Show Summary Details
Page of

(p. 607) An Update on Evidence-Based Practices for Children and Adolescents in the Context of Policy, Research, and Practice: A Systems Perspective 

(p. 607) An Update on Evidence-Based Practices for Children and Adolescents in the Context of Policy, Research, and Practice: A Systems Perspective
Chapter:
(p. 607) An Update on Evidence-Based Practices for Children and Adolescents in the Context of Policy, Research, and Practice: A Systems Perspective
Author(s):

Ka Ho Brian Chor

, Kimberly E. Hoagwood

, and Su-Chin Serene Olin

DOI:
10.1093/med-psych/9780199928163.003.0030
Page of

PRINTED FROM OXFORD CLINICAL PSYCHOLOGY ONLINE (www.oxfordclinicalpsych.com). © Oxford University Press, 2020. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a title in Oxford Clinical Psychology Online for personal use (for details see Privacy Policy and Legal Notice).

date: 28 March 2020

(p. 608) Overview

In the past decade, the policy, research, and practice contexts of evidence-based practices (EBPs) for children and adolescents have undergone significant transformation. While hundreds of potentially effective treatments have been developed (Chorpita, Daleiden, et al., 2011), their translation into real-world settings has been stymied by challenges at multiple levels (Fixsen, Blase, Metz, & van Dyke, 2013; Fixsen, Naoom, Blase, Friedman, & Wallace, 2005). The purpose of this chapter is to provide a 10-year update on our last synthesis by describing the major changes in the policy, research, and practice contexts that have highlighted systems issues in the dissemination and implementation of EBPs. We first provide an overview of the system issues surrounding the three contexts.

Since the early 1990s the treatment development literature has yielded both breadth and depth in knowledge about EBPs for major child and adolescent disorders (Silverman & Hinshaw, 2008). The focus of EBP has extended beyond DSM-bound disorders and specialty mental health contexts, as reviews have identified effective home-based (Chaffin, Hecht, Bard, Silovsky, & Beasley, 2012), school-based (Langley, Nadeem, Kataoka, Stein, & Jaycox, 2010), and family engagement interventions (Kim, Munson, & McKay, 2012). Further, there has been an accompanying shift away from treatment efficacy trials toward the dissemination and implementation of EBPs in child mental health systems (Bruns & Hoagwood, 2008; Fixsen et al., 2013; Kazak et al., 2010). This shift has been fueled by two troublesome findings. First, there is a 17-year gap between publishing research findings and having those findings translated into practice. Second, of research findings that are published, only 14% are ultimately used to change practice (Green, 2001, 2007).

States have undertaken the monumental task of installing EBPs in their delivery systems (Fixsen et al., 2013; Gleacher et al., 2011). At least 20 states have invested over $100 million in EBP rollouts in the past decade (Bruns & Hoagwood, 2008), with some states further supported by contracts with purveyors (Fixsen et al., 2005) and by federal assistance in implementation (Substance Abuse and Mental Health Services Administration, 2013). Despite such investments, many state systems find themselves rolling out EBPs through trial and error (McHugh & Barlow, 2010) with limited impact on service delivery (Fixsen et al., 2013); only 10% of public systems in California, for example, deliver any kind of EBP (Wang, Saldana, Brown, & Chamberlain, 2010).

Major policy changes in healthcare are reframing the research and practice contexts for implementation of EBPs for children. Unlike the political climate a decade ago, when reports from the Institute of Medicine (IOM, 2001, 2006), the Surgeon General’s Report on Mental Health (U.S. Public Health Service, 1999), and the National Action Plan on Children’s Mental Health (U.S. Public Health Service, 2000) converged on the research–practice gaps in mental health, the current healthcare reform is presenting a new set of opportunities. The Children’s Health Insurance Program Reauthorization Act of 2009 (CHIPRA; P.L. 111-3), the Paul Wellstone and Pete Domenici Mental Health Parity and Addiction Equity Act of 2008 (MHPAEA; P.L. 110-343), and the Patient Protection and Affordable Care Act of 2010 (ACA; P.L. 111-148) are changing the infrastructure, financing policies, and provider accountability standards for the mental health system. These policies have also repositioned mental health within a broader public health and prevention framework (Hoagwood, Olin, & Cleek, 2013; IOM, 2006; 2009).

Paradigm Shifts in Policy

The system changes consequent to the ACA and broader healthcare policies include continued attention to the installation of EBPs, but they extend beyond this. Integration of the behavioral health and the healthcare systems is happening across the country in part to address problems of costly service duplication and fragmentation. Increasingly, payers are demanding monitoring and tracking of mental health (p. 609) outcomes. This requires the development of specific quality indicators and measures. New financing systems and business practices are also needed to sustain these changes and to maintain fiscal solvency. These changes are described below.

Integrated Care and Care Coordination

The traditional specialty mental health system is being replaced by mental health services delivered within regionalized networks of healthcare providers (Hoagwood, 2013; Kelleher, 2010). In the ACA, this paradigm shift translates to accountable care organizations (ACOs) on the system level and patient-centered medical homes (PCMHs)/health homes on the individual practitioner level. Both models aim to improve the quality and outcomes of care (Katon & Unützer, 2013). A key example is the Nationwide Children’s Hospital Partners for Kids ACO, which serves 300,000 Medicaid children in Ohio. Partners for Kids uses a capitated arrangement with three Medicaid managed care plans. For each child, Partner for Kids is paid a set fee and is held responsible for managing and providing quality care, including mental health care (Allen, 2010; Vecchione, 2012). In the PCMH model, primary care physicians function as treatment leaders and are responsible for providing comprehensive and coordinated care with other professionals, including mental health professionals (Gabel, 2010). Many ACO and PCMH models are still being tested. Measuring their success will likely depend on the integration of clinical and administrative data and the performance of provider networks (Landon et al., 2013; Lewis & Fisher, 2012).

Standalone mental health clinics are being replaced by integrated health and behavioral health service agencies. This poses benefits and challenges. Since the ACA is incentivizing the integration of services through the co-location of primary and specialty care in community-based health settings, the overall quality and linkage of services for children, especially in rural areas, is likely to improve (Gabel, 2010). However, an integrated health and behavioral health system does not address the coordination of other child-serving sectors, most notably child welfare, juvenile justice, and education. These sectors operate under independent definitional and fiscal arrangements. Unless a broader reorganization is created to manage the behavioral health needs of children in these sectors, the fragmentation that has characterized mental health services for children for decades is likely to persist.

Quality Indicators

Quality indicators addressing children’s health needs are being developed to hold the healthcare system accountable for improving the quality of care and for targeting the needs of all children (Institute of Medicine & National Research Council, 2011). Quality indicators addressing behavioral or mental health needs are new and relatively undeveloped, lagging behind those developed for adults (Pincus, Spaeth-Rublee, & Watkins, 2011; Zima & Mangione-Smith, 2011). To initiate this work, CHIPRA (P.L. 111-3) awarded $55 million to the Agency for Healthcare Research and Quality in 2010 to fund seven national Centers of Excellence over 4 years. These Centers of Excellence are tasked with developing core quality indicators across all areas of children’s health (Zima et al., 2013). One priority area is the development of behavioral and mental health quality measures (Institute of Medicine & National Research Council, 2011). Specifically, one of the centers, the National Collaborative for Innovation in Quality (Scholle, principal investigator), is developing and testing quality indicators in child and adolescent depression (Lewandowski et al., 2013) and antipsychotic prescribing practices (Kealey et al., 2014). These quality indicators will help to align children’s behavioral health services with broader healthcare services. However, this is only a small start. Much larger efforts are needed to develop measures of quality addressing mental health services for children (Zima et al., 2013).

The establishment of quality indicators facilitates tracking, reporting, and communicating outcomes (Berenson, Pronovost, & Krumholz, 2013). Although electronic health records (p. 610) (EHRs) can support these functions, they are generally used to collect data on day-to-day operations and may not be transferrable from one record system to another. Further, their “meaningful use” for recording quality has not been a priority until the introduction of the Health Information Technology for Economic and Clinical Health (HITECH) Act under the American Recovery and Reinvestment Act of 2009 (P. L. 111-5). Moving forward, EHR-based quality measures will have vast potential to identify outcome patterns and trends to inform decision making (Zima et al., 2013) and to initiate quality improvement (Torda & Tinoco, 2013).

Financing Policies

Financing policies for mental health services are shaped by payment reforms that accompany care coordination. The ACO model employs a flexible payment infrastructure (e.g., capitation, shared losses and savings) to control the total cost of care and to incentivize networked providers with reimbursements that are tied to quality measures (Center for Medicare & Medicaid Services, 2013). In mental health, incentivized outcomes may provide additional flexibility for networked providers to innovate their practices by incorporating EBPs. Adoption of specific EBPs, however, will be a function of economic resources, network mission, and whether an EBP will cover a large portion of clients within the network, especially high-need and high-cost clients.

Payment reforms are also occurring on the state level. Mirroring the impetus of the ACA, New York State, for example, has initiated a Medicaid Redesign Team to rein in Medicaid spending, the largest payment source for child mental health services (New York State Department of Health, 2011). A key initiative stemming from Medicaid Redesign is contracting with behavioral health organizations to provide mental health services. The services include direct delivery and administrative, monitoring, and management functions using standard quality indicators such as inpatient admission rates, engagement with follow-up outpatient services, and use of EHR (NYSOMH, 2012). The behavioral health organization initiative will affect both inpatient and outpatient providers serving Medicaid populations, with one goal being cost reduction. Under this payment system shift, the viability of EBPs will depend on their goodness-of-fit with standard quality indicators and financing parameters (e.g., length of treatment allowed). It will also depend on providers’ ability to improve their business practices (e.g., setting and reaching productivity benchmarks, redesigning financial structure, and improving operational flow) in order to fiscally and operationally support EBP integration into their routine services. EBPs that yield measurable outcomes and long-term cost reductions will be particularly valuable (Saldana, Chamberlain, Bradford, Campbell, & Landsverk, 2015).

Paradigm Shifts in Research

To improve care quality, practitioners, states, and healthcare systems are increasingly motivated to translate the knowledge base for EBP (Silverman & Hinshaw, 2008) into service systems (Kazdin, 2013). Their efforts to adopt and routinize EBPs depend on many factors that are relevant to the fit of EBPs to the context of their system (Fixsen et al., 2013; McHugh & Barlow, 2010). In short, there is a strong need for a complementary knowledge base in dissemination and implementation research.

The research funding climate in the past 10 years has reflected this shift. In 2001, the National Institute of Mental Health (NIMH) released a funding announcement specifically for Dissemination Research in Mental Health and funded three grants; this number surged to over 40 grants from 2005 to 2009. On average 50 to 60 grant applications are now reviewed per funding cycle (Chambers, 2010, 2012). These funded studies increasingly target sustainability, adaptability, scaling up systems, and organizational decision making (Chambers, 2010, 2012). The recently established Patient-Centered Outcomes Research Institute (PCORI, 2013) funded 50 pilot projects to address five priorities in research to help patients and (p. 611) healthcare providers make informed decisions. These funding opportunities look beyond treatment development in a laboratory setting, focusing instead on aligning effective services and treatments with the demands of healthcare reform. A key funding priority is the communication and dissemination of research results to patients, caregivers, and clinicians to improve decision making (PCORI, 2013).

Below we highlight some of the progress and challenges in the models, designs, and measures surrounding dissemination and implementation (D&I) research.

D&I Models

Creating a scientific knowledge base on the effectiveness of services that can be readily adopted within different contexts requires a different paradigm from the typical efficacy to effectiveness model that has guided much research in the past. Two models designed to short-circuit the unnecessary delays in translating research findings into practice were developed and have been used to guide intervention development: the Deployment-Focused Model (Weisz, 2004) and the Clinic-Community Intervention Model (Hoagwood, Burns, & Weisz, 2002). Both models suggest that researchers attend to multilevel contextual variables through the development and testing of new interventions, even in the initial efficacy phase. These variables might include characteristics of practitioners, organizations, communities, and families.

There has been significant growth in the refinement of D&I-specific frameworks, as well as efforts to synthesize these models (Damschroder et al., 2009). Comprehensive D&I models such as the Consolidated Framework for Implementation Research (Damschroder et al., 2009), the Practical, Robust Implementation and Sustainability Model (Feldstein & Glasgow, 2008), and the Advanced Conceptual Model of EBP Implementation (Aarons, Hurlburt, & Horwitz, 2011) converge on the multiphase (i.e., from intervention development, to adoption, to implementation) and multilevel (e.g., from individual, organization, to system) nature of EBP delivery. Each model is useful in delineating information about facilitators and barriers to D&I (Damschroder et al., 2009; Durlak & DuPre, 2008). These models have been applied to health and mental health intervention implementation across diverse settings and sectors (Aarons et al., 2011; Damschroder et al., 2009; Feldstein & Glasgow, 2008).

In contrast to the traditional EBP focus on client-treatment factors, a key feature of D&I models is an emphasis on the organizational context in which changes, outcomes, and services take place. Organization-level variables such as leadership, operational capacity, and vertical and horizontal networks are influential in the different phases of D&I (Aarons et al., 2011; Wisdom, Chor, Hoagwood, & Horwitz, 2014). Organizational social context (e.g., culture and climate) has been found to influence a range of outcomes and quality practices (Glisson, 2007; Glisson & Schoenwald, 2005; Olin, Kutash, et al., 2014; Olin, Williams, et al., 2014).

D&I Designs and Measures

To expand the science base of D&I research, D&I designs are needed to study large system changes. For this purpose, Curran, Bauer, Mittman, Pyne, and Stetler (2012) propose three hybrid designs:

  1. 1. Testing a clinical intervention and gathering implementation data at the same time

  2. 2. Testing a clinical intervention and testing implementation strategies at the same time

  3. 3. Testing an implementation and gathering data on a clinical intervention’s impact on relevant outcomes.

Hybrid type 1 is best for reducing the time gap between efficacy and effectiveness research (e.g., during a randomized controlled trial, data on barriers and facilitators to implementation are gathered). Hybrid type 2 is most appropriate when there are clear clinical outcomes (e.g., patient-level improvement) and (p. 612) implementation outcomes (e.g., clinic-level adoption of EBP). For example, feasibility pilots or preliminary, small-scale randomized controlled trials prior to large-scale implementation are best suited for Hybrid type 2. Hybrid type 3 is best used when the focus is on implementation without necessarily completing the full portfolio of effectiveness studies so that the clinical effectiveness of an EBP can be tested under different conditions. Each hybrid design has different units of analysis (e.g., patient, clinic, system) and evaluation methods (e.g., quantitative, qualitative, mixed, formative, or summative methods).

Beyond individual interventions, D&I designs have been applied to several large-scale experiments that address healthcare system changes, with promising evidence. The Depression Improvement Across Minnesota—Offering a New Direction (DIAMOND) initiative partnered health plans with clinics to evaluate the implementation impact of a collaborative care model for depression on patient outcomes and stakeholder engagement (Solberg et al., 2010). The Community Partners in Care model, which promotes community engagement and planning and interagency collaboration, was found to be superior to a technical assistance and outreach approach in implementing depression quality improvement programs across community service sectors (Wells et al., 2013). A third study has focused on implementation strategies that are effective in communities, such as the Communities That Care coalition-based strategy targeted toward the adoption of prevention EBPs (Shapiro et al., 2013).

Optimal D&I designs also need to be compatible with evolving technologies in interventions. The Continuous Evaluation of Evolving Behavioral Intervention Technology (CEEBIT) is an evaluation framework tailored specifically to web-based and mobile interventions (Mohr, Cheung, Schueller, Brown, & Duan, 2013). Based on electronic data, the CEEBIT framework involves simultaneous evaluations of multiple interventions, eliminates those with inferior outcomes, and incorporates new interventions for further evaluation. Thus, this framework can empirically accelerate the validation of interventions that have the capacity to spread, a luxury that conventional, time-consuming D&I evaluations often cannot afford (Mohr et al., 2013).

Although effective and efficient D&I designs are important, few systematic measures assess the implementation processes and mechanisms to identify when and how implementation fails or succeeds. The Stages of Implementation Completion (Chamberlain, Brown, & Saldana, 2011) and the Reach Effectiveness Adoption Implementation (Glasgow, Lichtenstein, & Marcus, 2003) represent focused measurement efforts to derive useful and communicable metrics for implementation studies. Other complementary efforts include construction of measures associated with predictors of implementation outcomes. The Seattle Implementation Research Collaborative (2013) Instrument Review Project and the Grid-Enabled Measures database (National Cancer Institute, 2013) centralize measures for implementation-related factors (e.g., community, organization, provider, individual, and innovation characteristics). The measurement of implementation factors means that essential data at each stage of the implementation process are collected. This effort will improve the understanding of implementation thresholds, advance program evaluations, and refine D&I study designs (Durlak & DuPre, 2008).

Paradigm Shifts in Practice

Trends in practice are driven by the prevalence of psychiatric disorders, service delivery characteristics, and the needs of the populations being served. The occurrence of a DSM disorder associated with severe impairment is unfortunately common, affecting one in 10 children and adolescents (ages 8–15) every year (Merikangas, He, Brody, et al., 2010), and one in five adolescents (ages 13–18) in their lifetime (Merikangas, He, Burstein, et al., 2010). Among two nationally representative samples, 50% to 63% did not access mental health services (Mechanic, McAlpine, & Rochefort, 2014; Merikangas, He, Brody, (p. 613) et al., 2010; Merikangas et al., 2011). Racial/ethnic minorities also received significantly fewer services than their white counterparts. Adolescents diagnosed with mood, anxiety, and attention-deficit/hyperactivity disorders (ADHD) also received limited services (Merikangas et al., 2011). The underuse of mental health services, however, masks the needs of specific child-serving sectors with high rates of mental health problems (Farmer et al., 2010), including children in out-of-home placements (Substance Abuse and Mental Health Services Administration, 2007), foster care (Administration for Children and Families, 2013), and juvenile justice systems (Office of Juvenile Justice and Delinquency Prevention, 2009). These sectors continue to demonstrate high needs for mental health services (Desai et al., 2006; Farmer et al., 2010).

For clinicians, EBPs are the means to meet the population needs for mental health services. Pragmatic tools and resources help clinicians and consumers assess treatment options and select appropriate treatment. Public EBP registries facilitate this goal. The National Registry of Evidence-based Programs and Practices contains 195 mental health and substance abuse EBPs for children ages 0 to 17 (SAMHSA, 2013); the National Child Traumatic Stress Network (NCTSN, 2013) summarizes 48 EBPs and promising practices for trauma. EBP registries are also tailored to child-serving sectors. The California Evidence-based Clearinghouse (2013) contains 173 child welfare EBPs for children ages 0 to 17. The Office of Juvenile Justice and Delinquency Prevention (OJJDP, 2013) Model Programs Guide is a database of 142 EBPs that cover the continuum of services for youth in juvenile justice. Although review methods for evidence may vary across registries, treatments that are considered EBPs are relatively consistent. The underlying constant among diverse EBPs is the integration of best research evidence, clinical expertise, and patient values to produce specific, desired outcomes (IOM, 2001; Sexton et al., 2010).

Below we outline some of the significant changes in clinical practice that have occurred in the past decade.

Pediatric Psychopharmacology and the Role of Primary Care Physicians in Mental Health

Increasingly, mental health services for children and adolescents include use of psychotropic medications, especially for mood disorders and ADHD (Merikangas, He, Rapoport, Vitiello, & Olfson, 2013). Although antipsychotic use is infrequent in the general population (Merikangas, He, Rapoport, Vitiello, & Olfson, 2013), it has increased threefold between 1999 and 2008 among pediatric Medicaid recipients and has created a significant financial burden on Medicaid spending (Lagnado, 2013). These concerns prompted the Department of Health and Human Services to launch a five-state probe to review antipsychotic prescriptions for Medicaid children (Lagnado, 2013).

Since primary care physicians (e.g., pediatricians and family physicians) are often the first-line treatment providers for children with mental health needs, there is a high need to train these providers in identifying and managing mental health conditions in children, beyond prescribing psychotropic medications (Gabel, 2010; Pidano & Honigfeld, 2012). Twenty-six states have formed the National Network of Child Psychiatry Access Programs to exchange technical assistance in supporting child psychiatry training in primary care, developing documentation and outcome tools (Straus & Sarvet, 2012). Key state training efforts include the Massachusetts Child Psychiatry Access Project (Sarvet et al., 2010), the Washington Partnership Access Line (Hilt, McDonell, Rockhill, Golombek, & Thompson, 2009), and the New York State Training and Education for the Advancement of Children’s Health (Gabel, 2010). These concurrent efforts will likely result in improved identification and diagnosis of children with mental health disorders, leading to greater access and linkage to mental health services for these children who presented in primary care settings.

Large-Scale EBP Training and Use of Technology for Training

Major national and state initiatives have invested in large-scale EBP training to increase (p. 614) public access to EBPs and strengthen the professional workforce (Bruns & Hoagwood, 2008; McHugh & Barlow, 2010). They use a combination of didactics, workshops, supervision, and expert consultation to facilitate sustainability of adoption (Comer & Barlow, 2013; McHugh & Barlow, 2010). The SAMHSA-funded NCTSN has invested $377 million in 180 centers to train 901,411 professionals in 41 trauma-informed EBPs and promising practices between 2001 and 2009 (B. J. Burns, personal communication, October 17, 2013). States have also scaled up training in multiple EBPs (Bruns & Hoagwood, 2008; McHugh & Barlow, 2010). New York is a leading state in this training effort (McHugh & Barlow, 2010). In 2004, New York State Office of Mental Health funded the Evidence-Based Treatment Dissemination Center to train front-line clinicians and supervisors in outpatient and inpatient settings to provide EBPs. To date, more than 1,300 clinicians and 200 supervisors have been trained in functional family therapy and cognitive-behavioral therapy for trauma, depression, and disruptive behaviors (Gleacher et al., 2011).

The increased availability of webinars and online training has facilitated large-scale training initiatives. Webinars and online training can reach clinicians who want to keep abreast of current treatments. For clinicians with varying experiences, web- or computer-based training offers self-paced learning, standardization, and consistency of quality (Kendall, Khanna, Edson, Cummings, & Harris, 2011; Sigel et al., 2013). For others who are limited by cost and the inability to attend live training, free, web-based learning sanctioned by EBP developers becomes a feasible alternative (Sigel et al., 2013). The Medical University of South Carolina (2013) has partnered with trauma-focused cognitive-behavioral therapy (TF-CBT) developers to create TF-CBTWeb (http://tfcbt.musc.edu), which offers free resources for key treatment components, printable scripts, handouts, and instructions on handling challenging situations. To supplement TF-CBTWeb, Washington University in St. Louis and the University of Missouri have formed the Missouri Therapy Network (2013) to offer free TF-CBT training webinars, demonstration videos, and manuals (https://motherapynetwork.wustl.edu). National and state technical assistance centers also offer clinical webinars on a variety of topics. SAMHSA (2013) has funded the Disaster Technical Assistance Center (www.samhsa.gov/dtac) to offer webcasts on behavioral health training; the New York State Clinic Technical Assistance Center (2013) offers free webinars (www.ctacny.com) on important clinical topics, including cognitive-behavioral therapy, trauma assessment, and Motivational Interviewing.

Technology Advances in Practice

Technology advances are also revolutionizing the delivery of treatment to address patient needs and improve engagement. The structure and sequence of cognitive-behavioral therapy makes for a natural transition to interactive, computer, or web-based platforms (Baum, Epstein, & Kelleher, 2013). Cognitive-behavioral therapy for depression (e.g., Stressbuster) and anxiety (e.g., Camp-Copa-A-Lot) are available in CD-ROM packages and are associated with symptom reductions (Abeles et al., 2009; Khanna & Kendall, 2010). Online EBPs are appealing to children and families who are unable or unwilling to seek in-person treatment (Baum et al., 2013). For example, Triple P Online derives from the Triple P Positive Parenting Program, an EBP for parents of children with disruptive behavior. This online version allows parents to proceed through electronic modules at their own pace, and empirical evidence now exists for child behavioral outcomes and parent satisfaction (Sanders, Baker, & Turner, 2012). Effective online cognitive-behavioral treatments for depression include Master Your Mood Online (Gerrits, van der Zanden, Visscher, & Conijn, 2007) and MoodGYM (O’Kearney, Gibson, Christensen, & Griffiths, 2006). For anxiety, the BRAVE-ONLINE program exists (March, Spence, & Donovan, 2009). Diverse online peer support groups have also emerged in recent years to expand ancillary support for substance abuse in adolescents (Mermelstein (p. 615) & Turner, 2006) and children coping with parents’ medical conditions (Giesbers, Verdonck-de Leeuw, van Zuuren, Kleverlaan, & van der Linden, 2010). This trend in using digital technologies to deliver treatments, educational trainings, and supportive services will likely continue (Donovan, Spence, & March, 2013).

To support EBPs delivered in different technological modalities, web and mobile software applications are available for psychoeducation, symptom assessment, tracking of treatment progress, and communication between patients and clinicians (Baum et al., 2013; Luxton, McCann, Bush, Mishkind, & Reger, 2011). The myADHDportal.com, developed by Cincinnati Children’s Hospital Medical Center, offers training in office ADHD workflow and registers a child’s ADHD and side effect ratings by parents and teachers to aid diagnosis and monitoring of treatment (Baum et al., 2013). The portal also maintains secure communications among parents, teachers, and pediatricians during the treatment process (Baum et al., 2013). To improve self-awareness in adolescent depression, the Murdoch Children Research institute created the mobiletype program (Mobile Tracking Young People’s Experiences), a phone application that reminds users to monitor their daily mood, stress, and activities. These data are uploaded to a secure website and shared with the users’ physicians (Kauer et al., 2012). Although web and mobile data collection platforms may create ethical and confidentiality concerns (Luxton et al., 2011), their potential to streamline individual patient–clinician experiences and assist quality improvement should not be minimized (Baum et al., 2013).

Evidence-Based Clinical Decision Making

Given the EBP knowledge base in children’s mental health (Chorpita, Bernstein, & Daleiden, 2011; Silverman & Hinshaw, 2008), the field is turning to evidence-based clinical decision making to reach a larger portion of children with diverse clinical case mixes (Gomory, 2013) and to use electronic measurement systems to improve the quality of clinical decision making. Several scalable innovations have shown promising evidence.

The Modular Approach to Therapy for Children with anxiety, depression, trauma, or conduct problems (MATCH-ADTC; Chorpita & Weisz, 2009; Weisz et al., 2012) enables clinicians to conceptualize EBPs collectively rather than singly by offering a treatment package that consists of a guiding protocol for each problem area and 33 practice modules (e.g., a decision flowchart guiding module selection and sequencing for self-calming). In a two-state randomized controlled trial involving 84 clinicians and 174 treated children, MATCH-ADTC was compared with standard cognitive-behavioral psychotherapy and usual care. Results indicated that MATCH-ADTC produced significantly faster improvement, fewer diagnoses after treatment, and a balanced flexibility that resulted in more evidence-based treatment (Weisz et al., 2012).

An outgrowth of MATCH-ADTC is the Managing Adaptive Practice (MAP) tool, which provides clinicians access to the most updated scientific treatment information and detailed evidence-based treatment recommendations for specific problems (Southam-Gerow et al., 2014). The MAP web-based dashboard feedback system allows data collection on client outcomes. It also records the clinician’s use of practice elements throughout a client’s treatment trajectory. In Los Angeles County, youth treated by practitioners trained in the MAP tool demonstrated large effect sizes in the improvement of trauma and depression symptoms (Southam-Gerow et al., 2014).

Another clinical decision-making tool is the Contextualized Feedback System (CFS), which promotes clinicians’ practice through session-to-session documentation of psychometrically and clinically sound measures (e.g., client functioning) (Bickman, Kelley, Breda, de Andrade, & Riemer, 2011). Multisite trials of the CFS over a 2-year period showed that youths treated by clinicians who received weekly feedback from CFS improved faster than youths treated by clinicians who did not use CFS (Bickman et al., 2011). Another study (p. 616) examined the implementation challenges of embedding CFS into community-based mental health clinics in New York State (Hoagwood et al., 2014). Strategies for integrating CFS in routine use included mandating clinical documentation, developing site-specific project plans to manage implementation, and using weekly consultation calls to strengthen the appropriate use of the system (Hoagwood et al., 2014).

Treatment innovations such as MATCH-ADTC, MAP, and CFS can enhance client outcomes and can be adapted to fit the real-world context of divergent practices and settings. Their scalability in state systems can be extended to other kinds of systems, including healthcare systems, and even countries.

Task Shifting and Use of Peers in Family Support Services

A systemic approach to improving EBP delivery and care coordination not only is driven by policy mandates, but is also influenced by evolution of the clinical workforce. Changes in healthcare are leading to workforce shifts that redistribute specialist tasks to nonspecialists. Task shifting has a long history in global health and mental health initiatives in developing countries. It has transferred the roles previously assumed by more experienced and expensive providers to others with less formal training to provide therapeutic and support services. Task shifting has direct implications for the delivery of mental health services in both developed and underdeveloped countries (Kazdin & Rabbitt, 2013). The U.S. public mental health system is largely supported by bachelor’s-level counselors and social workers who are supervised by advanced mental health professionals. It entails the use of standardized trainings and simplified treatment protocols geared toward lay counselors, with a built-in model of monitoring and evaluation to ensure fidelity (Kazdin & Rabbitt, 2013).

An example of task shifting in children’s mental health is the employment of parents or caregivers who have raised a child with a mental health problem in working directly—family to family—with other parents/caregivers seeking services. These peer parents may deliver a range of services, including family support, intake, screening, referral, and group interventions (Hoagwood et al., 2010). One group treatment employs peer parents along with social workers in the Multiple Family Group intervention (McKay et al., 2011).

Family support services have become billable under Medicaid or federal block grants in 16 states (Center for Health Care Strategies Inc., 2012). In addition, family advocacy organizations report a national trend to certify family support specialists (Hoagwood et al., 2008). The evidence base for peer/parent-delivered services in children’s mental health is emerging (Hoagwood et al., 2010), but evidence for its impact on youth outcomes is needed (Blau et al., 2010; Hoagwood et al., 2010; Kutash, Duchnowski, Green, & Ferron, 2011).

One major challenge is the integration of family support services into agencies that provide an array of child-centered services. A study is under way in New York State to assist in understanding methods for integrating and assessing the quality of these services. To characterize 21 organizations that provide family support services in New York State, this study identified 14 organization-level and 27 family support services–level quality indicators (Olin, Kutash, et al., 2014). These indicators were significantly associated with organizational climate and culture (Olin, Williams, et al., 2014). The relationship between these quality indicators and the organizational social context suggests that some contextual aspects of agencies (role clarity, stress, decision making, job attitudes) may be malleable and could be improved to facilitate integration of high-quality family support services. These quality indicators may also be a useful tool for aligning family support services with other health services in the new healthcare context, as they provide metrics for monitoring quality.

Summary

Significant—even tectonic—shifts in healthcare policy, research, and practice have (p. 617) occurred in the past decade and have laid a new foundation for the work that lies ahead. ACA marks a significant policy shift; ACA and MHPAEA restructure mental health services under the umbrella of general health services. MHPAEA ensures that all individuals with mental health and substance abuse problems are given equitable care, care that is equivalent in value (i.e., in its financial requirements and treatment limitations) to medical benefits. The ACA’s emphasis on integrating and coordinating care, use of EHR, ACOs, health homes, and quality benchmarks holds providers accountable for outcomes. This is a major change for health and behavioral health systems. Under these new mandates, requirements, and structures, networks of service providers integrated within larger structures will be responsible for the health of the population under their purview.

The foci of research on children’s mental health during the decade 1990 to 2000 emphasized efficacy and effectiveness studies designed to strengthen the knowledge base on interventions and services that improved children’s outcomes. The emphasis in the past decade has advanced a broader set of aims, focusing on the translation of effective interventions and services into different contexts, settings, and systems. This shift has called for a different set of frameworks and theories that are oriented toward broader public health impact. This is the crux of the new scientific agenda in dissemination and implementation. It is leading to a set of research projects and a portfolio that tests strategies, methods, and designs to support large-scale system changes. The D&I research agenda, by definition, has to be practical and innovative with respect to partnerships with system designers, practitioners, and consumers/families. Studies of interventions targeted at organizational, policy, and even system changes will also be important. These include how to embed and implement effective practices into primary care, schools, child welfare systems, juvenile justice facilities, communities, and the healthcare system. With the latest funding interest in global mental health research, D&I studies will be needed to address, for example, the World Health Organization’s global development agenda after 2015 to improve mental health services research in low- and middle-income countries (NIMH, 2013). Further, as the National Institutes of Health (2012) awarded $100 million to fund 11 Autism Centers of Excellence, research on diagnosis and treatment will reflect a stronger focus on genetics and neuroscience in the coming years (Insel, 2013).

As major changes in emphasis and direction have been shaped by advances in policy and research, the practice of mental health services is also shifting. Training models to install EBPs in the hands of front-line practitioners (i.e., primary care physicians, nurses, social workers, teachers, case managers, peer/parent partners) have been developed and are being tested. Yet, unmet service needs persist. Child-serving sectors (e.g., primary care, schools, mental health clinics, child welfare agencies, juvenile justice facilities) face significant challenges: heavy caseloads, long waiting lists, more distressed families, and changes in reimbursement structures away from volume only (as in fee-for-service environments) and toward accountability for outcomes. To adapt to this new environment, clinicians need tools and resources to provide effective and efficient services. These include tele-health consultation, supervision models that attend to specific changes in outcomes, and clinical decision-making tools. The behavioral health workforce will continue to expand as states and healthcare systems expand Medicaid services and health insurance coverage under the ACA. Workforce expansion will include training individuals who enter the workforce with less formal training and require more targeted skills. These workforce changes will also require different trainings not only on specific EBP skills but also on organizational issues related to the culture and climate of the work environment. These may include team building (Kutash et al., 2014), organizational problem solving (Glisson, Hemmelgarn, et al., 2012; Glisson & Schoenwald, 2005), and use of quality indicators (Olin, Kutash, et al., 2014; Olin, Williams, et al., 2014).

(p. 618) Conclusion

The policy, research, and practice changes that have occurred in the past decade are altering the fundamental infrastructure of mental health services for children and adolescents. These changes necessitate that policymakers, researchers, practitioners, and consumers/families form new alliances and partnerships among themselves and with healthcare systems. These new alliances and networks, if structured correctly, have the potential to provide, for the first time, quality health and mental health care to the millions of children and their families who suffer unnecessarily. Aligning policy, research, and practice in the service of improved quality of life for children with mental health needs should be our horizon line.