CLINICAL DECISION SUPPORT SYSTEM FOR DIAGNOSING AND MONITORING OF A DISEASE OF A PATIENT

• US 20160259899A1
• Filed: 03/04/2016
• Published: 09/08/2016
• Est. Priority Date: 03/04/2015
• Status: Abandoned Application

• Current Assignee: Expeda Ehf
• Original Assignee: Expeda Ehf
• Inventors: LUDVIKSSON, Bjorn Runar, GUDBJORNSSON, Bjorn, HALLDORSSON, Bjarni, JONASDOTTIR, Dagrun
• Application Number:
  US15/061,305
• Publication Number:
  US 20160259899A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A clinical decision support system for diagnosis and monitoring of a disease of at least one patient includes a computing system, a storage media, in communication with the computer system, configured to store medical data sets from two or more different medical training data sources, where each of the two or more different medical training data sources have uniquely defined objective findings influencing the disease. The severity of the objective findings within each data source is indicated by independent weight factors. A computer program operating on the computing system is configured to perform a knowledge mapping between the data in the two or more different medical training data sources for obtaining plurality of clinical weight factors that define a unique classification rules. An input module is provided for receiving medical data about a patient, and a processor processes the received medical data from the input module.

Claims

1. A clinical decision support system for diagnosis and monitoring of a disease of at least one patient, the system comprising:

a computing system;

a storage media, in communication with the computer system, configured to store medical data sets from two or more different medical training data sources, where each of the two or more different medical training data sources have uniquely defined objective findings influencing the disease, the severity of the objective findings within each data source being indicated by independent weight factors;

a computer program operating on the computing system, the computer program being configured to perform a knowledge mapping between the data in the two or more different medical training data sources, where the knowledge mapping includes;

a) receiving a first and at least one second weight factors from a first and at least one second medical training data sources selected from the two or more different medical training data sources;

b) determining, based on the received weight factors, at least one clinical weight factor by means of utilizing interactive rules associated to the two or more different medical training data sources, the at least one clinical weight factor indicating the severity of the combination of the first and the at least one second symptom weight factors to the disease;

c) repeating steps a) and b) for the remaining weight factors within the two or more different medical training data sources so as to determine the remaining clinical weight factors defining a unique classification rules;

an input module adapted to receive medical data about a patient; and

a processor for processing the received medical data from the input module, where the processing includes;

comparing the receive medical data to the unique classification rules, and based thereon;

extracting an appropriate personalized medical assessment indicator for the patient.

2. The clinical decision support system according to claim 1, wherein the interactive rules associated to the two or more different medical training data sources are governed by mathematical functions whereby the variable factors of the functions are the first and the at least one second weight factors.

3. The clinical decision support system according to claim 1, wherein the interactive rules associated to the two or more different medical training data sources are defined by a look-up table indicating how different values of the first and the at least one second weight factors result in different clinical weight factors.

4. The clinical decision support system according to claim 1, wherein the independent weight factors within the two or more different medical training data sources are within a pre-defined weight value range and where the severity of the objective findings within each data source is indicated by different values within the pre-defined weight value range.

5. The clinical decision support system according to claim 1, wherein the independent weight factors within the two or more different medical training data sources are defined by medical experts where the severity of the objective findings within each data source is indicated with values within the pre-defined weight value range.

6. The clinical decision support system according to claim 1, further comprising triggering, upon that the severity of the objective findings within a data source indicated by independent weight factors changes, a signal instructing the computer program to updated the knowledge mapping by means of repeating steps a)-c) so as to update the update the unique classification rules.

7. The clinical decision support system according to claim 1, wherein the unique classification rules are defined in at least one decision tree where the different branching in the decision tree indicate different clinical weight factors, wherein the step of comparing the receive medical data to the unique classification rules comprises positioning the patient within the at least one decision tree.

8. The clinical decision support system according to claim 7, wherein the associated weight value of the clinical weight factor where the patient is positioned within the at least one decision tree is utilized as input data in extracting the appropriate personalized medical assessment indicator for the patient.

9. The clinical decision support system according to claim 1, wherein the appropriate personalized medical assessment indicator is indicated in ascending order values where the higher the order is the more severe is the diagnosis of the disease.

10. The clinical decision support system according to claim 9, further comprising a display operated by the processor wherein the ascending order values are adapted to visually presenting the severity visually to the patient.

11. The clinical decision support system according to claim 10, wherein the personalized medical assessment indicator triggers at least one of the following recommendations:

diagnostic recommendation;

therapeutic medical recommendation;

therapeutic and preventive life-style recommendation;

follow up recommendation.

12. The clinical decision support system according to claim 1, wherein the receive medical data about the patient include the age of the patient, wherein the age is utilized in by the processor in triggering comparison process where the diagnosis of the patient is compared with the diagnosis of other patients of the same or similar age.

13. The clinical decision support system according to claim 1, wherein in case the personalized medical assessment indicator exceeds a pre-defined threshold level the processor instructs that patient via communication means to immediately seek for assistance by a medical expert.

14. A computerized diagnostic method for diagnosis and monitoring of a disease of at least one patient, the method comprising:

storing medical data sets from two or more different medical training data sources at a storage media in a computer system, where each of the two or more different medical training data sources have uniquely defined objective findings influencing the disease, the severity of the objective findings within each data source being indicated by independent weight factors;

performing, via a computer program operating on the computing system, a knowledge mapping between the data in the two or more different medical training data sources, where the knowledge mapping includes;

a) receiving a first and at least one second weight factors from a first and at least one second medical training data sources selected from the two or more different medical training data sources;

b) determining, based on the received weight factors, at least one clinical weight factor by means of utilizing interactive rules associated to the two or more different medical training data sources, the at least one clinical weight factor indicating the severity of the combination of the first and the at least one second symptom weight factors to the disease;

c) repeating steps a) and b) for the remaining weight factors within the two or more different medical training data sources so as to determine the remaining clinical weight factors resulting in a unique classification rules;

receiving, via an input module, medical data about a patient; and

processing, via a processor, the received medical data from the input module, where the processing includes;

comparing the receive medical data to the unique classification rules, and based thereon;

extracting an appropriate personalized medical assessment indicator for the patient.

15. A computer readable medium storing computer readable program code embodied therein for diagnosing and monitoring of a disease of at least one patient, the computer readable code comprising instructions which when executed by a processor perform the method of:

performing, via a computer program operating on a computing system, a knowledge mapping between data in two or more different medical training data sources stored;

a storage media in the computer system, where each of the two or more different medical training data sources have uniquely defined objective findings influencing the disease, the severity of the objective findings within each data source being indicated by independent weight factors, where the data where the knowledge mapping includes;

a) receiving a first and at least one second weight factors from a first and at least one second medical training data sources selected from the two or more different medical training data sources;

b) determining, based on the received weight factors, at least one clinical weight factor by means of utilizing interactive rules associated to the two or more different medical training data sources, the at least one clinical weight factor indicating the severity of the combination of the first and the at least one second symptom weight factors to the disease;

c) repeating steps a) and b) for the remaining weight factors within the two or more different medical training data sources so as to determine the remaining clinical weight factors resulting in a unique classification rules;

receiving, via an input module, medical data about a patient; and

processing, via a processor, the received medical data from the input module, where the processing includes;

comparing the receive medical data to the unique classification rules, and based thereon;

extracting an appropriate personalized medical assessment indicator for the patient.