Bending the cost curve? Results from a comprehensive primary care payment pilot
dc.contributor.author | Vats, Sonal | |
dc.contributor.author | Ash, Arlene S. | |
dc.contributor.author | Ellis, Randall P. | |
dc.date | 2022-08-11T08:08:29.000 | |
dc.date.accessioned | 2022-08-23T15:56:50Z | |
dc.date.available | 2022-08-23T15:56:50Z | |
dc.date.issued | 2013-11-01 | |
dc.date.submitted | 2013-12-23 | |
dc.identifier.citation | <p>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. <a href="http://dx.doi.org/10.1097/MLR.0b013e3182a97bdc" target="_blank">Link to article on publisher's site</a></p> | |
dc.identifier.issn | 1537-1948 | |
dc.identifier.doi | 10.1097/MLR.0b013e3182a97bdc | |
dc.identifier.pmid | 24113816 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14038/30056 | |
dc.description.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. | |
dc.language.iso | en_US | |
dc.publisher | Lippincott Williams & Wilkins | |
dc.relation | <p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=24113816&dopt=Abstract">Link to article in PubMed</a></p> | |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845668/ | |
dc.subject | Adult | |
dc.subject | Aged | |
dc.subject | Algorithms | |
dc.subject | Female | |
dc.subject | Health Expenditures | |
dc.subject | Humans | |
dc.subject | Insurance Claim Review | |
dc.subject | Insurance Coverage | |
dc.subject | Insurance, Health | |
dc.subject | Male | |
dc.subject | Massachusetts | |
dc.subject | Medicaid | |
dc.subject | Medicare | |
dc.subject | Middle Aged | |
dc.subject | Patient-Centered Care | |
dc.subject | Primary Health Care | |
dc.subject | Propensity Score | |
dc.subject | Risk Adjustment | |
dc.subject | United States | |
dc.subject | UMCCTS funding | |
dc.subject | Health Services Administration | |
dc.subject | Primary Care | |
dc.title | Bending the cost curve? Results from a comprehensive primary care payment pilot | |
dc.type | Journal Article | |
dc.source.journaltitle | Medical care | |
dc.source.volume | 51 | |
dc.source.issue | 11 | |
dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/faculty_pubs/290 | |
dc.identifier.contextkey | 4943189 | |
html.description.abstract | <p>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.</p> <p>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.</p> <p>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.</p> <p>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).</p> <p>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.</p> | |
dc.identifier.submissionpath | faculty_pubs/290 | |
dc.contributor.department | Department of Quantitative Health Sciences | |
dc.source.pages | 964-9 |