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Article
Bending the cost curve? Results from a comprehensive primary care payment pilot
University of Massachusetts Medical School Faculty Publications
  • Sonal Vats, Boston University
  • Arlene S. Ash, University of Massachusetts Medical School
  • Randall P. Ellis, Boston University
UMMS Affiliation
Department of Quantitative Health Sciences
Date
11-1-2013
Document Type
Article
Medical Subject Headings
Adult; Aged; Algorithms; Female; Health Expenditures; Humans; Insurance Claim Review; Insurance Coverage; Insurance, Health; Male; Massachusetts; Medicaid; Medicare; Middle Aged; Patient-Centered Care; Primary Health Care; Propensity Score; Risk Adjustment; United States
Abstract
BACKGROUND: There is much interest in understanding how using bundled primary care payments to support a patient-centered medical home (PCMH) affects total medical costs. RESEARCH DESIGN AND SUBJECTS: We compare 2008-2010 claims and eligibility records on about 10,000 patients in practices transforming to a PCMH and receiving risk-adjusted base payments and bonuses, with similar data on approximately 200,000 patients of nontransformed practices remaining under fee-for-service reimbursement. METHODS: We estimate the treatment effect using difference-in-differences, controlling for trend, payer type, plan type, and fixed effects. We weight to account for partial-year eligibility, use propensity weights to address differences in exogenous variables between control and treatment patients, and use the Massachusetts Health Quality Project algorithm to assign patients to practices. RESULTS: Estimated treatment effects are sensitive to: control variables, propensity weighting, the algorithm used to assign patients to practices, how we address differences in health risk, and whether/how we use data from enrollees who join, leave, or change practices. Unadjusted PCMH spending reductions are 1.5% in year 1 and 1.8% in year 2. With fixed patient assignment and other adjustments, medical spending in the treatment group seems to be 5.8% (P=0.20) lower in year 1 and 8.7% (P=0.14) lower in year 2 than for propensity-weighted, continuously enrolled controls; the largest proportional 2-year reduction in spending occurs in laboratory test use (16.5%, P=0.02). CONCLUSIONS: Although estimates are imprecise because of limited data and quasi-experimental design, risk-adjusted bundled payment for primary care may have dampened spending growth in 3 practices implementing a PCMH.
Comments

Citation: Vats S, Ash AS, Ellis RP. Bending the cost curve? Results from a comprehensive primary care payment pilot. Med Care. 2013 Nov;51(11):964-9. doi:10.1097/MLR.0b013e3182a97bdc. Link to article on publisher's site

Related Resources
Link to article in PubMed
Keywords
  • UMCCTS funding
PubMed ID
24113816
Citation Information
Sonal Vats, Arlene S. Ash and Randall P. Ellis. "Bending the cost curve? Results from a comprehensive primary care payment pilot" Vol. 51 Iss. 11 (2013) ISSN: 1537-1948
Available at: http://works.bepress.com/arlene_ash/162/