similar patients so as to recommend diagnostic and therapeutic steps for the current patient. The system receives the health record of the patient, determines which clinical actions were already applied on the patient, generates classifiers associated with potential future clinical actions, generates a success value for each health record of another patient using the classifiers, displays the health record of the other patient having the greatest success value, and indicates a proposed clinical action that is to be applied on the patient. The system also calculates a quality value indicating the probability that a sequence of clinical actions that were applied to a similar patient will be successful if applied to the patient.

Claims

1. A method comprising:

receiving a first electronic health record of a patient;

determining a first clinical action that was applied on the patient;

generating a plurality of classifiers, wherein each of the classifiers is associated with a clinical action that is to occur after the first clinical action;

classifying stored electronic health records of other patients using the plurality of classifiers, wherein the classifying generates a success value for each electronic health record of another patient;

displaying a portion of that electronic health record of another patient that has the greatest success value; and

indicating a second clinical action that is to be applied on the patient, wherein the second clinical action is determined by the classifier that generated the greatest success value.

2. The method of claim 1, wherein the indicating is performed by displaying a representation of the second clinical action on a graphical user interface.

3. The method of claim 1, wherein the first clinical action is acquiring an x-ray mammography, and wherein the second clinical action is acquiring a magnetic resonance (MR) tomography.

4. The method of claim 1, wherein the second clinical action is a diagnosis that refines an earlier diagnosis obtained using the first clinical action.

5. The method of claim 1, wherein the second clinical action is a therapy that follows a diagnosis obtained using the first clinical action.

6. The method of claim 1, wherein the second clinical action is an examination that extends the first electronic health record.

7. The method of claim 1, wherein each of the stored electronic health records is structured hierarchically, and wherein the classifying is performed using the hierarchical structure.

8. The method of claim 1, wherein one of the plurality of classifiers uses a fuzzy membership function to classify the stored electronic health records, and wherein the fuzzy membership function is related to an entry in the stored electronic health records.

9. The method of claim 1, further comprising:

indicating a plurality of potential second clinical actions, wherein the second clinical action is one of the plurality of potential second clinical actions.

10. The method of claim 1, wherein the second clinical action is retrieved from a database in which patient medical records and associated clinical actions are stored.

11. A method comprising:

(a) receiving an electronic health record of a patient, wherein the electronic health record indicates a past clinical action applied to the patient;

(b) identifying a group of similar patients who are similar to the patient by performing a similarity search in a database, wherein the similarity search determines the similarity between two patients based on their electronic health records;

(c) calculating a quality value for the patient based on the electronic health records of each patient in the group of similar patients, wherein each quality value indicates a probability that a sequence of clinical actions that were applied to a similar patient will be successful if applied to the patient; and

(d) indicating the clinical actions associated with the highest quality value.

12. The method of claim 11, wherein the indicating is performed by displaying a representation of the clinical actions on a graphical user interface.

13. The method of claim 11, wherein each quality value is determined based on a quality-of-life parameter for the patient.

14. The method of claim 11, wherein each quality value is determined based on an estimated disease free survival time for the patient.

15. The method of claim 11, wherein each quality value is determined based on an estimated overall survival time for the patient.

16. The method of claim 11, wherein each quality value is determined based on a cost of the clinical actions associated with each quality value.

17. A method comprising:

receiving an electronic health record of a patient, wherein the electronic health record indicates a past clinical action applied to the patient;

identifying potential next clinical actions to be applied to the patient;

receiving a decision as to which of the potential next clinical actions are to be applied to the patient;

generating a protocol that indicates the decision and the potential next clinical actions; and

displaying the protocol on a graphical user interface.

18. The method of claim 17, further comprising:

determining a quality value for each of the potential next clinical actions, wherein each quality value indicates a probability that a potential next clinical action will be successful if applied to the patient.

19. The method of claim 18, further comprising:

determining which of the potential next clinical actions has the highest quality value; and

highlighting a representation of the potential next clinical action with the highest quality value on a graphical user interface.

20. A method comprising:

receiving an electronic health record of a patient, wherein the electronic health record indicates a clinical action being applied to the patient;

identifying a potential next clinical action to be applied to the patient;

determining a success value for the potential next clinical action, wherein the success value indicates a probability that the potential next clinical action will be successful if applied to the patient;

determining a quality value associated with a set of potential next clinical actions, wherein the set of potential next clinical actions includes the potential next clinical action, and wherein the quality value is based on the success value;

determining that the set of potential next clinical actions has the highest quality value as compared to other sets of potential next clinical actions; and

displaying medical data on a graphical user interface supporting the determination that the set of potential next clinical actions has the highest quality value.

21. The method of claim 20, wherein the quality value is determined based on a quality-of-life parameter for the patient.

22. The method of claim 20, wherein the quality value is determined based on an estimated disease free survival time for the patient.

23. The method of claim 20, wherein the quality value is determined based on a cost of the set of potential next clinical actions.

24. The method of claim 20, further comprising:

receiving a decision as to which set of potential next clinical actions are to be applied to the patient.