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The American Journal of Managed Care November 2018
The American Journal of Managed Care November 2018
CLINICAL
David H. Smith, PhD, RPh; Jennifer L. Kuntz, PhD; Lynn L. DeBar, PhD, MPH; Jill Mesa; Xiuhai Yang, MS; Jennifer Schneider, MPH; Amanda Petrik, MS; Katherine Reese, PharmD; Lou Ann Thorsness, RPh; David Boardman, MD; and Eric S. Johnson, PhD
COMMENTARY
Anupam B. Jena, MD, PhD; Jacquelyn W. Chou, MPP, MPL; Lara Yoon, MPH; Wade M. Aubry, MD; Jan Berger, MD, MJ; Wayne Burton, MD; A. Mark Fendrick, MD; Donna M. Fick, RN, PhD; David Franklin, BA; Rebecca Killion, MA; Darius N. Lakdawalla, PhD; Peter J. Neumann, ScD; Kavita Patel, MD, MSHS; John Yee, MD, MPH; Brian Sakurada, PharmD; and Kristina Yu-Isenberg, PhD, MPH, RPh
From The Editorial Board
Glen D. Stettin, MD
LETTERS TO THE EDITORS
Daniel B. Wolfson, MHSA, Executive Vice President and COO, ABIM Foundation
METHODS
Kathryn E. McCollister, PhD; Jared A. Leff, MS; Xuan Yang, MPH, MHS; Joshua D. Lee, MD; Edward V. Nunes, MD; Patricia Novo, MPA, MPH; John Rotrosen, MD; Bruce R. Schackman, PhD; and Sean M. Murphy, PhD
TRENDS FROM THE FIELD
Guneet K. Jasuja, PhD; Omid Ameli, MD, MPH; Donald R. Miller, ScD; Thomas Land, PhD; Dana Bernson, MPH; Adam J. Rose, MD, MSc; Dan R. Berlowitz, MD, MPH; and David A. Smelson, PsyD
WEB EXCLUSIVE
Currently Reading
Effects of a Community-Based Care Management Model for Super-Utilizers
Purvi Sevak, PhD; Cara N. Stepanczuk, MPP; Katharine W.V. Bradley, PhD; Tim Day, MSPH; Greg Peterson, PhD; Boyd Gilman, PhD; Laura Blue, PhD; Keith Kranker, PhD; Kate Stewart, PhD; and Lorenzo Moreno, PhD
Kelly Gao; Gene Pellerin, MD; and Laurence Kaminsky, PhD
Jennifer Elston Lafata, PhD; Carrie A. Miller, PhD, MPH; Deirdre A. Shires, PhD; Karen Dyer, PhD; Scott M. Ratliff, MS; and Michelle Schreiber, MD
Patricia R. Salber, MD, MBA; Christobel E. Selecky, MA; Dirk Soenksen, MS, MBA; and Thomas Wilson, PhD, DrPH
Jinyoung Shin, MD, PhD; Hyeonyoung Ko, MD, MPH; Jeong Ah Kim, BS; Yun-Mi Song, MD, PhD; Jin Seok Ahn, MD, PhD; Seok Jin Nam, MD, PhD; and Jungkwon Lee, MD, PhD
Effects of a Community-Based Care Management Model for Super-Utilizers
Purvi Sevak, PhD; Cara N. Stepanczuk, MPP; Katharine W.V. Bradley, PhD; Tim Day, MSPH; Greg Peterson, PhD; Boyd Gilman, PhD; Laura Blue, PhD; Keith Kranker, PhD; Kate Stewart, PhD; and Lorenzo Moreno, PhD
A community-based care management program for high-risk patients reduced hospital readmissions and also likely reduced admissions and Medicare parts A and B spending.
ABSTRACT
Objectives: Medicare, Medicaid, and commercial plans have all explored ways to improve outcomes for patients with high costs and complex medical and social needs. The purpose of this study was to test the effectiveness of a high-intensity care management program that the Rutgers University Center for State Health Policy (CSHP) implemented as an adaptation of a promising model developed by the Camden Coalition of Healthcare Providers.
Study Design: We estimated the impact of the program on 6 utilization and spending outcomes for a subgroup of beneficiaries enrolled in Medicare fee-for-service (n = 149) and a matched comparison group (n = 1130).
Methods: We used Medicare claims for all analyses. We used propensity score matching to construct a comparison group of beneficiaries with baseline characteristics similar to those of program participants. We employed regression models to test the relationship between program enrollment and outcomes over a 12-month period while controlling for baseline characteristics.
Results: A test of joint significance across all outcomes showed that the CSHP program reduced service use and spending in aggregate (P = .012), although estimates for most of the individual measures were not statistically significant. Participants had 37% fewer unplanned readmissions (P = .086) than did comparison beneficiaries. Although we did not find statistically significant results for the other 5 outcomes, the CIs for these outcomes spanned substantively large effects.
Conclusions: Although these findings are mixed, they suggest that adaptations of the Camden model hold promise for reducing short-term service use and spending for Medicare super-utilizers.
Am J Manag Care. 2018;24(11):e365-e370
Objectives: Medicare, Medicaid, and commercial plans have all explored ways to improve outcomes for patients with high costs and complex medical and social needs. The purpose of this study was to test the effectiveness of a high-intensity care management program that the Rutgers University Center for State Health Policy (CSHP) implemented as an adaptation of a promising model developed by the Camden Coalition of Healthcare Providers.
Study Design: We estimated the impact of the program on 6 utilization and spending outcomes for a subgroup of beneficiaries enrolled in Medicare fee-for-service (n = 149) and a matched comparison group (n = 1130).
Methods: We used Medicare claims for all analyses. We used propensity score matching to construct a comparison group of beneficiaries with baseline characteristics similar to those of program participants. We employed regression models to test the relationship between program enrollment and outcomes over a 12-month period while controlling for baseline characteristics.
Results: A test of joint significance across all outcomes showed that the CSHP program reduced service use and spending in aggregate (P = .012), although estimates for most of the individual measures were not statistically significant. Participants had 37% fewer unplanned readmissions (P = .086) than did comparison beneficiaries. Although we did not find statistically significant results for the other 5 outcomes, the CIs for these outcomes spanned substantively large effects.
Conclusions: Although these findings are mixed, they suggest that adaptations of the Camden model hold promise for reducing short-term service use and spending for Medicare super-utilizers.
Am J Manag Care. 2018;24(11):e365-e370
