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CMAP Publications
ABSTRACT
Objective: To develop consensus guidelines for medication treatment algorithms for childhood major depressive disorder (MDD) based on scientific evidence and clinical opinion when science is lacking. The ultimate goal of this approach is to synthesize research and clinical experience for the practitioner and to increase the uniformity of preferred treatment for childhood MDD. A final goal is to develop an approach that can be tested as to whether it improves clinical outcomes for children and adolescents with MDD.
Method: A consensus conference was held. Participants included academic clinicians and researchers, practicing clinicians, administrators, consumers, and families. The focus was to review and use clinical evidence to recommend specific pharmacological approaches for treatment of MDD in children and adolescents. Following a series of presentations of current research evidence and panel discussion, the consensus panel met, agreed on assumptions, and drafted the algorithms. The process initially addressed strategies of treatment and then tactics to implement the strategies.
Results: Consensually agreed upon algorithms for major depressions (with and without psychosis), and comorbid attention deficit disorders were developed. Treatment strategies emphasized the use of SSRIs. The algorithm consists of systematic strategies for treatment interventions and recommended tactics for implementation of the strategies, including medication augmentation and medication combinations. Participants recommended prospective evaluation of the algorithms in various public sector settings and many volunteered as sites for such an evaluation.
Conclusions: Using scientific and clinical experience, consensus derived algorithms for children and adolescents with MDD can be developed.
ABSTRACT
Objective: Utilizing expert consensus methodology, to develop evidence-based, consensually agreed upon medication treatment algorithms for ADHD in the public mental health sector. Although treatment algorithms for adult mental disorders have been developed, this represents one of the first attempts to develop similar algorithms for childhood mental disorders. While developed initially for the public sector, the goals of this approach are to increase the uniformity of treatment and improve the clinical outcomes of children and adolescents with ADHD in a variety of treatment settings.
Method: We convened a consensus conference of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families to develop evidence based consensus algorithms for the pharmacotherapy of childhood ADHD. Following a series of presentations of current research evidence and panel discussion, the consensus panel met and drafted the algorithms along with guidelines for implementation.
Results: The panel developed consensually agreed algorithms for ADHD with and without specific comorbid disorders. The algorithms consist of systematic strategies for psychopharmacologic interventions and tactics to assure successful implementation of the strategies. While the algorithms focused on the medication management of ADHD, the conference emphasized that psychosocial treatments are often a critical component of the overall management of ADHD.
Conclusions: Medication algorithms for ADHD can be developed with consensus. A companion paper will discuss the implementation of these algorithms.
ABSTRACT
Objective: Expert consensus methodology was used to develop a medication treatment algorithm for attention-deficit/hyperactivity disorder (ADHD). The algorithm broadly outlined the choice of medication for ADHD and some of its most common comorbid conditions. Specific tactical recommendations were developed with regard to medication dosage, assessment of drug response, management of side effects, and long-term medication management.
Method: The consensus conference of academic clinicians and researchers, practicing clinicians, administrators, consumers, and families developed evidence-based tactics for the pharmacotherapy of childhood ADHD and its common comorbid disorders. The panel discussed specifics of treatment of ADHD and its comorbid conditions with stimulants, antidepressants, mood stabilizers, alpha-agonists, and (when appropriate) antipsychotics.
Results: Specific tactics for the use of each of the above agents are outlined. The tactics are designed to be practical for implementation in the public mental health sector, but they may have utility in many practice settings, including the private practice environment.
Conclusions: Tactics for psychopharmacological management of ADHD can be developed with consensus.
ABSTRACT
Objective: To determine whether an algorithm for the treatment of attention-deficit/hyperactivity disorder (ADHD) can be implemented in a community mental health center.
Method: Fifty child an adolescent patients at Texas Community mental health centers who met critieria for ADHD were treated according to an algorithm- based disease management program for ADHD. Psychiatritist were trained in the use of the algorithm, and each subject underwent a baseline assessment consisting of a structured interview and standardized rating scales. Subjects were monitored for 4 months. At the end of treatment, the psychiatrists completed the Clinical Global Impression Scale (CGI) and the baseline rating scales were repeated. The primary variables of interest were psychiatrist and family adherence to the algorithm. To examine impact on treatment outcome, the CGI of the algorithm subjects were compared with CGIs based on chart reviews of 118 historical controls.
Results: Psychiatrists implemented the major aspects of the algorithm, but the detailed tactics of the algorithm (use of fixed titration of stimulants) were less well adhered to.
Conclusions: An algorithm for the treatment of ADHD can be implemented in a community mental health center. Journal of the American Academy of Child and Adolescent Psychiatry,2003, 42(3):279-287 . www.aacap.org/publications/journal
ASTRACT
Objective: To evaluate the feasibilty and impact on clinical response and function associated with the use of an algorithm-driven disease management program (ALGO) for children and adolescents treated for depression with or without attention-deficit/hyperactivity disorder (ADHD) in community mental health centers.
Method: Interventions included (1) medication algorithms, (2) clinical and technical support for the physician, (3) uniform chart documentation of outcomes, and (4) a patient/family psychoeducation program. Children eligible for entry into the study were referred to the child psychiatrist for initiation or change in medicine. Outcomes of treatment with the ALGO for up to 4 months are presented. Measures of change included clinical symptoms, functioning, and global improvement (Clinical Global Impression Scale). A historical chart cohort from the same clinics was used as a quasi-control.
Results: Thirty-nine individuals (depression = 24; comorbid depression with ADHD = 15) were enrolled for treatment with ALGO. One hundred fourteen children were in the control cohort (74 depressed, 40 comorbid). For the ALGO groups, Children's Depression Rating Scale-Revised depression severity scores decreased from 48.2 to 32.5 and Child Adolescent Functioning Assessment Scale function scores improved from 70.3 to 40.9 (all p ≤ .0005). Clinical Global Impression Scale severity scores decreased from 5.7 to 3.7 in ALGO compared to only 5.8 to 4.8 in the control (p < .003).
Conclusions: There was clear improvement in clinical symptoms, functioning, and global response with ALGO treatment. The magnitude of the improvement was greater in children and adolescents treated with the ALGO program compared with a historical cohort. These data support the need for controlled studies in larger populations examining the effects of algorithm-driven disease management programs on the clinical outcomes of children with mental illness.
Please direct all questions regarding this page to: Molly Lopez
Last Updated August 18, 2005
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