Methods for electronically processing insurance claims and devices thereof
A method and computing apparatus for automatically identifying whether or not one or more identified injuries are related to the insurance claim which has been submitted is described. The method and computing apparatus identify injury data in an electronic medical claim data associated with a claimant based diagnosis code data, uses a classifier to determine an association between the identified injury data represented by the diagnosis code data and the initial injury data represented by the initial diagnosis code data is identified when historical claim data is determined to be present for the claimant.
1. A method comprising:
obtaining a database comprising correlations between conditions having diagnosis codes, the correlations indicating whether a current condition is not caused by, caused by, or associated with a traumatic incident associated with a historical condition;
receiving a first electronic medical claim associated with a first claimant;
determining whether historical claim data includes a historical medical claim associated with the first claimant; and
responsive to determining the historical claim data includes the historical medical claim associated with the first claimant, providing the historical medical claim and the first electronic medical claim as input to one or more trained machine learning models, wherein responsive to the input, at least one of the trained machine learning models outputs one of the correlations between a condition associated with the first electronic medical claim and a condition associated with the historical medical claim, wherein the one or more trained machine learning models have been trained using the correlations in the database.
2. The method of claim 1 , wherein the condition associated with the historical medical claim specifies historical claim data for the first claimant.
3. The method of claim 1 , further comprising providing, when the correlation is absent, claim processing guidance data relating to absence of correlation between the condition associated with the first electronic medical claim and the condition associated with the historical medical claim.
4. The method of claim 1 , wherein the first electronic medical claim comprises an electronic casualty claim and the diagnosis codes include training at least one ICD code.
5. The method of claim 1 , further comprising analyzing by a data processor training at least one of the diagnosis codes to determine a severity of the condition associated with the historical medical claim.
6. The method of claim 1 , further comprising:
training the one or more machine learning models using the correlations in the database.
7. A system, comprising:
a processor;
a memory coupled to the processor; wherein the processor is configured to:
obtain a database comprising correlations between conditions having diagnosis codes, the correlations indicating whether a current condition is not caused by, caused by, or associated with a traumatic incident associated with a historical condition;
receive a first electronic medical claim associated with a first claimant;
determine whether historical claim data includes a historical medical claim associated with the first claimant; and
responsive to determining the historical claim data includes the historical medical claim associated with the first claimant, provide the historical medical claim and the first electronic medical claim as input to one or more trained machine learning models, wherein responsive to the input, at least one of the trained machine learning models outputs one of the correlations between a condition associated with the first electronic medical claim and a condition associated with the historical medical claim, wherein the one or more trained machine learning models have been trained using the correlations in the database.
8. The system of claim 7 , wherein the condition associated with the historical medical claim specifies historical claim data for training the first claimant.
9. The system of claim 7 , wherein the processor is further configured to provide, when the correlation is absent, claim processing guidance data relating to absence of correlation between the condition associated with the first electronic medical claim and the condition associated with the historical medical claim.
10. The system of claim 9 , wherein the processor is further configured to analyze training at least one of the diagnosis codes to determine a severity of the condition associated with the historical medical claim.
11. The system of claim 7 , wherein the first electronic medical claim comprises an electronic casualty claim and the diagnosis codes include training at least one ICD code.
12. The system of claim 7 , wherein the processor is configured to:
train the one or more machine learning models using the correlations in the database.
13. A non-transitory computer-readable storage medium storing a plurality of instructions executable by one or more processors, the plurality of instructions when executed by the one or more processors cause the one or more processors to:
obtain a database comprising correlations between conditions having diagnosis codes, the correlations indicating whether a current condition is not caused by, caused by, or associated with a traumatic incident associated with a historical condition;
receive a first electronic medical claim associated with a first claimant;
determine whether historical claim data includes a historical medical claim associated with the first claimant; and
responsive to determining the historical claim data includes the historical medical claim associated with the first claimant, provide the historical medical claim and the first electronic medical claim as input to one or more trained machine learning models, wherein responsive to the input, at least one of the trained machine learning models outputs one of the correlations between a condition associated with the first electronic medical claim and a condition associated with the historical medical claim, wherein the one or more trained machine learning models have been trained using the correlations in the database.
14. The non-transitory computer readable medium of claim 10 , wherein the condition associated with the historical medical claim specifies historical claim data for training the first claimant.
15. The non-transitory computer readable medium of claim 13 , wherein the processor is further configured to provide, when the correlation is absent, claim processing guidance data relating to absence of correlation between the condition associated with the first electronic medical claim and the condition associated with the historical medical claim.
16. The non-transitory computer readable medium of claim 10 , wherein the first electronic medical claim comprises an electronic casualty claim and the diagnosis codes include training at least one ICD code.
17. The non-transitory computer readable medium of claim 10 , wherein the processor is further configured to analyze training at least one of the diagnosis codes to determine a severity of the condition associated with the historical medical claim.
18. The non-transitory computer readable medium of claim 13 , wherein the processor is further configured to:
train the one or more machine learning models using the correlations in the database.