Literature DB >> 30020755

Forgotten patients: ACO attribution omits those with low service use and the dying.

Mariétou H Ouayogodé1, Ellen Meara, Chiang-Hua Chang, Stephanie R Raymond, Julie P W Bynum, Valerie A Lewis, Carrie H Colla.   

Abstract

OBJECTIVES: Alternative payment models, such as accountable care organizations, hold provider groups accountable for an assigned patient population, but little is known about unassigned patients. We compared clinical and utilization profiles of patients attributable to a provider group with those of patients not attributable to any provider group. STUDY
DESIGN: Cross-sectional study of 2012 Medicare fee-for-service beneficiaries 21 years and older.
METHODS: We applied the Medicare Shared Savings Program attribution approach to assign beneficiaries to 2 mutually exclusive categories: attributable or unattributable. We compared attributable and unattributable beneficiaries according to demographics, dual eligibility for Medicaid, nursing home residency, clinical comorbidities, annual service utilization, annual spending, and 1- and 2-year mortality. We estimated multivariate regression models describing correlates of attribution status.
RESULTS: Most beneficiaries (88%) were attributable to a provider group. The remaining 12% were unattributable. Beneficiaries unattributable to any provider group were more likely to be younger, male, and from a minority group; to have disability as the basis for enrollment; and to live in high-poverty areas. Unattributable beneficiaries included 3 distinct subgroups: nonusers of care, decedents, and those with healthcare service use but no qualifying evaluation and management visits. Many unattributable Medicare beneficiaries had minimal use of healthcare services, with the exception of a small subgroup of beneficiaries who died within the attribution year.
CONCLUSIONS: Attribution approaches that more fully capture unattributable patients with low service use and patients near the end of life should be considered to reward population health efforts and improve end-of-life care.

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Mesh:

Year:  2018        PMID: 30020755      PMCID: PMC6089367     

Source DB:  PubMed          Journal:  Am J Manag Care        ISSN: 1088-0224            Impact factor:   2.229


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