Browsing by Author "Cheng, Lung-I"
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Item Impact of Medicare Part D on prescription use, health care expenditures, and health services utilization : national estimates for Medicare beneficiaries and vulnerable populations, 2002 to 2009(2012-08) Cheng, Lung-I; Rascati, Karen L.; Barner, Jamie C.; Lawson, Kenneth A.; Strassels, Scott A.; Warner, David C.The purpose of this study was to investigate the impact of Medicare Part D on prescription utilization, health services utilization, and health care expenditures in the general Medicare population – as well as Medicare sub-populations, including non-Hispanic blacks (NHBs), Hispanics, near poor individuals, and persons with higher disease burden. A retrospective analysis of Medicare beneficiaries (N=32,228) was conducted using the Medical Expenditure Panel Survey 2002 to 2009 data. Multivariable quantile regression was used to estimate the following outcomes, adjusting for socio-demographic characteristics: 1) number of prescription fills; 2) out-of-pocket (OOP) drug expenditures; 3) total drug expenditures; 4) OOP health care expenditures; 5) total health care expenditures; 6) number of hospitalizations; and 7) number of emergency department (ED) visits between the pre-Part D (2002-2005) and post-Part D (2006-2009) periods. All expenditures were inflation-adjusted to 2009 dollars. The average age of the study sample was 71.0 (SD=14.5). In the general Medicare population, Part D was associated with decreases in OOP drug expenditures (-25.7% to -33.6%; p<0.0001) and OOP health care expenditures (-22.1% to -24.3%; p<0.0001) as well as increases in the number of prescription fills (5.8% to 8.4%; p<0.0001) and total drug expenditures (75th percentile: 5.5%; 90th percentile: 10.2%; p<0.0001). Part D was not associated with changes in total health care expenditures in the general Medicare population. Changes in hospitalizations and ED visits were tested at the 90th percentile, and the results were not statistically significant. In sub-group analyses based on race/ethnicity, non-Hispanic whites (NHWs) experienced more significant reductions in OOP drug and/or health care expenditures when compared with NHBs and Hispanics. Near poor beneficiaries experienced larger reductions in OOP drug expenditures than beneficiaries with middle- to high-income, while Medicare beneficiaries with three or more conditions experienced more substantial reductions in OOP drug and OOP health expenditures after Part D was introduced, compared with those with fewer than three conditions. Part D resulted in increases in medication utilization and reductions in OOP drug and OOP health care expenditures among Medicare beneficiaries. Part D was not associated with differences in total health care spending. The effects of Part D were more pronounced in Medicare subgroups, including NHWs, near poor individuals, and patients with higher chronic disease burden.Item Performance of comorbidity adjustment measures to predict healthcare utilization and expenditures for patients with diabetes using a large administrative database(2010-12) Cheng, Lung-I; Rascati, Karen L.; Barner, Jamie C.; Lawson, Kenneth A.Objective: The objective of this study was to compare the use of different comorbidity measures to predict future healthcare utilization and expenditures for diabetic patients. Methods: This was a retrospective study that included 8,704 diabetic patients enrolled continuously for three years in the Department of Defense TRICARE program. Administrative claims data were used to calculate six comorbidity measures: number of distinct medications, index-year healthcare expenditures, two versions of the Charlson Comorbidity Index (CCI), and two versions of the Chronic Disease Score (CDS). Linear regression models were used to estimate three health outcomes for one- and two-year post-index periods: healthcare expenditures (COST), number of hospitalizations (HOS), and number of emergency department visits (ED). Logistic regression models were used to estimate binary outcomes (above or below the 90th percentile of COST; [greater than or equal to] 1 HOS or none; [greater than or equal to] 1 ED or none). Comparisons were based on adjusted R², areas under the receiver-operator-curve (c statistics), and the Hosmer-Lemeshow goodness-of-fit tests. Results: The study population had a mean age of 51.0 years (SD = 10.5), and 46.3 percent were male. After adjusting for age and sex, the updated CCI was the best predictor of one-year and two-year HOS (adjusted R² = 8.1%, 9.3%), the number of distinct medications was superior in predicting one-year and two-year ED (adjusted R² = 9.9%, 12.4%), and the index-year healthcare expenditures explained the most variance in one-year and two-year COST (adjusted R² = 35.6%, 31.6%). In logistic regressions, the number of distinct medications was the best predictor of one-year and two-year risks of emergency department use (c = 0.653, 0.654), but the index-year healthcare expenditures performed the best in predicting one-year and two-year risks of hospitalizations (c = 0.684, 0.676) and high-expenditure cases (c = 0.810, 0.823). The updated CCI consistently outperformed the original CCI in predicting the outcomes of interest. Conclusions: In a diabetic population under age 65, the number of distinct medications and baseline healthcare expenditures appeared to have superior or similar powers compared to the CCI or CDS for the prediction of future healthcare utilization and expenditures. The updated CCI was a better predictor than the original CCI in this population.