Predicting patient deterioration in youth mental health services: community mental health vs. managed care settings

Warren, Judith J.; Nelson, Philip L.; Burlingame, Gary M.; Mondragon, Sasha

doi:10.1002/jclp.20831

Cited by 22 publications

(17 citation statements)

References 52 publications

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“…Shorter 30-item and 12-item versions of the Y-OQ have also been developed (Dunn, Burlingame, Walbridge, Smith, & Crum, 2005;Tzoumas et al, 2007). The Y-OQ and Y-OQ-SR have been used to identify youths at-risk of treatment failure in community mental health and managed care settings (Cannon, Warren, Nelson, & Burlingame, 2010;Warren, Nelson, Burlingame, & Mondragon, 2012). Computer software is available to score the items and generate reports displaying clinically relevant information (e.g.…”

Section: Measurement Feedback Systemsmentioning

confidence: 99%

Annual Research Review: Building a science of personalized intervention for youth mental health

Weisz

2015

Child Psychology Psychiatry

228

147

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Background Within the past decade, healthcare service and research priorities have shifted from evidence-based medicine to personalized medicine. In mental healthcare, a similar shift to personalized intervention may boost the effectiveness and clinical utility of empirically supported therapies (ESTs). Aims and Scope The emerging science of personalized intervention will need to encompass evidence-based methods for determining which problems to target and in which order, selecting treatments and deciding whether and how to combine them, and informing ongoing clinical decision-making through monitoring of treatment response throughout episodes of care. We review efforts to develop these methods, drawing primarily from psychotherapy research with youths. Then we propose strategies for building a science of personalized intervention in youth mental health. Findings The growing evidence base for personalizing interventions includes research on therapies adapted for specific subgroups; treatments targeting youths’ environments; modular therapies; sequential, multiple assignment, randomized trials; measurement feedback systems; meta-analyses comparing treatments for specific patient characteristics; data-mining decision trees; and individualized metrics. Conclusion The science of personalized intervention presents questions that can be addressed in several ways. First, to evaluate and organize personalized interventions, we propose modifying the system used to evaluate and organize ESTs. Second, to help personalizing research keep pace with practice needs, we propose exploiting existing randomized trial data to inform personalizing approaches, prioritizing the personalizing approaches likely to have the greatest impact, conducting more idiographic research, and studying tailoring strategies in usual care. Third, to encourage clinicians’ use of personalized intervention research to inform their practice, we propose expanding outlets for research summaries and case studies, developing heuristic frameworks that incorporate personalizing approaches into practice, and integrating personalizing approaches into service delivery systems. Finally, to build a richer understanding of how and why treatments work for particular individuals, we propose accelerating research to identify mediators within and across RCTs, to isolate mechanisms of change, and to inform the shift from diagnoses to psychopathological processes. This ambitious agenda for personalized intervention science, though challenging, could markedly alter the nature of mental health care and the benefit provided to youths and families.

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Section: Measurement Feedback Systemsmentioning

confidence: 99%

Annual Research Review: Building a science of personalized intervention for youth mental health

Weisz

2015

Child Psychology Psychiatry

228

147

View full text Add to dashboard Cite

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“…Further, they found a “dose–effect” response whereby there was a positive association between providers’ frequency of use of outcome measurement feedback and the extent of child improvement, thus reinforcing support for the value of routine, systematic outcome measurement and feedback to providers. There has been a growing literature on “patient-focused” research methods to efficiently and effectively assess individual patient’s progress in treatment and to identify risk for negative outcomes (e.g., Howard et al 1996; Warren et al 2012). Use of outcome monitoring systems has demonstrated a positive impact on treatment effectiveness and efficiency for adult and child/family services (Lambert and Shimokawa 2011; Shimokawa et al 2010; Timimi et al 2012).…”

Section: Target Area #3: Outcome Accountabilitymentioning

confidence: 99%

“…Use of outcome monitoring systems has demonstrated a positive impact on treatment effectiveness and efficiency for adult and child/family services (Lambert and Shimokawa 2011; Shimokawa et al 2010; Timimi et al 2012). Outcome monitoring “warning” systems have also been shown to accurately identify youths who are at-risk for treatment failure (Warren et al 2012). Thus, there is great potential utility for measurement systems that can be used to assess treatment progress (or lack thereof).…”

Section: Target Area #3: Outcome Accountabilitymentioning

confidence: 99%

Improving Community-Based Mental Health Care for Children: Translating Knowledge into Action

Garland

Haine‐Schlagel

Brookman‐Frazee

et al. 2012

Adm Policy Ment Health

119

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There is urgent need for improvement in community-based mental health care for children and families. Multiple studies have documented serious limitations in the effectiveness of “usual care.” Fortunately, many empirically-supported strategies to improve care have been developed, and thus there is now a great deal of knowledge available to address this significant public health problem. The goal of this selective review is to highlight and synthesize that empirically-supported knowledge to stimulate and facilitate the needed translation of knowledge into action. The review provides a sound foundation for constructing improved services by consolidating descriptive data on the status quo in children’s mental health care, as well as evidence for an array of promising strategies to improve (a) Service access and engagement; (b) Delivery of evidence-based practices; and (c) Outcome accountability. A multi-level framework is used to highlight recommended care improvement targets.

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“…The TSM-Y and TSM-P domains and items were selected because of their association with positive treatment outcomes in longitudinal research with 750 children, adolescents and their parents served in community mental health systems [51] and their importance in the literature on youth psychotherapy outcome [52]. For children and adolescents, the domains are: (1) feelings of self-efficacy, (2) supportive relationships with family members and friends, (3) the child’s or adolescent’s motivation to participate in treatment, and (4) the alliance between the child or adolescent and the clinician.…”

Section: Methodsmentioning

confidence: 99%

Effective components of feedback from Routine Outcome Monitoring (ROM) in youth mental health care: study protocol of a three-arm parallel-group randomized controlled trial

et al. 2014

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BackgroundRoutine Outcome Monitoring refers to regular measurements of clients’ progress in clinical practice, aiming to evaluate and, if necessary, adapt treatment. Clients fill out questionnaires and clinicians receive feedback about the results. Studies concerning feedback in youth mental health care are rare. The effects of feedback, the importance of specific aspects of feedback, and the mechanisms underlying the effects of feedback are unknown. In the present study, several potentially effective components of feedback from Routine Outcome Monitoring in youth mental health care in the Netherlands are investigated.Methods/DesignWe will examine three different forms of feedback through a three-arm parallel-group randomized controlled trial. 432 children and adolescents (aged 4 to 17 years) and their parents, who have been referred to mental health care institution Pro Persona, will be randomly assigned to one of three feedback conditions (144 participants per condition). Randomization will be stratified by age of the child or adolescent and by department. All participants fill out questionnaires at the start of treatment, one and a half months after the start of treatment, every three months during treatment, and at the end of treatment. Participants in the second and third feedback conditions fill out an additional questionnaire. In condition 1, clinicians receive basic feedback regarding clients’ symptoms and quality of life. In condition 2, the feedback of condition 1 is extended with feedback regarding possible obstacles to a good outcome and with practical suggestions. In condition 3, the feedback of condition 2 is discussed with a colleague while following a standardized format for case consultation. The primary outcome measure is symptom severity and secondary outcome measures are quality of life, satisfaction with treatment, number of sessions, length of treatment, and rates of dropout. We will also examine the role of being not on track (not responding to treatment).DiscussionThis study contributes to the identification of effective components of feedback and a better understanding of how feedback functions in real-world clinical practice. If the different feedback components prove to be effective, this can help to support and improve the care for youth.Trial registrationDutch Trial Register NTR4234

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Predicting patient deterioration in youth mental health services: community mental health vs. managed care settings

Abstract: Results are consistent with previous research demonstrating that patient-focused warning systems can be reasonably accurate in identifying youth cases at risk for treatment failure.

Cited by 22 publications

References 52 publications

Annual Research Review: Building a science of personalized intervention for youth mental health

Annual Research Review: Building a science of personalized intervention for youth mental health

Improving Community-Based Mental Health Care for Children: Translating Knowledge into Action

Effective components of feedback from Routine Outcome Monitoring (ROM) in youth mental health care: study protocol of a three-arm parallel-group randomized controlled trial

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