Computer-implemented system and method for associating prescription data and de-duplication

A computer system for associating prescription-related data, comprising:

• a memory;
• a communication device operatively coupled to the memory to receive incoming batch transaction data from a plurality of sources, said incoming batch transaction data relating to the prescription-related data, said batch transaction data comprising a plurality of predetermined classifications;
• and
• at least one processor, operatively coupled to the communications device for processing the classifications in order to obtain attributes for the classifications and processing the attributes to determine matches among the attributes for a respective classification for a predetermined period of time;
• wherein the at least one processor matches the attributes via:
• a primary association pass, whereby the primary association pass compares attributes reflecting at least one of (i) prescription number, (ii) prescription fill date, or (iii) refill code of the incoming batch transaction data to attribute in existing event cluster;
• a secondary association pass, whereby the secondary association pass compares attributes reflecting at least one of (i) parmarch ID, (ii) prescription number, (iii) drug identification number, or (iv) prescription fill of the incoming batch transaction data to attribute in said existing event clusters;
• wherein, when no match has occurred in either the primary or secondary association pass, the at least one processor matches incoming attribute groups to attribute in existing event clusters;
• via:
• a tertiary association pass, whereby the tertiary association pass compares attributes reflecting a tertiary incoming attribute group of the incoming batch transaction data to attribute in said existing event clusters:
• a quaternary association pass, whereby the quaternary association pass compares attributes reflecting a quaternary incoming attribute group of the incoming batch transaction data to attributes in said existing event clusters;
• and
• a quinary association pass, whereby the quinary association pass compares attributes reflecting a quinary incoming attribute group of the incoming batch transaction data to attributes in said existing event clusters;
• wherein the at least one processor updates existing clusters to include one more attributes of the incoming batch transaction data when a match with one or more existing event clusters has occurred in the primary, secondary, tertiary, quaternary, or quinary association passes, thereby identifying event associated with the prescription-related data;
• and
• wherein the at least one processor groups into one or more event clusters the matches for each attribute during the predetermined period of time to identify event associated with the prescription-related data that do not match an existing event cluster.

A computer network for associating prescription-related data, comprising:

• at least one memory device;
• at least one communication device operatively coupled to the at least one memory device to receive incoming batch transaction data from a plurality of sources, said incoming batch transaction data relating to the prescription-related data, said incoming batch transaction data comprising a plurality of predetermined classifications;
• and at least one processor, operatively coupled to the communications device for processing the classifications in order to obtain attributes for the classifications and processing the attributes to determine matches among the attributes for a respective classification for a predetermined period of time;
• wherein the at least one processor
• (i) processes the attributes by identifying a first matching attributes comprising pharmacy identification, prescription number, refill code, and a prescription fill date within a specified range,
• (ii) processes the attributes by identifying a second matching attribute comprising pharmacy identification, prescription number, drug identification code, and a prescription fill date within a specified range,
• (iii) processes the attributes by identifying a third matching attribute comprising prescription fill date, refill code, drug identification number, gender and age,
• (iv) processes the attributes by identifying a fourth matching attribute comprising fill date, refill code, drug identification number, practitioner and days' supply,
• (vii) processes the attributes by identifying a fifth matching attribute comprising prescription fill date, refill code and number of refills authorized,
• (viii) updates existing event clusters to include one more attributes of the incoming batch transaction data when a match with one or more existing event clusters has occurred in the first, second, third, fourth or fifth matching attribute processes;
• and
• (ix) groups into one or more event clusters the matches for each attribute during the predetermined period of time to identify events associates with the prescription-related data that do not match an existing event cluster.