Title

Bending the cost curve? Results from a comprehensive primary care payment pilot

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

Disciplines

Health Services Administration | Primary Care

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