OBJECTIVE: To develop an instrument to characterize public sector managed behavioral health care arrangements to capture key differences between managed and "unmanaged" care and among managed care arrangements. STUDY DESIGN: The instrument was developed by a multi-institutional group of collaborators with participation of an expert panel. Included are six domains predicted to have an impact on access, service utilization, costs, and quality. The domains are: characteristics of the managed care plan, enrolled population, benefit design, payment and risk arrangements, composition of provider networks, and accountability. Data are collected at three levels: managed care organization, subcontractor, and network of service providers. DATA COLLECTION METHODS: Data are collected through contract abstraction and key informant interviews. A multilevel coding scheme is used to organize the data into a matrix along key domains, which is then reviewed and verified by the key informants. PRINCIPAL FINDINGS: This instrument can usefully differentiate between and among Medicaid fee-for-service programs and Medicaid managed care plans along key domains of interest. Beyond documenting basic features of the plans and providing contextual information, these data will support the refinement and testing of hypotheses about the impact of public sector managed care on access, quality, costs, and outcomes of care. CONCLUSIONS: If managed behavioral health care research is to advance beyond simple case study comparisons, a well-conceptualized set of instruments is necessary.
OBJECTIVE: To develop an instrument to characterize public sector managed behavioral health care arrangements to capture key differences between managed and "unmanaged" care and among managed care arrangements. STUDY DESIGN: The instrument was developed by a multi-institutional group of collaborators with participation of an expert panel. Included are six domains predicted to have an impact on access, service utilization, costs, and quality. The domains are: characteristics of the managed care plan, enrolled population, benefit design, payment and risk arrangements, composition of provider networks, and accountability. Data are collected at three levels: managed care organization, subcontractor, and network of service providers. DATA COLLECTION METHODS: Data are collected through contract abstraction and key informant interviews. A multilevel coding scheme is used to organize the data into a matrix along key domains, which is then reviewed and verified by the key informants. PRINCIPAL FINDINGS: This instrument can usefully differentiate between and among Medicaid fee-for-service programs and Medicaid managed care plans along key domains of interest. Beyond documenting basic features of the plans and providing contextual information, these data will support the refinement and testing of hypotheses about the impact of public sector managed care on access, quality, costs, and outcomes of care. CONCLUSIONS: If managed behavioral health care research is to advance beyond simple case study comparisons, a well-conceptualized set of instruments is necessary.
Authors: Cameo F Borntrager; Bruce F Chorpita; Trina Orimoto; Allison Love; Charles W Mueller Journal: J Behav Health Serv Res Date: 2015-07 Impact factor: 1.505
Authors: Edward P Post; Amy M Kilbourne; Robert W Bremer; Francis X Solano; Harold Alan Pincus; Charles F Reynolds Journal: Implement Sci Date: 2009-12-31 Impact factor: 7.327