Systems and methods for decoding payer identification in health care data records

• US 7,747,658 B2
• Filed: 07/19/2004
• Issued: 06/29/2010
• Est. Priority Date: 07/18/2003
• Status: Active Grant

• Current Assignee: IMS Software Services Ltd. (IQVIA Holdings, Inc.)
• Original Assignee: IMS Software Services Ltd. (IQVIA Holdings, Inc.)
• Inventors: Pennente, Kimberly, James, Mary Kay, Blanton, Ilene, Moyer, Kevin, Franklin, Dave
• Primary Examiner(s): Cottingham; John R.
• Assistant Examiner(s): Reyes; Mariela D
• Application Number:
  US10/893,838
• Publication Number:
  US 20050071200A1
• Time in Patent Office: 2,171 Days
• Field of Search: 705/2
• US Class Current: 707/809
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: Y10S 707/941 Human sciences

Abstract

Processing arrangements and methods are provided for the automated decoding or translation of information in healthcare data records, which are coded in a non-standardized or varying formats. A data record which contains information, a portion which is recognized and another portion of which is new, is decoded or translated using a statistical mapping rule. The mapping rule assigns a most likely translation value to the information based on the recognized portion of the information. The statistical mapping rules are established by analysis of a set of previously decoded data records.

Claims

1. A method for establishing mapping rules for mapping user codes (MR payer IDs) to prescription transaction data records, wherein each data record comprises at least a first, a second and a third data fields, the method comprising:

analyzing a set of previously mapped data records that have been assigned MR payer IDs based on at least the values of the third data fields;

determining unique combinations of first and second data field values present in the set of data records;

for each unique combination of the first and second data field values, determining a MR payer ID that is frequently assigned to the corresponding data records, wherein the frequency of assignment is above a cutoff limit value;

establishing a mapping rule that assigns the frequently mapped MR payer ID to all data records having the unique combination of the first and second data field values;

Wherein a mapping rule is assigned only for the unique combinations of the first and second data field values that occur with a frequency greater than a cutoff limit.

2. The method of claim 1, further comprising validating the mapping rule with a data supplier of the data records.

3. A computer data processing arrangement comprising software applications for carrying out the steps of claim 1.

4. A method for assigning user codes (MR payer IDs) to prescription transaction data records fields selected from the group of a bank identification number (BIN) data field, and a Group ID (GID) data field and a data supplier specified payer indicia (DS) data field, and wherein a first subset of the data records have been previously assigned MR payer IDs based on known mappings of the values in their respective DS data fields, and a second subset of data records that have not been assigned MR payer IDs, the method comprising:

for the first subset,

extracting data records in which at least one of the BIN and GID fields are populated;

determining the unique combinations of the BIN and GID values present in the first subset;

determining the occurrence frequency of each unique combination of BIN and GID values in the first subset,

selecting only those unique combinations of BIN and GID values that occur with a frequency greater than a cutoff limit X;

for each such selected combination of BIN and GID values determining the frequency distribution of MR payer IDs assigned to corresponding data records in the first subset;

selecting MR payer IDs having an occurrence frequency greater than a cutoff limit Y,

for each such selected MR payer ID, establishing the combination of the BIN and GID values and the selected MR payer ID as a mapping rule for mapping data records in a second subset of data records.

5. The method of claim 4 further comprises validating the mapping rule with a data supplier.

6. The method of claim 4 wherein the data records further comprise a Processor Control Number (PCN) data field, and wherein the combinations of the BIN and GID values comprises a combination of the BIN, GID and PCN values.

7. The method of claim 4 further comprising:

for the second subset,

grouping data records by unique combinations of BIN and GID values present in the second subset;

identifying BIN and GID combinations that have mapping rules established by analysis of the first subset of data records; and

assigning the grouped data records MR payer IDs according to the mapping rules established by analysis of the first subset of data records.

8. The method of claim 7 wherein the data records further comprise a Processor Control Number (PCN) data field, and wherein the combinations of the BIN and GID values comprise a combination of the BIN, GID and PCN values.

9. The method of claim 4 further comprising:

for the second subset,

grouping data records by unique combinations of BIN and GID values present in the second set;

identifying unique BIN and GID combinations that do not have mapping rules established by analysis of the first subset of data records;

manually verifying the MR payer ID for those data records that do not have matching rules established by analysis of the first subset of data records;

establishing the unique combination of BIN and GID values and the corresponding manually verified MR payer ID as a mapping rule.

10. The method of claim 9 wherein the data records further comprise a Processor Control Number (PCN) data field, and wherein the combinations of the BIN and GID values comprise a combination of the BIN, GID and PCN values.