title: Risk-adjustment methods for all-payer comparative performance reporting in Vermont.
abstract: As the emphasis in health reform shifts to value-based payments, especially through multi-payer initiatives supported by the U.S. Center for Medicare & Medicaid Innovation, and with the increasing availability of statewide all-payer claims databases, the need for an all-payer, "whole-population" approach to facilitate the reporting of utilization, cost, and quality measures has grown. However, given the disparities between the different populations served by Medicare, Medicaid, and commercial payers, risk-adjustment methods for addressing these differences in a single measure have been a challenge.
  
  
  
  This study evaluated different levels of risk adjustment for primary care practice populations - from basic adjustments for age and gender to a more comprehensive "full model" risk-adjustment method that included additional demographic, payer, and health status factors. It applied risk adjustment to populations attributed to patient-centered medical homes (283,153 adult patients and 78,162 pediatric patients) in the state of Vermont that are part of the Blueprint for Health program. Risk-adjusted expenditure and utilization outcomes for calendar year 2014 were reported in 102 adult and 56 pediatric primary-care comparative practice profiles.
  
  
  
  Using total expenditures as the dependent variable for the adult population, the r2for the model adjusted for age and gender was 0.028. It increased to 0.265 with the additional adjustment for 3M Clinical Risk Groups and to 0.293 with the full model. For the adult population at the practice level, the no-adjustment model had the highest variation as measured by the coefficient of variation (18.5) compared to the age and gender model (14.8); the age, gender, and CRG model (13.0); and the full model (11.7). Similar results were found for the pediatric population practices.
  
  
  
  Results indicate that more comprehensive risk-adjustment models are effective for comparing cost, utilization, and quality measures across multi-payer populations. Such evaluations will become more important for practices, many of which do not distinguish their patients by payer type, and for the implementation of incentive-based or alternative payment systems that depend on "whole-population" outcomes. In Vermont, providers, accountable care organizations, policymakers, and consumers have used Blueprint profiles to identify priorities and opportunities for improving care in their communities.
authors.affiliation: Onpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA. kfinison@onpointhealthdata.org.
authors.forename: Karl
authors.identifier: 0000-0002-5928-4445
authors.initials: K
authors.lastname: Finison
authors.affiliation: Vermont Blueprint for Health, 280 State Dr. Waterbury, Vermont, 05671, USA.
authors.forename: MaryKate
authors.initials: M
authors.lastname: Mohlman
authors.affiliation: U.S. Department Health and Human Services, Vermont Blueprint for Health. Office of the National Coordinator for Health Information Technology, 330 C Street, SW; Floor 7, Washington, DC, 20024, USA.
authors.forename: Craig
authors.initials: C
authors.lastname: Jones
authors.affiliation: Onpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
authors.forename: Melanie
authors.initials: M
authors.lastname: Pinette
authors.affiliation: Onpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
authors.forename: David
authors.initials: D
authors.lastname: Jorgenson
authors.affiliation: Onpoint Health Data, 254 Commercial Street, Suite 257, Portland, ME, 04101, USA.
authors.forename: Amy
authors.initials: A
authors.lastname: Kinner
authors.affiliation: Vermont Blueprint for Health, 280 State Dr. Waterbury, Vermont, 05671, USA.
authors.forename: Tim
authors.initials: T
authors.lastname: Tremblay
authors.affiliation: The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth Hitchcock Medical Center, Lebanon, NH, 03766, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Gottlieb
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003365:Costs and Cost Analysis; D005260:Female; D018166:Health Care Reform / Q000191:economics; D005102:Health Expenditures; D006801:Humans; D007223:Infant; D008297:Male; D008484:Medicaid / Q000191:economics*; D006278:Medicare / Q000191:economics*; D008875:Middle Aged; D011320:Primary Health Care / Q000191:economics*; D012052:Reimbursement, Incentive; D020379:Risk Adjustment / Q000191:economics / Q000379:methods; D014481:United States; D014707:Vermont; D055815:Young Adult
keywords: APCD; Accountable care; Population health; Primary care practice; Risk adjustment