title: An Empirical Framework for Breast Screening Bundled Payments.
abstract: OBJECTIVE
  In an effort to curb health care costs and improve the quality of care, bundled payment models are becoming increasingly adopted, but to date, they have focused primarily on treatment episodes and primary care providers. To achieve current Medicare goals of transitioning fee-for-service payments to alternative payment models, however, a broader range of patient episodes and specialty physicians will need opportunities to participate. The authors explore breast cancer screening episodes as one such opportunity.
  
  
  METHODS
  The authors developed a bundled payment model for breast cancer screening and calibrated it using both a national sample of retrospective Medicare claims data and data from a private health system. The model includes alternative screening episode definitions, methods for calibrating prices, and an examination of risk and can serve as a general framework on which other cancer screening bundles could be crafted.
  
  
  RESULTS
  The utilization of services associated with breast cancer screening and diagnosis is stable over time. The inclusion of high-risk patients in breast screening bundles did not cause substantial changes in estimated bundle prices. However, prices are sensitive to the choice of services included in the bundle.
  
  
  CONCLUSIONS
  Breast cancer screening may provide a mechanism to expand the use of bundled payments in radiology and could serve as a framework for other episodic specialty bundles. Because screening bundles include costs for follow-up diagnostic imaging in addition to the initial screening mammographic examination, patient adherence to screening guidelines may improve, which may have profound effects on public health.
authors.affiliation: Harvey L. Neiman Health Policy Institute, Reston, Virginia; Department of Health Administration and Policy, George Mason University, Fairfax, Virginia. Electronic address: dhughes@neimanhpi.org.
authors.forename: Danny R
authors.initials: DR
authors.lastname: Hughes
authors.affiliation: Harvey L. Neiman Health Policy Institute, Reston, Virginia; Department of Health Administration and Policy, George Mason University, Fairfax, Virginia.
authors.forename: Miao
authors.initials: M
authors.lastname: Jiang
authors.affiliation: Department of Radiology, Weill Cornell Medicine, New York, New York.
authors.forename: Geraldine
authors.initials: G
authors.lastname: McGinty
authors.affiliation: Department of Radiology, Tufts University School of Medicine, Boston, Massachusetts.
authors.forename: Sanjay K
authors.initials: SK
authors.lastname: Shetty
authors.affiliation: Harvey L. Neiman Health Policy Institute, Reston, Virginia; Deprtament of Radiology, Emory University School of Medicine, Atlanta, Georgia.
authors.forename: Richard
authors.initials: R
authors.lastname: Duszak
mesh_terms: D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000191:economics*; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D055088:Early Detection of Cancer / Q000191:economics*; D018588:Fee-for-Service Plans / Q000191:economics; D006278:Medicare / Q000191:economics*; D018803:Models, Economic; D064872:Patient Care Bundles / Q000191:economics*; D012051:Reimbursement Mechanisms / Q000191:economics*; D014481:United States
keywords: Bundled payments; alternative payment models; breast cancer; cancer screening; mammography