Mass customization for management of healthcare

• US 8,799,023 B2
• Filed: 02/21/2003
• Issued: 08/05/2014
• Est. Priority Date: 10/18/2002
• Status: Active Grant

• Current Assignee: Medimpact Healthcare Systems Incorporated
• Original Assignee: Medimpact Healthcare Systems Incorporated
• Inventors: White, William D, Chao, Schumarry
• Primary Examiner(s): Gilligan, Luke
• Assistant Examiner(s): RAPILLO, KRISTINE K
• Application Number:
  US10/372,052
• Publication Number:
  US 20060178915A1
• Time in Patent Office: 4,183 Days
• Field of Search: 705 2- 4
• US Class Current: 705/4
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 40/08 Insurance
• 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: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

A healthcare mass customization infrastructure individualizes plan designs by incorporating demographics, income, drug history, medical history, lab values, and future genomic information for appropriate and affordable access to medications. The mass customization infrastructure results in quality outcomes for the patients, improved care and productivity for the providers, and lower medical costs for the payers.

Claims

1. An automated computerized method of customizing an individual participant'"'"'s co-payment for a prescription medication, the method comprising:

providing a healthcare data platform, the platform comprising detailed individual healthcare information for a participant requesting a medication,

wherein the information comprises data from third-party partners, providers and payers,

and wherein the information comprises clinical information and financial information, and wherein the clinical information comprises at least one of;

a detailed health history, prior healthcare utilization, one or more current health treatment, one or more current health concerns, genomic information, drug history, one or more laboratory values, and healthcare demographic data, and wherein the financial information comprises income data and financial demographic data,

and wherein the information pertains to an individual participant;

receiving information regarding a prescription for a medication prescribed to the participant;

accessing the data platform to obtain medical history information of the participant including information regarding the one or more current health concerns of the participant and clinical implications of the prescription;

based on at least the medical history information and the clinical implications of the prescription, determining a current clinical value of the medication to the individual participant for addressing the one or more current health concerns of the participant, wherein a medical and drug history of the individual participant that does not support use of the medication results in a lower clinical value, and wherein a medical and drug history that does support use of the medication results in a high clinical value, and wherein a lower clinical value determines a higher copayment and a high clinical value determines a lower copayment;

accessing the data platform to obtain financial information associated with the participant including an income level associated with the participant, wherein a higher income level determines a higher copayment and a lower income level determines a lower copayment;

determining a copayment amount for the participant requesting a medication based on both the determined current clinical value of the medication to the participant and the income level associated with the individual; and

wherein all steps of the method are performed by a mass customization infrastructure comprising a healthcare data platform and one or more computing devices, and wherein the infrastructure automatically integrates, analyzes and mines participant-specific clinical and financial data to determine the copayment for the participant requesting a medication in order to enhance the quality of healthcare.