Kimberly Danae Cauley Narain1,2, Jessica Harwood3, Carol Mangione3,4, O Kenrik Duru3, Susan Ettner3,4. 1. Division of General Internal Medicine and Health Services Research (GIM/HSR), Department of Medicine, University of California Los Angeles, 1100 Glendon Ave., Suite 850, Los Angeles, CA, 90024, USA. KNarain@mednet.ucla.edu. 2. Center for Health Advancement, Fielding School of Public Health, University of California Los Angeles, 650 Charles Young Dr., 31-269 CHS, Box 951772, Los Angeles, CA, 90095-1772, USA. KNarain@mednet.ucla.edu. 3. Division of General Internal Medicine and Health Services Research (GIM/HSR), Department of Medicine, University of California Los Angeles, 1100 Glendon Ave., Suite 850, Los Angeles, CA, 90024, USA. 4. Health Policy and Management, Fielding School of Public Health, UCLA, 650 Charles Young Dr. S., 31-269 CHS, Box 951772, Los Angeles, CA, 90095-1772, USA.
Abstract
BACKGROUND: To determine if requiring Dual Eligible Special Need Plans (D-SNPs) to receive approval from the National Committee of Quality Assurance and contract with state Medicaid agencies impacts healthcare utilization. METHODS: We use a Multiple Interrupted Time Series to examine the association of D-SNP regulations with dichotomized measures of emergency room (ER) and hospital utilization. Our treatment group is elderly D-SNP enrollees. Our comparison group is near-elderly (ages 60-64) beneficiaries enrolled in Medicaid Managed Care plans (N = 360,405). We use segmented regression models to estimate changes in the time-trend and slope of the outcomes associated with D-SNP regulations, during the post-implementation (2012-2015) period, relative to the pre-implementation (2010-2011) period. Models include a treatment-status indicator, a monthly time-trend, indicators and splines for the post-period and the interactions between these variables. We conduct the following sensitivity analyses: (1) Re-estimating models stratified by state (2) Estimating models including interactions of D-SNP implementation variables with comorbidity count to assess for differential D-SNP regulation effects across comorbidity level. (3) Re-estimating the models stratifying by race/ethnicity and (4) Including a transition period (2012-2013) in the model. RESULTS: We do not find any statistically significant changes in ER or hospital utilization associated with D-SNP regulation implementation in the broad D-SNP population or among specific racial/ethnic groups; however, we do find a reduction in hospitalizations associated with D-SNP regulations in New Jersey (DD level = - 3.37%; p = 0.02)/(DD slope = - 0.23%; p = 0.01) and among individuals with higher, relative to lower levels of co-morbidity (DDD slope = - 0.06%; p = 0.01). CONCLUSIONS: These findings suggest that the impact of D-SNP regulations varies by state. Additionally, D-SNP regulations may be particularly effective in reducing hospital utilization among beneficiaries with high levels of co-morbidity.
BACKGROUND: To determine if requiring Dual Eligible Special Need Plans (D-SNPs) to receive approval from the National Committee of Quality Assurance and contract with state Medicaid agencies impacts healthcare utilization. METHODS: We use a Multiple Interrupted Time Series to examine the association of D-SNP regulations with dichotomized measures of emergency room (ER) and hospital utilization. Our treatment group is elderly D-SNP enrollees. Our comparison group is near-elderly (ages 60-64) beneficiaries enrolled in Medicaid Managed Care plans (N = 360,405). We use segmented regression models to estimate changes in the time-trend and slope of the outcomes associated with D-SNP regulations, during the post-implementation (2012-2015) period, relative to the pre-implementation (2010-2011) period. Models include a treatment-status indicator, a monthly time-trend, indicators and splines for the post-period and the interactions between these variables. We conduct the following sensitivity analyses: (1) Re-estimating models stratified by state (2) Estimating models including interactions of D-SNP implementation variables with comorbidity count to assess for differential D-SNP regulation effects across comorbidity level. (3) Re-estimating the models stratifying by race/ethnicity and (4) Including a transition period (2012-2013) in the model. RESULTS: We do not find any statistically significant changes in ER or hospital utilization associated with D-SNP regulation implementation in the broad D-SNP population or among specific racial/ethnic groups; however, we do find a reduction in hospitalizations associated with D-SNP regulations in New Jersey (DD level = - 3.37%; p = 0.02)/(DD slope = - 0.23%; p = 0.01) and among individuals with higher, relative to lower levels of co-morbidity (DDD slope = - 0.06%; p = 0.01). CONCLUSIONS: These findings suggest that the impact of D-SNP regulations varies by state. Additionally, D-SNP regulations may be particularly effective in reducing hospital utilization among beneficiaries with high levels of co-morbidity.
Authors: David J Nyweide; Denise L Anthony; Julie P W Bynum; Robert L Strawderman; William B Weeks; Lawrence P Casalino; Elliott S Fisher Journal: JAMA Intern Med Date: 2013-11-11 Impact factor: 21.873