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the primary work or treatment level (Lynn, Heinrich and Hill, 2001).  The data we use, from the National Treatment Improvement Evaluation Study (NTIES), were collected from more than 500 substance abuse treatment service delivery units (SDUs) and more than 6,500 clients by the National Opinion Research Center (NORC) and a sub-contractor, the Research Triangle Institute.  (See Appendix A for more information about NTIES and Gerstein et al., 1997 for a thorough description of the study and data.)  The NTIES design was intrinsically multilevel, and client-level data are linked to a subset of the service delivery units for which data on institutional and programmatic factors was collected, including information about administrative and financial structures, external organizational relationships, program policies, administrator and clinician treatment philosophies, administrative procedures, and staff characteristics.  In this regard, NTIES provides a uniquely rich and extensive data base on substance abuse treatment at all pertinent levels of analysis, many of which have not yet been fully or even partially explored.  

The primary goal of the empirical component of this paper is to identify instruments of policy and governance, within an organizing framework based in public management theory, that might either frustrate or facilitate the implementation of best practices, including practices that are identified and strongly supported by substance abuse treatment research.  The findings presented about the organization and management of substance abuse treatment programs are mainly descriptive and exploratory, yet they constitute an important contribution to understanding what structural and management factors might be manipulated to improve post-treatment outcomes.  The analyses showed statistically significant and substantively interesting relationships among measures of organizational structure and mission, financial management variables (e.g., revenues per client and revenue sources), human resources management (e.g., staffing levels, the use of case managers, etc.), and measures of service technology (e.g., the

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