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.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Female
  • Health Expenditures / statistics & numerical data*
  • Humans
  • Insurance Claim Review / statistics & numerical data
  • Insurance Coverage / economics*
  • Insurance Coverage / statistics & numerical data
  • Insurance, Health / economics*
  • Insurance, Health / statistics & numerical data
  • Male
  • Massachusetts
  • Medicaid / statistics & numerical data
  • Medicare / statistics & numerical data
  • Middle Aged
  • Patient-Centered Care / economics
  • Patient-Centered Care / organization & administration*
  • Primary Health Care / economics
  • Primary Health Care / organization & administration*
  • Propensity Score
  • Risk Adjustment
  • United States