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

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.

Intentional research design in implementation science: implications for the use of nomothetic and idiographic assessment

“…Regarding intervention outcomes, problem identification and outcome measurement strategies are receiving international attention [24][25][26], and are central to studies evaluating the effectiveness of programs, demonstrating the efficiency of such programs to funders, and determining where to target quality improvement efforts [27]. Outcomes of interest may include reductions in symptoms or disease states, improved service recipient functioning, adjustments in services received, or changes to the environmental contexts in which service recipients interact, among others [28].…”

Evidence for the Management of Adolescent Depression

“…149,150 No studies documenting this phenomenon in adolescent treatment were identified; however, the Treatment of Resistant Depression in Adolescents study showed that depressed adolescents who were not improved after an 8-week treatment trial had improved outcomes after switching medication and adding CBT. 96 By comparison, the Sequenced Treatment Alternatives to Relieve Depression study in adults suggests that citalopram nonresponders may benefit more from increased dose or augmentation with CBT compared with a switch to another medication, and that augmenting medication treatment with CBT may be no more effective than switching to CBT alone.…”

Management of Chronic Depressive Patients with Residual Symptoms

“…In a survey study, psychiatrists' most frequent method for diagnosing depression was through a clinical interview with patients (53 %). Only 11 % of psychiatrists reported that they used measurement scales [6]. The STAR*D study underscored the concept of measurement-based clinical practice, highlighting the importance of the periodic evaluation of symptoms and depression severity using measurement scales [6].…”

“…Only 11 % of psychiatrists reported that they used measurement scales [6]. The STAR*D study underscored the concept of measurement-based clinical practice, highlighting the importance of the periodic evaluation of symptoms and depression severity using measurement scales [6]. In real clinical settings, diagnosing depression is a complex and easily confounded goal because of depression's varied symptoms and comorbid medical and psychiatric conditions [7].…”