System and method for multi-dimensional physician-specific data mining for pharmaceutical sales and marketing

• US 7,698,157 B2
• Filed: 06/06/2003
• Issued: 04/13/2010
• Est. Priority Date: 06/12/2002
• Status: Active Grant

• Current Assignee: Humana Incorporated
• Original Assignee: Anvita, Inc. (Humana Incorporated)
• Inventors: Ghouri, Ahmed
• Primary Examiner(s): Koppikar; Vivek D
• Application Number:
  US10/456,402
• Publication Number:
  US 20040049506A1
• Time in Patent Office: 2,503 Days
• Field of Search: 705 2- 4
• US Class Current: 705/3
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage

Abstract

The present invention relates to a system and method for electronic and algorithmic data mining of an individual physician'"'"'s prescribing history to determine the approximate distribution of diseases within their practice population for optimizing pharmaceutical sales and marketing. Rapid and large-scale determination of specific clinical safety and efficacy attributes of a marketed drug which are most pertinent and relevant to a given physician, when compared to a competitor'"'"'s drug, are defined and tabularized. Major clinical characteristics taken into account include a drug'"'"'s safety, efficacy, cost, dosing convenience, formulary insurance coverage, side effect profiles, and FDA approval for the intended use. A symbolic representation of knowledge is employed in which the marketed drug and each competitor'"'"'s drug are compared algorithmically against each other with a scoring system that is based upon machine analysis of each major clinical characteristic. The score is further refined according to the number and severity of safety interactions which are relevant to the comparison, and also based upon predicted prevalence of such interactions within a specific physician'"'"'s practice.

Claims

1. A method for optimizing pharmaceutical sales and marketing information based on a prescribing entity'"'"'s prescribing history on a computer-based system, the method comprising:

obtaining a prescribing entity'"'"'s prescription history for a defined time period;

establishing an actual disease prevalence for the prescribing entity based on a frequency relationship between each drug prescribed by the prescribing entity and a disease for which it is prescribed;

determining a general prevalence value for each disease in the general population; and

establishing, by a computer, a weighted disease prevalence profile for the prescribing entity based on a mathematical combination of an adjusted general prevalence value and an adjusted actual prevalence value, wherein the adjusted general prevalence value and the adjusted actual prevalence value are adjusted based on the proportion of patients who have untreated disease and diseases requiring at least one drug.

2. The method according to claim 1, further comprising:

establishing a database of hierarchical medical attributes, the attributes arranged in a parent-child relationship fashion in accordance with medical ontology; and

symbolically representing each attribute as a data object.

3. The method according to claim 2, wherein the medical attributes include drug, disease and allergy term definitions, the method further comprising:

establishing interaction dimensions between and among the drug, disease and allergy term definitions; and

defining a severity score for a particular drug based on the severity of a drug-drug interaction dimension.

4. The method according to claim 3, further comprising:

determining a composite safety score for a particular drug based on the severity score of the drug-drug interaction and a prevalence score based on a frequency of occurrence of a drug-disease interaction; and

ranking selected ones of a plurality of generally related drugs on the basis of their composite safety scores.

5. The method according to claim 4, further comprising:

determining relevant therapeutic endpoints for determining efficacy of a particular drug with respect to a particular indication for which it is prescribed, the endpoints included in the database of medical attributes;

determining a composite efficacy score for a particular drug based on its efficacy with respect to an endpoint for its associated indication and a prevalence of use score based on the prescription history of the prescribing entity; and

ranking selected ones of a plurality of generally related drugs on the basis of their composite efficacy scores.

6. The method according to claim 5, further comprising:

identifying differences in the composite safety and efficacy scores of a drug which is being marketed and particular ones of substantially similar drugs commonly prescribed by the prescribing entity; and

preparing marketing material for the marketed drug comparing its safety and efficacy to the particular ones of substantially similar drugs commonly prescribed by the prescribing entity.

7. The method according to claim 6, wherein the marketing material includes safety and efficacy score comparison information for the marketed drug characterized in accordance with drug-disease interactions based on the prescribing entity'"'"'s weighted disease prevalence.

8. A method for optimizing pharmaceutical sales and marketing information to a specific prescribing entity on a computer-based system, the method comprising:

acquiring a prescribing entity'"'"'s prescription history including a listing of prescribed drugs and a frequency of prescription of each drug;

determining a disease distribution among the individuals comprising the prescribing entity'"'"'s practice on the basis of the prescription history;

establishing, by a computer, a drug safety score on the basis of a severity criteria and a frequency criteria for at least known drug-drug and drug-disease interactions between and among a plurality of substantially similar drugs; and

ranking the plurality of substantially similar drugs on the basis of the drug safety score and a prevalence criteria determined by the prevalence of use of a particular drug by the prescribing entity and the prevalence of occurrence of a particular disease within the prescribing entity'"'"'s practice wherein the prevalence criteria is adjusted based on the proportion of patients who have untreated disease and diseases requiring at least one drug.

9. The method according to claim 8, further comprising:

establishing a drug efficacy score on the basis of a drug'"'"'s efficacy towards a defined therapeutic endpoint for each of the plurality of substantially similar drugs; and

ranking the plurality of substantially similar drugs on the basis of the drug efficacy score and a prevalence criteria determined by the prevalence of use of a particular drug within the prescribing entity'"'"'s practice.

10. The method according to claim 9, further comprising:

comparing the safety and efficacy score of a drug being marketed against the safety and efficacy scores of the plurality;

identifying particular ones of the drugs commonly prescribed by the prescribing entity that exhibit lower safety and/or efficacy scores from the drug being marketed; and

identifying those drug-drug and/or drug-disease interactions for which the drug being marketed exhibits superior scores than the drugs commonly prescribed by the prescribing entity.

11. The method according to claim 10, further comprising:

establishing a database of hierarchical medical attributes, the attributes arranged in a parent-child relationship fashion in accordance with medical ontology; and

symbolically representing each attribute as a data object.

12. The method according to claim 11, wherein the medical attributes include drug-drug interaction, drug-disease and allergy term definitions, the method further comprising:

establishing a severity and a frequency of occurrence criteria between and among the term definitions; and

defining the severity score for a particular drug based on the severity of a drug-drug interaction criteria.

13. The method according to claim 12, further comprising:

determining a composite safety score for a particular drug based on the severity score of the drug-drug interaction and a prevalence score based on a frequency of occurrence of a drug-disease interaction; and

ranking the a plurality of generally related drugs on the basis of their composite safety scores.

14. A method for optimizing pharmaceutical sales and marketing information to a specific prescribing entity on a computer-based system, the method comprising:

determining a listing of drugs prescribed by the prescribing entity;

defining, by a computer a distribution of disease among the patients of the prescribing entity'"'"'s practice on the basis of drugs prescribed to generate a weighted disease prevalence that is adjusted based on the proportion of patients who have untreated disease and diseases requiring at least one drug;

scoring a drug being marketed on the basis of a safety criteria with respect to drug-drug interactions against the drugs prescribed by the prescribing entity;

scoring a drug being marketed on the basis of an efficacy criteria with respect to disease against the drugs prescribed by the prescribing entity; and

identifying safety and efficacy criteria of the drug being marketed with respect to the drugs prescribed by the prescribing entity.

15. The method according to claim 14, further comprising:

establishing an actual disease prevalence for the prescribing entity based on a frequency relationship between each drug prescribed by the prescribing entity and a disease for which it is prescribed;

determining a general prevalence value for each disease in the general population; and

establishing a weighted disease prevalence profile for the prescribing entity based on a combination of the general prevalence value and the actual prevalence value.

16. The method according to claim 15, further comprising:

establishing a database of hierarchical safety and efficacy attributes, the attributes arranged in a parent-child relationship fashion in accordance with medical ontology; and

symbolically representing each attribute as a data object.

17. The method according to claim 16, wherein the attributes include drug, disease and allergy term definitions, the method further comprising:

establishing interaction dimensions between and among the term definitions; and

defining an interaction severity score for a particular drug based on the severity of a drug-drug interaction dimension.

18. The method according to claim 17, further comprising:

determining a composite safety score for a particular drug based on the severity score of the drug-drug interaction and a prevalence score based on a frequency of occurrence of a drug-disease interaction; and

ranking selected ones of a plurality of generally related drugs on the basis of their composite safety scores.

19. The method according to claim 18, wherein the determining and ranking steps are performed by computational operation on the data objects, such that the identification of superior safety and efficacy criteria of the drug being marketed with respect to the drugs prescribed by the prescribing entity is performed electronically.