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Algorithm for Improving Beneficiary Identifier Quality in Medicaid Administrative Data
Konstantin Kunze1, Meredith C B Adams2, Robert W Hurley2
1University of Rochester.
None:
Accurately linking Medicaid beneficiaries over time and across administrative files is essential for health policy research, yet the federally assigned Chronic Conditions Warehouse (CCW) identifier and state-assigned identifier are subject to systematic data quality problems that can lead to inaccurate linkages and biased analyses. Drawing on MAX Person Summary files (1999-2015) and T-MSIS Analytic Files (2014-2022), this paper documents four key identifier problems: identifier reassignment beginning in 2020, missing identifiers, discordant identifiers, and identifier clustering. It provides a structured algorithm for correcting each. Our corrections are applied to enrollment, utilization, and mortality files, and result in a composite identifier that allows beneficiaries to be uniquely and reliably tracked over time and across files.
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