Online ISSN: 1099-176X Print
ISSN: 1091-4358 Copyright © 2006 ICMPE. |
The Implementation of Managed Behavioral Healthcare in Colorado and the Effects on Older Medicaid Beneficiaries |
Brian Kaskie,1 Neal Wallace,2 Soo Kang,3 Joan Bloom3 |
1Ph.D., Department of
Health Management and Policy, University of Iowa, Iowa, IA, USA |
* Correspondence to: Brian Kaskie, Ph.D., Department of Health Management
and Policy, The University of Iowa, 200 Hawkins Drive, E206 GH, Iowa City, IA
52242, USA
Tel.: +1-319-384 5134
Fax: +1-319-384 5125
E-mail: brian-kaskie@uiowa.edu
Source of Funding: This research was funded through a pilot grant awarded to the first author by the University of California Berkeley, Center for Mental Health services.
Abstract |
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Background: One of five persons over the age of 65 experiences a diagnosable form of mental illness. Yet their access to and use of specialty services are the lowest among all age groups. It is unclear how managed behavioral healthcare has affected this problematic situation. The Colorado Medicaid Mental Health Capitation Pilot Program, implemented in 1995, provided an opportunity to investigate the impact of managed behavioral healthcare on older Medicaid beneficiaries. Study Aims: This study compared two capitated administrative models of Medicaid mental health service delivery to a traditional fee-for-service model, and specifically focused on how these models shaped service use and expenditure patterns for Medicaid beneficiaries over the age of 65. Methods: This study employed a quasi-experimental, pre-post design with a non-equivalent comparison group that reflects the implementation of capitation financing in some parts of Colorado and not others. A difference in difference specification was used to identify the effects of capitation under two administrative models relative to areas remaining under fee-for-service reimbursement. Logistic and Ordinary Least Squares regression were used to estimate service use and (logged) expenditures per repeat and total number of service users. Generalized corrections for heteroskedasticity and repeated observations were applied. Probabilities and average user expenditures were derived from regression results with a fixed case-mix and compared to actuals. Results: The analyses indicated that one of the capitated administrative models increased the total number of older beneficiaries who used services while the total number of service users decreased in the other capitated models. Both capitated models reduced repeat use and expenditures for specialty mental health services relative to the traditional FFS model. Discussion: Capitation had the expected effect of reducing the duration and intensity of treatment. Clear differences between the two capitated administrative models emerged that appeared consistent with their management philosophies. Measured effects were limited to services covered by capitation and may have been influenced by the observational design. Overall results were somewhat different from those pertaining to younger populations studied in Colorado. Implications for Health Care Provision and Use: While capitation clearly reduced total expenditures for older beneficiaries, its influence on specific treatment process measures such as user expenditures, repeat users and total users may vary considerably across treatment systems. Notably, capitation may result in increases or decreases in total users within a specific sub-population such as elders. Implications for Health Policies: This analysis provides critical information for those state mental health and Medicaid agencies that are expanding the application of managed behavioral healthcare within a demographic environment where the population of older adults with mental illnesses is increasing. Financing, organization and their impact on specific treatment populations need to be considered in developing and applying managed behavioral health care. Implications for Further Research: The differential effects on elders by administrative models needs further explication and should be measured against clinical and social outcomes as well as the effect of other sources of financing and service substitution.
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Received 18 April 2005; accepted 20 December 2005
Copyright © 2006 ICMPE