title: Patient-Centered Medical Home Features and Health Care Expenditures of Medicare Beneficiaries with Chronic Disease Dyads.
abstract: Three out of 4 Medicare beneficiaries have multiple chronic conditions, and managing the care of this growing population can be complex and costly because of care coordination challenges. This study assesses how different elements of the patient-centered medical home (PCMH) model may impact the health care expenditures of Medicare beneficiaries with the most prevalent chronic disease dyads (ie, co-occurring high cholesterol and high blood pressure, high cholesterol and heart disease, high cholesterol and diabetes, high cholesterol and arthritis, heart disease and high blood pressure). Data from the 2007-2011 Medical Expenditure Panel Survey suggest that increased access to PCMH features may differentially impact the distribution of health care expenditures across health care service categories depending on the combination of chronic conditions experienced by each beneficiary. For example, having no difficulty contacting a provider after regular hours was associated with significantly lower outpatient expenditures for beneficiaries with high cholesterol and diabetes (n = 635; P = 0.038), but it was associated with significantly higher inpatient expenditures for beneficiaries with high blood pressure and high cholesterol (n = 1599; P = 0.015), and no significant differences in expenditures in any category for beneficiaries with high blood pressure and heart disease (n = 1018; P > 0.05 for all categories). However, average total health care expenditures are largely unaffected by implementing the PCMH features considered. Understanding how the needs of Medicare beneficiaries with multiple chronic conditions can be met through the adoption of the PCMH model is important not only to be able to provide high-quality care but also to control costs. (Population Health Management 2016;19:206-211).
authors.affiliation: 1 Mayo Clinic, Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery , Rochester, Minnesota.|2 Office of the Chief Quality Officer, Baylor Scott & White Health , Dallas, Texas.
authors.forename: Lindsey M
authors.initials: LM
authors.lastname: Philpot
authors.affiliation: 3 Department of Health Management and Policy, University of North Texas Health Science Center , School of Public Health, Fort Worth, Texas.|4 Department of Behavioral Health Analytics, Magellan Health Inc. , Columbia, Maryland.
authors.forename: Erica L
authors.initials: EL
authors.lastname: Stockbridge
authors.affiliation: 5 Center for Health Innovation , The New York Academy of Medicine, New York, New York.|6 Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai , New York, New York.
authors.forename: Norma A
authors.initials: NA
authors.lastname: Padrón
authors.affiliation: 5 Center for Health Innovation , The New York Academy of Medicine, New York, New York.|6 Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai , New York, New York.|7 Leonard Davis Institute of Health Economics, University of Pennsylvania , Philadelphia, Pennsylvania.
authors.forename: José A
authors.initials: JA
authors.lastname: Pagán
mesh_terms: D019538:Health Care Surveys; D005102:Health Expenditures / Q000706:statistics & numerical data; D006297:Health Services Accessibility; D006801:Humans; D006278:Medicare; D000071069:Multiple Chronic Conditions / Q000191:economics*; D018802:Patient-Centered Care; D014481:United States