Measurement-based care for refractory depression: A clinical decision support model for clinical research and practice

Mood Disorders Program, Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX 75390, USA.
Drug and Alcohol Dependence (Impact Factor: 3.28). 06/2007; 88 Suppl 2:S61-71. DOI: 10.1016/j.drugalcdep.2007.01.007
Source: PubMed

ABSTRACT Despite years of antidepressant drug development and patient and provider education, suboptimal medication dosing and duration of exposure resulting in incomplete remission of symptoms remains the norm in the treatment of depression. Additionally, since no one treatment is effective for all patients, optimal implementation focusing on the measurement of symptoms, side effects, and function is essential to determine effective sequential treatment approaches. There is a need for a paradigm shift in how clinical decision making is incorporated into clinical practice and for a move away from the trial-and-error approach that currently determines the "next best" treatment. This paper describes how our experience with the Texas Medication Algorithm Project (TMAP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial has confirmed the need for easy-to-use clinical support systems to ensure fidelity to guidelines. To further enhance guideline fidelity, we have developed an electronic decision support system that provides critical feedback and guidance at the point of patient care. We believe that a measurement-based care (MBC) approach is essential to any decision support system, allowing physicians to individualize and adapt decisions about patient care based on symptom progress, tolerability of medication, and dose optimization. We also believe that successful integration of sequential algorithms with MBC into real-world clinics will facilitate change that will endure and improve patient outcomes. Although we use major depression to illustrate our approach, the issues addressed are applicable to other chronic psychiatric conditions including comorbid depression and substance use disorder as well as other medical illnesses.

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    • "Self-report measures are also used in clinical contexts for the measurement of severity on admission, to monitor change during treatment or as a tool for follow up. Frequently, the use of self-report measures is endorsed in practice guidelines, for example Practice guidelines Depression, third edition, published by the American Psychiatric Association (2010) and the Swedish national guidelines for the treatment of depression and anxiety disorders from The National Board of Health and Welfare (Socialstyrelsen 2010), and models for measurement based care have been proposed (Trivedi & Daly 2007). "
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