27 research outputs found
An Integrated Model for the Management of Co-Occurring Psychiatric and Substance Disorders in Managed-Care Systems
This article describes research-based principles of successful treatment interventions in individuals with co-occurring disorders. These principles are placed in the context of an integrated model of service delivery that utilises a common language or treatment philosophy that makes sense from the perspective of both mental health treatment and substance disorder treatment fields. The article begins with an overview of the clinical and programmatic dilemmas faced by clinicians in treating these `dually diagnosed' individuals and then enumerates 7 principles of treatment. These are: 1. dual diagnosis is an expectation, not an exception, within any of the 4 subtypes of comorbidity (using a subtyping model based on high/low severity of each disorder); 2. the most significant predictor of treatment success is the provision of an empathic, hopeful, continuous treatment relationship in which integrated treatment and care coordination are provided over time; 3. within the context of this relationship, caretaking and case management are balanced with empathic detachment, empowerment and confrontation at each point in time; 4. within this ongoing treatment context, both mental illness and substance disorder are considered primary, and integrated dual primary treatment is provided; 5. both mental illness and addiction are examples of not just random primary disorders, but chronic biological mental illnesses which can be understood using a disease and recovery model; 6. the model defines parallel phases of recovery, which themselves define phase-specific treatment interventions; as a result, there is no single correct intervention in this model. For each individual, the correct treatment must be matched to subtype, diagnosis, phase of treatment and extent of patient motivation and disability; and 7. within a managed-care system, these interventions must be further individualised by a discrete level of care assessment for each disorder. These principles provide a template both for developing practice guidelines to determine individualised clinical treatment matching, as well as providing a template for large-scale system initiatives for the creation of comprehensive continuous integrated systems of care, and for assigning roles for each type of programme within those systems. These large systems initiatives are currently underway in several US states, and provide a laboratory for further research on this model.Drug abuse, Managed care, Pharmacoeconomics, Psychiatric disorders
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Argonne National Laboratory Reports
The solution of the general nonlinear programming problem by means of a subroutine called VMCON is described. VMCON uses an algorithm that solves a sequence of positive-definite quadratic programming sub-problems. Each solution determines a direction in which a one-dimensional minimization is performed. In developing this code, changes in the original implementation were made to make the program easier to use and maintain and to incorporate some recently developed LINPACK subprograms. The current implementation contains extensive in-line documentation; an interface subroutine, VMCON1, with a simplified calling sequence; and print options to aid the user in interpreting results
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Argonne National Laboratory Reports
This report describes the implementation of an algorithm of Stoer and Schittkowski for solving linearly constrained linear least-squares problems. These problems arise in many areas, particularly in data fitting where a model is provided and parameters in the model are selected to be a best least-squares fit to known experimental observations. By adding constraints to the least-squares fit, one can force user-specified properties on the parameters selected. The algorithm used applies a numerically stable implementation of the Gram-Schmidt orthogonalization procedure to deal with a factorization approach for solving the constrained least-squares problem. The software developed allows for either a user-supplied feasible starting point or the automatic generation of a feasible starting point, re-decomposition after solving the problem to improve numerical accuracy, and diagnostic printout to follow the computations in the algorithm. In addition to a description of the actual method used to solve the problem, a description of the software structure and the user interfaces is provided, along with a numerical example