Medical data analysis system

• US 20050197862A1
• Filed: 01/28/2005
• Published: 09/08/2005
• Est. Priority Date: 01/30/2004
• Status: Abandoned Application

• Current Assignee: PharMetrics, Inc. (IQVIA Holdings, Inc.)
• Original Assignee: PharMetrics, Inc. (IQVIA Holdings, Inc.)
• Inventors: Morgan, Dane, Norton, Stan, Paterson, Daniel, Ceder, Gerbrand
• Application Number:
  US11/047,467
• Publication Number:
  US 20050197862A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Prediction methods including statistical and artificial intelligence methods to predict the prescribing behavior and characteristics and size of patient populations under the care of health care providers from limited data, based on processes developed on integrated medical and pharmaceutical claims data. Prescribers can be classified into groups and subgroups, and marketing recommendations can be made to organizations with interest in the drug prescriptions based on prescription data; sales force effectiveness and marketing message effectiveness products can also be developed.

Claims

1. A method comprising:

using medical claims data to determine a treatment rate for a number of medical providers based on treated and untreated patients;

using pharmacological script data that includes prescription behavior for treated patients, but does not include prescription behavior for untreated patients, to model the treatment rate determined from the medical claims data based on data contained in the script data; and

using the model to predict treatment rates for providers based on script data for such providers.

2. The method of claim 1, wherein the claims data is used to determine a treatment rate for one or more conditions indicative of how a provider treats such one or more conditions, the model being constructed by using as inputs script data to model treatment rates as a function of script data.

3. The method of claim 2, wherein the modeling includes using regression to construct the model with coefficients R_n for script data inputs X_n to derive a treatment rate.

4. The method of claim 2, wherein the modeling includes using a neutral network to construct the model with coefficients R_n for script data inputs X_n to derive a treatment rate.

5. The method of claim 1, wherein the predicted treatment rates are used to identify and classify prescription providers with relatively high and relatively low treatment rates.

8. The method of claim 1, wherein predicting treatment rates for providers based on script data is performed by the owner of the script data using software that includes the model.

9. The method of claim 1, wherein predicting treatment rates for providers based on script data is performed by a third party service provider after receiving script data from the owner of the script data.

10. The method of claim 1, further comprising, for at least some of the providers a persistence rate indicting the rate at which patients stay on the prescribed therapy.

11. The method of claim 1, further comprising, for at least some of the providers a compliance rate indicting the rate at which patients comply with the prescribed therapy.

6. The method of claim 6, wherein the prescription providers are classified into at least three groups based on the treatment rates.

7. The method of claim 6, further comprising using the prescription provider treatment rates to direct further advertising to the providers with lower treatment rates.

12. A method comprising:

using a superset of medical data to determine a parameter for a number of medical providers;

using a subset of the medical data from which the parameter cannot be directly determined to model the parameter determined from the superset based on data contained in the subset; and

using the model to predict the parameter for medical providers based on the subset of medical data for such providers.

13. The method of claim 12, wherein the subset is prescription script data and the superset is medical claims data.

14. The method of claim 12, wherein the parameter is a treatment rate.

15. The method of claim 12, wherein predicting the parameter for providers based on the superset of data is performed by the owner of the subset of data using software that includes the model.

16. The method of claim 12, wherein predicting the parameter for providers based on the superset of data is performed by a third party service provider after receiving the subset of data from the owner of the subset of data.

17. The method of claim 12, further comprising classifying the providers into at least two groups based on the values of the parameter, and targeting advertising to the providers based on the group the provider is in.