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Effects of a New York Medicaid Care Management Program on Substance Use Disorder Treatment Services and Medicaid Spending: Implications for Defining the Target Population.
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- المؤلفون: Neighbors, Charles J.1,2 ; Yerneni, Rajeev1; Yi Sun3; Sugy Choi1,2; Burke, Constance3; O'Grady, Megan A.1; McDonald, Rebecca1,4; Morgenstern, Jon1,5
- المصدر:
Substance Abuse: Research & Treatment. Jan-Dec2022, Vol. 16, p1-9. 9p.
- الموضوع:
- معلومة اضافية
- الموضوع:
- نبذة مختصرة :
AIMS: We examined the effects of a statewide New York (NY) care management (CM) program for substance use disorder (SUD), Managed Addiction Treatment Services (MATS), on SUD treatment services' utilization and spending among patients with a recent history of high Medicaid spending and among those for whom a predictive algorithm indicates a higher probability of outlier spending in the following year. METHODS: We applied difference-in-difference analyses with propensity score matching using NY Medicaid claims data and a state registry of SUD-treatment episodes from 2006 to 2009. A total of 1263 CM enrollees with high SUD treatment spending (>$10K) in the prior year and a matched comparison group were included in the analysis. Crisis care utilization for SUD (detoxification and hospitalizations), outpatient SUD treatment, and Medicaid spending were examined over 12 months among both groups. CM effects among predicted high-future-spending patients (HFS) were also analyzed. RESULTS: CM increased outpatient SUD treatment visits by approximately 10.5 days (95% CI = 0.9, 20.0). CM crisis care and spending outcomes were not statistically different from comparison since both conditions had comparable pre-post declines. Conversely, CM significantly reduced SUD treatment spending by approximately $955 (95% CI = -1518, -391) and reduced days of detox utilization by about 1.0 days (95% CI = -1.9, -0.1) among HFS. CONCLUSION: Findings suggest that CM can reduce SUD treatment spending and utilization when targeted at patients with a greater likelihood of high future spending, indicating the potential value of predictive models to select CM patients. [ABSTRACT FROM AUTHOR]
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