Using diagnoses to identify adults with disabilities
OwnerSusan Palsbo, Margaret Mastalinventors
Life of this patent
Estimating the term…
Abstract
Individuals with disabilities may be classified under a particular health risk level using an access risk classification system based on nonstatistical risks. This computer methodology and system collects and aggregates medical data, which includes a person identifier and the person identifier's medical codes. By applying a data mining technique, each person identifier's medical codes can be assigned a highest access risk level, which in turn, may be used to classify the person identifier.
Claims20
A tangible computer readable medium encoded with instructions for classifying individuals with disabilities, executable by a machine under the control of a program of instructions, in which said machine includes a memory storing said program, wherein execution of said instructions by one or more processors causes said one or more processors to perform a multitude of steps comprising:
- a. collecting medical data, said medical data including;
- i. a person identifier;
- and
- ii. at least one medical code, each of said medical code being associated with an access risk level;
- b. aggregating said medical data around said person identifier, creating aggregated medical data;
- and
- c. classifying said person identifier under a highest access risk level for each diagnosis within said aggregated medical data to determine a corresponding level of clinical service intensity by applying a data mining technique, said data mining technique using said access risk level associated with one or more records associated with said person identifier.
A tangible computer readable medium encoded with instructions for classifying individuals with disabilities, executable by a machine under the control of a program of instructions, in which said machine includes a memory storing said program, wherein execution of said instructions by one or more processors causes said one or more processors to perform a multitude of steps comprising:
- a. collecting medical data from a database, said database including a multitude of records, each of said multitude of records including;
- i. a person identifier;
- and
- ii. at least one medical code, each of said medical code being associated with an access risk level;
- b. aggregating said medical data around said person identifier, creating aggregated medical data;
- c. classifying said person identifier into one of a multitude of said access risk level by applying a data mining technique, said data mining technique using said access risk level associated with one or more of said records associated with said person identifier;
- and
- d. performing said data mining technique for each of said person identifier, said data mining technique including iterative steps comprising:
- i. associating said access risk level with said medical code;
- ii. grouping all of said records with the same said person identifier;
- iii. determining a highest access risk level by using said “all of said records with the same said person identifier”;
- and
- iv. associating said highest access risk level with said “same said person identifier”.
A method for classifying individuals with disabilities comprising:
- a. collecting medical data, said medical data including;
- i. a person identifier;
- and
- ii. at least one medical code, each of said medical code being associated with an access risk level;
- b. aggregating said medical data around said person identifier, creating aggregated medical data;
- and
- c. classifying said person identifier under a highest access risk level for each diagnosis within said aggregated medical data to determine a corresponding level of clinical service intensity by applying a data mining technique, said data mining technique using said access risk level associated with one or more records associated with said person identifier.
A system for classifying individuals with disabilities comprising:
- a. a medical data collector configured for collecting medical data, said medical data including;
- i. a person identifier;
- and
- ii. at least one medical code, each of said medical code being associated with an access risk level;
- b. a medical data aggregator configured for aggregating said medical data around said person identifier, creating aggregated medical data;
- and
- c. a medical data classifier configured for classifying said person identifier under a highest access risk level for each diagnosis within said aggregated medical data to determine a corresponding level of clinical service intensity by applying a data mining technique, said data mining technique using said access risk level associated with one or more records associated with said person identifier.
Dependencies are inferred from the claim text.