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Association of Medicare enrollment with increased inpatient coding intensity
Michael I Ellenbogen1, Daniel J Brotman2
1Department of Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Meyer 8-134P, Baltimore, MD 21287.
Objectives:
Significant variation in coding intensity exists across patients and institutions, with important implications for reimbursement and risk-adjusted quality metrics. The degree to which coding intensity for hospitalized patients may be a function of primary payer is not well understood. We sought to measure differences in coding intensity between commercially insured and Medicare, Medicaid and Medicare, and self-pay and Medicare inpatient encounters for the same cohort of patients.
Study Design:
Regression discontinuity, leveraging the fact that patients typically enroll in Medicare at age 65 years.
Methods:
A multivariable linear regression was estimated to evaluate the relationship between the outcomes of interest and primary payer, controlling for age, age by payer interaction term, and inpatient visit count. Our analysis included Florida inpatients with at least 1 commercially insured, Medicaid, or self-pay inpatient hospitalization before age 65 years and at least 1 inpatient Medicare hospitalization at 65 years and older, with patients serving as their own controls. The outcome of interest was the number of hospital discharge diagnoses. Outcomes were measured separately for each group (commercial insurance to Medicare, Medicaid to Medicare, and self-pay to Medicare).
Results:
Medicare inpatient encounters were associated with 0.8 (95% CI, 0.4-1.2), 1.0 (95% CI, 0.5-1.5), and 2.0 (95% CI, 1.2-2.8) more discharge diagnoses than commercially insured, Medicaid, and self-pay inpatient encounters, respectively.
Conclusions:
Our findings suggest that Medicare inpatient encounters are associated with higher coding intensity than commercially insured, Medicaid, or self-pay inpatient encounters for those same individuals prior to age 65 years. This has important implications for the impact that insurance status may have on risk-adjusted quality measures.
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