Author
Abstract
Health care spending for the nursing home sector has been an understudied topic despite institutionalized long-term care patients often facing higher mortality rates, having numerous and serious comorbidities, and accounting for over $194 billion dollars in personal health care expenditure just in 2018. Research on this population is increasing in importance as the U.S. population ages, but data limitations have constrained investigations in this area. To improve measurement for this significant sector of health care, this study utilizes Medicaid Analytic eXtract (MAX) Long-Term Care (LT) claims for 2000–2005, 2008, and 2011, and focuses on long-term care dual MedicareMedicaid residents. Diagnoses from each claim are used to appropriate total costs to 260 Clinical Classification Software (CCS) categories. The long-term care population share of spending for many of these conditions greatly exceeds that of the general non-institutionalized U.S. population. The result shows two broad condition categories dominate spending for this population: circulatory and mental health conditions, each category accounting for about 20 percent of long-term care expenditures in 2011. Among circulatory conditions, treated prevalence for severe circulatory conditions (for example, strokes) has fallen while treated prevalence for early-stage circulatory conditions (for example, high cholesterol) has risen. Approximately 43 percent of residents received a mental health diagnosis in 2011 and conditions such as anxiety, mood disorders, and dementia have grown in importance over the study period. Overall, this paper demonstrates how these methods and MAX LT file may be used to track spending-by-disease for this increasingly important sector.
Suggested Citation
Abe C. Dunn & Peter Shieh & Lasanthi Fernando, 2020.
"Spending by Condition for the Long-Term Care Population Using Medicaid Claims,"
BEA Working Papers
0180, Bureau of Economic Analysis.
Handle:
RePEc:bea:wpaper:0180
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