title: Value-based benefit design: using a predictive modeling approach to improve compliance.
abstract: BACKGROUND
  Increased medication compliance rates have been demonstrated to result in improved clinical outcomes and reduced overall medical expenditures. As such, managed care stakeholders should take the total value approach to benefit design and consider total medical costs beyond the cost of pharmacotherapy alone.
  
  
  OBJECTIVE
  To describe the value-based benefit design employed by Pitney Bowes (specifically, the predictive modeling approach), to improve medication compliance, and to report the results of this intervention.
  
  
  CONCLUSIONS
  Despite significant skepticism surrounding value-based benefit design, there is growing evidence that these plans can be used in conjunction with careful pharmacy management. In fact, value-based design provides a different lever on pharmacy management and allows for the appropriate drug to be channeled to the appropriate person. Studies demonstrating the adverse impact of high coinsurance levels further augment the argument for value-based benefit design. Value-based benefit design was employed at Pitney Bowes, a $6.1-billion global provider of integrated mailstream solutions, with noticeable success. Patients were either placed in a disease management program or in a secondary program promoting preventive care. The company selectively cut copays to achieve that end, and this total value approach translated into significant savings.
  
  
  CONCLUSIONS
  To develop a successful value-based benefit design, stakeholders cannot simply cut costs or cut copays. Action must be taken as part of a concerted program, coupled with disease management or similar interventions. "Value based" means that positive outcomes are the ultimate goal, and barriers to those positive outcomes must be addressed.
authors.affiliation: Strategic Health Innovations, Pitney Bowes, Stamford, CT 06926, USA. jack.mahoney@pb.com
authors.forename: John J
authors.initials: JJ
authors.lastname: Mahoney
mesh_terms: D003237:Connecticut; D017046:Cost Savings / Q000379:methods / Q000706:statistics & numerical data*; D003362:Cost-Benefit Analysis / Q000379:methods / Q000706:statistics & numerical data; D016527:Drug Costs / Q000706:statistics & numerical data*; D006801:Humans; D007354:Insurance, Major Medical / Q000706:statistics & numerical data*; D008329:Managed Care Programs / Q000191:economics / Q000458:organization & administration; D008962:Models, Theoretical; D009936:Organizational Innovation / Q000191:economics; D010349:Patient Compliance / Q000706:statistics & numerical data*