Using Measurement-Based Care to Enhance Any Treatment

Measurement-based Care in Psychiatry-Past, Present, and Future

The authors define measurement-based care (MBC) in psychiatry as the use of validated clinical measurement instruments to objectify the assessment, treatment, and clinical outcomes, including efficacy, safety, tolerability, functioning, and quality of life, in patients with psychiatric disorders. MBC includes two processes: routine assessments, such as measuring the severity of symptoms with rating scales, and the use of assessments in decision-making. MBC implementation was tested in the Texas Medication Algorithm Project and the German Algorithm Project and has been shown to improve patient outcomes. Even though more recent research has shown the many benefits of MBC compared to the usual care, MBC is still not the standard of care in psychiatric practice. This review article addresses the advantages of MBC, the barriers to implementing MBC in clinical practice, and the basic properties of MBC instruments. Recent developments in the 21st century that are expected to accelerate the adoption of MBC in clinical practice, including electronic health records, health information technology, and the development of the Standard for Clinicians' lnterview in Psychiatry (SCIP) as an MBC tool, will be reviewed. The authors recommend including MBC in psychiatry residency training to promote its use in future generations.

Enhancing implementation of measurement-based mental health care in primary care: a mixed-methods randomized effectiveness evaluation of implementation facilitation

BACKGROUND

Mental health care lags behind other forms of medical care in its reliance on subjective clinician assessment. Although routine use of standardized patient-reported outcome measures, measurement-based care (MBC), can improve patient outcomes and engagement, clinician efficiency, and, collaboration across care team members, full implementation of this complex practice change can be challenging. This study seeks to understand whether and how an intensive facilitation strategy can be effective in supporting the implementation of MBC. Implementation researchers partnering with US Department of Veterans Affairs (VA) leaders are conducting the study within the context of a national initiative to support MBC implementation throughout VA mental health services. This study will focus specifically on VA Primary Care-Mental Health Integration (PCMHI) programs.

METHODS

A mixed-methods, multiple case study design will include 12 PCMHI sites recruited from the 23 PCMHI programs that volunteered to participate in the VA national initiative. Guided by a study partnership panel, sites are clustered into similar groups using administrative metrics. Site pairs are recruited from within these groups. Within pairs, sites are randomized to the implementation facilitation strategy (external facilitation plus QI team) or standard VA national support. The implementation strategy provides an external facilitator and MBC experts who work with intervention sites to form a QI team, develop an implementation plan, and, identify and overcome barriers to implementation. The RE-AIM framework guides the evaluation of the implementation facilitation strategy which will utilize data from administrative, medical record, and primary qualitative and quantitative sources. Guided by the iPARIHS framework and using a mixed methods approach, we will also examine factors associated with implementation success. Finally, we will explore whether implementation of MBC increases primary care team communication and function related to the care of mental health conditions.

DISCUSSION

MBC has significant potential to improve mental health care but it represents a major change in practice. Understanding factors that can support MBC implementation is essential to attaining its potential benefits and spreading these benefits across the health care system.

A Method for Tracking Implementation Strategies: An Exemplar Implementing Measurement-Based Care in Community Behavioral Health Clinics

Implementation experts suggest tailoring strategies to the intended context may enhance outcomes. However, it remains unclear which strategies are best suited to address specific barriers to implementation, in part because few measurement methods exist that adhere to recommendations for reporting. In the context of a dynamic cluster randomized trial comparing a standardized to tailored approach to implementing measurement-based care (MBC), this study aimed to (a) describe a method for tracking implementation strategies, (b) demonstrate the method by tracking strategies generated by teams tasked with implementing MBC at their clinics in the tailored condition, and (c) conduct preliminary examinations of the relation between strategy use and implementation outcomes (i.e., self-reported fidelity to MBC). The method consisted of a coding form based on Proctor, Powell, and McMillen (2013) implementation strategy reporting guidelines and Powell et al.'s (2012) taxonomy to facilitate specification of the strategies. A trained research specialist coded digitally recorded implementation team meetings. The method allowed for the following characterization of strategy use. Each site generated 39 unique strategies across an average of six meetings in five months. There was little variability in the use of types of implementation strategies across sites with the following order of prevalence: quality management (50.00%), restructuring (16.53%), communication (15.68%), education (8.90%), planning (7.20%), and financing (1.69%). We identified a new category of strategies not captured by the existing taxonomy, labeled "communication." There was no evidence that number of implementation strategies enacted was statistically significantly associated with changes in self-reported fidelity to MBC-however, financing strategies were associated with increased fidelity. This method has the capacity to yield rich data that will inform investigations into tailored implementation approaches.

Quality of life and well-being following inpatient and partial hospitalization treatment for opioid use disorder

Treatment of opioid use disorder often begins with brief intensive inpatient or outpatient programs. Given the high relapse rates following intensive treatment, it is important to determine factors that lead to success post-discharge. Incorporating assessment during and early post-discharge may help determine such factors. The current study evaluated changes in quality of life among individuals during and after discharge from inpatient and partial hospitalization opiate treatment programs. Participants (n = 143) were recruited while in the programs and were re-assessed one month later (n = 113). Results found improvements in quality of life and reductions in rates of opiate use at follow-up. Individuals with greater improvements in Health, Substance Use, and Emotional Health domains were less likely to have relapsed. Treatment utilization post-discharge was not associated with relapse. Findings emphasize the importance of measurement-based care and suggest the need to assess indicators of treatment success beyond rates of relapse.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.

Quality Improvement in Health Care: The Role of Psychologists and Psychology

Quality Improvement (QI) is a health care interprofessional team activity wherein psychology as a field and individual psychologists in health care settings can and should adopt a more robust presence. The current article makes the argument for why psychology's participation in QI is good for health care, is good for our profession, and is the right thing to do for the patients and families we serve. It reviews the varied ways individual psychologists and our profession can integrate quality processes and improve health care through: (1) our approach to our daily work; (2) our roles on health care teams and involvement in organizational initiatives; (3) opportunities for teaching and scholarship; and (4) system redesign and advocacy within our health care organizations and health care environment.

Best practices in supervising cognitive behavioral therapy with youth

Clinical supervision of cognitive behavioral therapy (CBT) with youth ensures better patient care and fosters trainees' professional development. However, often insufficient attention is directed toward disseminating best practices in supervision of CBT with youth. This Therapeutic Advances contribution aims to communicate the core content of supervision. Additionally, the key supervisory practices associated with CBT with youth are described. Supervisory outcomes are summarized and recommendations for supervisory practices are made.

Implementing measurement based care in community mental health: a description of tailored and standardized methods

Objective

Although tailored implementation methods are touted as superior to standardized, few researchers have directly compared the two and little guidance regarding the specific details of each method exist. Our study compares these methods in a dynamic cluster randomized trial seeking to optimize implementation of measurement based care (MBC) for depression in community behavioral health. This specific manuscript provides a detailed, replicable account of the components of each multi-faceted implementation method.

Results

The standardized best practice method includes training, consultation, a clinical guideline, and electronic health record enhancements with the goal to optimize the delivery of MBC with fidelity. Conversely, the tailored, customized and collaborative method is informed by recent implementation science advancements and begins with a needs assessment, followed by tailored training that feeds back barriers data to clinicians, the formation of an implementation team, a clinician-driven clinic-specific guideline, and the use of fidelity data to inform implementation team activities; the goal of the tailored condition is to ensure the intervention and implementation strategies address unique factors of the context. The description of these methods will inform others seeking to implement MBC, as well as those planning to use standardized or tailored implementation methods for interventions beyond behavioral health.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3193-0) contains supplementary material, which is available to authorized users.

Psychometric assessment of three newly developed implementation outcome measures

BACKGROUND

Implementation outcome measures are essential for monitoring and evaluating the success of implementation efforts. Yet, currently available measures lack conceptual clarity and have largely unknown reliability and validity. This study developed and psychometrically assessed three new measures: the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM).

METHODS

Thirty-six implementation scientists and 27 mental health professionals assigned 31 items to the constructs and rated their confidence in their assignments. The Wilcoxon one-sample signed rank test was used to assess substantive and discriminant content validity. Exploratory and confirmatory factor analysis (EFA and CFA) and Cronbach alphas were used to assess the validity of the conceptual model. Three hundred twenty-six mental health counselors read one of six randomly assigned vignettes depicting a therapist contemplating adopting an evidence-based practice (EBP). Participants used 15 items to rate the therapist's perceptions of the acceptability, appropriateness, and feasibility of adopting the EBP. CFA and Cronbach alphas were used to refine the scales, assess structural validity, and assess reliability. Analysis of variance (ANOVA) was used to assess known-groups validity. Finally, half of the counselors were randomly assigned to receive the same vignette and the other half the opposite vignette; and all were asked to re-rate acceptability, appropriateness, and feasibility. Pearson correlation coefficients were used to assess test-retest reliability and linear regression to assess sensitivity to change.

RESULTS

All but five items exhibited substantive and discriminant content validity. A trimmed CFA with five items per construct exhibited acceptable model fit (CFI = 0.98, RMSEA = 0.08) and high factor loadings (0.79 to 0.94). The alphas for 5-item scales were between 0.87 and 0.89. Scale refinement based on measure-specific CFAs and Cronbach alphas using vignette data produced 4-item scales (α's from 0.85 to 0.91). A three-factor CFA exhibited acceptable fit (CFI = 0.96, RMSEA = 0.08) and high factor loadings (0.75 to 0.89), indicating structural validity. ANOVA showed significant main effects, indicating known-groups validity. Test-retest reliability coefficients ranged from 0.73 to 0.88. Regression analysis indicated each measure was sensitive to change in both directions.

CONCLUSIONS

The AIM, IAM, and FIM demonstrate promising psychometric properties. Predictive validity assessment is planned.

Measurement-Based Care in Psychiatry

Measurement-based care (MBC) uses patient-reported rating scales in conjunction with evidence-based clinical practice guidelines to provide an objective assessment of patient progress over time to guide a more precise plan of care. Use of MBC is routine in medical disease management. Unfortunately, MBC is not standard practice in psychiatric care. The current nonsystematic approach to the delivery of mental health care has created considerable variability in practice and may stall recovery. Although MBC has proven benefits, there are perceived barriers to its implementation. Greater research is needed to standardize psychiatric measures and clinical practice guidelines and determine the most effective implementation strategies. A review of the literature was conducted to (a) provide an overview of MBC and relevant screening tools; (b) examine the clinical use of MBC, including its relevance to evidence-based clinical guidelines and empirical support; and (c) detail the benefits and challenges of MBC implementation. As mental health care moves in the direction of value-driven incentives, it will be important for providers and organizations to consider MBC as an evidence-based framework to reduce variability in psychiatric treatment and improve patient outcomes. [Journal of Psychosocial Nursing and Mental Health Services, 55(11), 30-35.].

Digital technology and clinical decision making in depression treatment: Current findings and future opportunities

Clinical decision making encompasses a broad set of processes that contribute to the effectiveness of depression treatments. There is emerging interest in using digital technologies to support effective and efficient clinical decision making. In this paper, we provide "snapshots" of research and current directions on ways that digital technologies can support clinical decision making in depression treatment. Practical facets of clinical decision making are reviewed, then research, design, and implementation opportunities where technology can potentially enhance clinical decision making are outlined. Discussions of these opportunities are organized around three established movements designed to enhance clinical decision making for depression treatment, including measurement-based care, integrated care, and personalized medicine. Research, design, and implementation efforts may support clinical decision making for depression by (1) improving tools to incorporate depression symptom data into existing electronic health record systems, (2) enhancing measurement of treatment fidelity and treatment processes, (3) harnessing smartphone and biosensor data to inform clinical decision making, (4) enhancing tools that support communication and care coordination between patients and providers and within provider teams, and (5) leveraging treatment and outcome data from electronic health record systems to support personalized depression treatment. The current climate of rapid changes in both healthcare and digital technologies facilitates an urgent need for research, design, and implementation of digital technologies that explicitly support clinical decision making. Ensuring that such tools are efficient, effective, and usable in frontline treatment settings will be essential for their success and will require engagement of stakeholders from multiple domains.

Dimensionality of DSM-5 posttraumatic stress disorder and its association with suicide attempts: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III

BACKGROUND

Emerging confirmatory factor analytic (CFA) studies suggest that posttraumatic stress disorder (PTSD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) is best characterized by seven factors, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal. The seven factors, however, have been found to be highly correlated, suggesting that one general factor may exist to explain the overall correlations among symptoms.

METHODS

Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, a large, national survey of 36,309 U.S. adults ages 18 and older, this study proposed and tested an exploratory bifactor hybrid model for DSM-5 PTSD symptoms. The model posited one general and seven specific latent factors, whose associations with suicide attempts and mediating psychiatric disorders were used to validate the PTSD dimensionality.

RESULTS

The exploratory bifactor hybrid model fitted the data extremely well, outperforming the 7-factor CFA hybrid model and other competing CFA models. The general factor was found to be the single dominant latent trait that explained most of the common variance (~76%) and showed significant, positive associations with suicide attempts and mediating psychiatric disorders, offering support to the concurrent validity of the PTSD construct.

CONCLUSIONS

The identification of the primary latent trait of PTSD confirms PTSD as an independent psychiatric disorder and helps define PTSD severity in clinical practice and for etiologic research. The accurate specification of PTSD factor structure has implications for treatment efforts and the prevention of suicidal behaviors.

Patterns of practice in community mental health treatment of adult depression

OBJECTIVE

Community mental health therapists often endorse an eclectic orientation, but few studies reveal how therapists utilize elements of evidence-based psychotherapies. This study aimed to characterize treatment as usual patterns of practice among therapists treating depressed adults in community mental health settings.

METHOD

Therapists (N = 165) from the USA's largest not-for-profit provider of community-based mental health services completed surveys assessing their demographics and practice element use with depressed adult clients. Specifically, therapists indicated whether they utilized each of 45 unique practice elements from the following evidence-based psychotherapies: Acceptance and Commitment Therapy, Behavioral Activation, Brief Psychodynamic Therapy, Cognitive Behavioral Therapy (CBT), Interpersonal Therapy, Mindfulness-Based CBT, Problem-Solving Therapy, and Self-Control Therapy. Principal component analysis was employed to identify practice patterns.

RESULTS

The principal component analysis included 31 practice elements and revealed a three-factor model with distinct patterns of practice that did not align with traditional evidence-based practice approaches, including: (i) Planning, Practice, and Monitoring; (ii) Cognitive, Didactic, and Interpersonal; and (iii) Between Session Activities.

CONCLUSIONS

Therapist-reported practice patterns confirmed an eclectic approach that brought together elements from theoretically distinct evidence-based psychotherapies. Future research is needed to explore how these patterns of practice relate to client outcomes to inform focused training and/or de-implementation efforts.

A Digital Feedback System to Support Implementation of Measurement-Based Care by School-Based Mental Health Clinicians

Evidence supports the utility of measurement-based care (MBC) to improve youth mental health outcomes, but clinicians rarely engage in MBC practices. Digital measurement feedback systems (MFS) may reflect a feasible strategy to support MBC adoption and sustainment. This pilot study was initiated to evaluate the impact of a MFS and brief consultation supports to facilitate MBC uptake and sustainment among mental health clinicians in the education sector, the most common mental health service delivery setting for youth. Following an initial training in MBC, 14 clinicians were randomized to either a digital MFS and brief consultation supports or control. Baseline ratings of MBC attitudes, skill, and use were collected. In addition, daily assessment ratings tracked 2 core MBC practices (i.e., assessment tool administration, provision of feedback) over a 6-month follow-up period. Clinicians in the MFS condition demonstrated rapid increases in both MBC practices, whereas the control group did not significantly change. For clinicians in the MFS group, consultation effects were significant for feedback and approached significance for administration. Over the follow-up period, average decreases in the current study were moderate with only 1 of the 2 outcome variables (administration) decreasing significantly. Inspection of individual clinician trajectories revealed substantial within-group trend variation. MFS may represent an effective MBC implementation strategy beyond initial training, although individual clinician response is variable. Identifying feasible and impactful implementation strategies is critical given the ability of MBC to support precision health care.

Capabilities and Characteristics of Digital Measurement Feedback Systems: Results from a Comprehensive Review

Measurement feedback systems (MFS) are a class of health information technology (HIT) that function as an implementation support strategy for integrating measurement based care or routine outcome monitoring into clinical practice. Although many MFS have been developed, little is known about their functions. This paper reports findings from an application of health information technology-academic and commercial evaluation (HIT-ACE), a systematic and consolidated evaluation method, to MFS designed for use in behavioral healthcare settings. Forty-nine MFS were identified and subjected to systematic characteristic and capability coding. Results are presented with respect to the representation of characteristics and capabilities across MFS.

Progress Monitoring in an Integrated Health Care System: Tracking Behavioral Health Vital Signs

Progress monitoring implementation in an integrated health care system is a complex process that must address factors such as measurement, technology, delivery system care processes, patient needs and provider requirements. This article will describe how one organization faced these challenges by identifying the key decision points (choice of measure, process for completing rating scale, interface with electronic medical record and clinician engagement) critical to implementation. Qualitative and quantitative data will be presented describing customer and stakeholder satisfaction with the mental health progress monitoring tool (MHPMT) as well as organizational performance with key measurement targets.

Determinants and Functions of Standardized Assessment Use Among School Mental Health Clinicians: A Mixed Methods Evaluation

The current study evaluated why and how school mental health clinicians use standardized assessment tools in their work with youth and families. Quantitative and qualitative (focus group) data were collected prior to and following a training and consultation sequence as part of a trial program to assess school clinician's (n = 15) experiences administering standardized tools to youth on their caseloads (n = 191). Findings indicated that, although assessment use was initially somewhat low, clinicians used measures to conduct initial assessments with the bulk of their caseloads (average = 62.2%) during the implementation period. Clinicians also reported on factors influencing their use of assessments at the client, provider, and system levels; perceived functions of assessment; student responses to assessment use; and use of additional sources of clinically-relevant information (primarily educational data) for the purposes of assessment and progress monitoring. Implications for the contextual appropriateness of standardized assessment and training in assessment tools are discussed.

Health Information Technologies-Academic and Commercial Evaluation (HIT-ACE) methodology: description and application to clinical feedback systems

Background

Health information technologies (HIT) have become nearly ubiquitous in the contemporary healthcare landscape, but information about HIT development, functionality, and implementation readiness is frequently siloed. Theory-driven methods of compiling, evaluating, and integrating information from the academic and commercial sectors are necessary to guide stakeholder decision-making surrounding HIT adoption and to develop pragmatic HIT research agendas. This article presents the Health Information Technologies—Academic and Commercial Evaluation (HIT-ACE) methodology, a structured, theory-driven method for compiling and evaluating information from multiple sectors. As an example demonstration of the methodology, we apply HIT-ACE to mental and behavioral health measurement feedback systems (MFS). MFS are a specific class of HIT that support the implementation of routine outcome monitoring, an evidence-based practice.

Results

HIT-ACE is guided by theories and frameworks related to user-centered design and implementation science. The methodology involves four phases: (1) coding academic and commercial materials, (2) developer/purveyor interviews, (3) linking putative implementation mechanisms to hit capabilities, and (4) experimental testing of capabilities and mechanisms. In the current demonstration, phase 1 included a systematic process to identify MFS in mental and behavioral health using academic literature and commercial websites. Using user-centered design, implementation science, and feedback frameworks, the HIT-ACE coding system was developed, piloted, and used to review each identified system for the presence of 38 capabilities and 18 additional characteristics via a consensus coding process. Bibliometic data were also collected to examine the representation of the systems in the scientific literature. As an example, results are presented for the application of HIT-ACE phase 1 to MFS wherein 49 separate MFS were identified, reflecting a diverse array of characteristics and capabilities.

Conclusions

Preliminary findings demonstrate the utility of HIT-ACE to represent the scope and diversity of a given class of HIT beyond what can be identified in the academic literature. Phase 2 data collection is expected to confirm and expand the information presented and phases 3 and 4 will provide more nuanced information about the impact of specific HIT capabilities. In all, HIT-ACE is expected to support adoption decisions and additional HIT development and implementation research.

A qualitative study of perceived needs and factors associated with the quality of care for common mental disorders in patients with chronic diseases: the perspective of primary care clinicians and patients

BACKGROUND

The prevalence of comorbid anxiety and depressive disorders is high among patients with chronic diseases in primary care, and is associated with increased morbidity and mortality rates. The detection and treatment of common mental disorders in patients with chronic diseases can be challenging in the primary care setting. This study aims to explore the perceived needs, barriers and facilitators for the delivery of mental health care for patients with coexisting common mental disorders and chronic diseases in primary care from the clinician and patient perspectives.

METHODS

In this qualitative descriptive study, we conducted semi-structured interviews with clinicians (family physician, nurse, psychologist, social worker; n = 18) and patients (n = 10) from three primary care clinics in Quebec, Canada. The themes explored included clinician factors (e.g., attitudes, perception of roles, collaboration, management of clinical priorities) and patient factors (e.g., needs, preferences, access to care, communication with health professionals) associated with the delivery of care. Qualitative data analysis was conducted based on an interactive cyclical process of data reduction, data display and conclusion drawing and verification.

RESULTS

Clinician interviews highlighted a number of needs, barriers and enablers in the provision of patient services, which related to inter-professional collaboration, access to psychotherapy, polypharmacy as well as communication and coordination of services within the primary care clinic and the local network. Two specific facilitators associated with optimal mental health care were the broadening of nurses' functions in mental health care and the active integration of consulting psychiatrists. Patients corroborated the issues raised by the clinicians, particularly in the domains of whole-person care, service accessibility and care management.

CONCLUSIONS

The results of this project will contribute to the development of quality improvement interventions to increase the uptake of organizational and clinical evidence-based practices for patients with chronic diseases and concurrent common mental disorders, in priority areas including collaborative care, access to psychotherapy and linkages with specialized mental health care.

Defined symptom-change trajectories during acute-phase cognitive therapy for depression predict better longitudinal outcomes

BACKGROUND

Acute-phase cognitive therapy (CT) is an efficacious treatment for major depressive disorder (MDD), but responders experience varying post-acute outcomes (e.g., relapse vs. recovery). Responders' symptom-change trajectories during response to acute-phase CT may predict longer term outcomes.

METHOD

We studied adult outpatients (N = 220) with recurrent MDD who responded to CT but had residual symptoms. Responders with linear (steady improvement), log-linear (quicker improvement earlier and slower later), one-step (a single, relatively large, stable improvement between adjacent assessments), or undefined (not linear, log-linear, or one-step) symptom trajectories were assessed every 4 months for 32 additional months.

RESULTS

Defined (linear, log-linear, one-step) versus undefined acute-phase trajectories predicted lower depressive symptoms (d = 0.36), lower weekly probability of being in a major depressive episode (OR = 0.46), higher weekly probabilities of remission (OR = 1.93) and recovery (OR = 2.35), less hopelessness (d = 0.41), fewer dysfunctional attitudes (d = 0.31), and better social adjustment (d = 0.32) for 32 months after acute-phase CT. Differences among defined trajectory groups were nonsignificant.

CONCLUSIONS

Responding to acute-phase CT with a defined trajectory (orderly pattern) of symptom reduction predicts better longer term outcomes, but which defined trajectory (linear, log-linear, or one-step) appears unimportant. Frequent measurement of depressive symptoms to identify un/defined CT response trajectories may clarify need for continued clinical monitoring and treatment.

User-Centered Design for Psychosocial Intervention Development and Implementation

The current paper articulates how common difficulties encountered when attempting to implement or scale-up evidence-based treatments are exacerbated by fundamental design problems, which may be addressed by a set of principles and methods drawn from the contemporary field of user-centered design. User-centered design is an approach to product development that grounds the process in information collected about the individuals and settings where products will ultimately be used. To demonstrate the utility of this perspective, we present four design concepts and methods: (a) clear identification of end users and their needs, (b) prototyping/rapid iteration, (c) simplifying existing intervention parameters/procedures, and (d) exploiting natural constraints. We conclude with a brief design-focused research agenda for the developers and implementers of evidence-based treatments.

Penn State Worry Questionnaire - 10: A new tool for measurement-based care

The Penn State Worry Questionnaire - Past Week (PSWQ-PW) is an adaptation of the widely used Penn State Worry Questionnaire, measuring pathological worry weekly. However, it contains problematic negatively worded items and has not been validated in a large sample yet. To meet the needs of measurement-based care (MBC), we developed a shortened version (PSWQ-10) based on the PSWQ-PW, retaining only positively worded items, and examined its psychometric properties and clinical utility. Patients with Generalized Anxiety Disorder (GAD), Major Depressive Disorder (MDD), and other anxiety disorders completed the PSWQ-10 and other instruments during routine evaluation in an academic anxiety clinic. A second cohort from a perinatal clinic was evaluated similarly. The PSWQ-10 displayed excellent internal consistency, convergent and discriminant validity, and criterion group validity. Patients with GAD scored significantly higher than those with other anxiety disorders but did not differ from those with MDD. The PSWQ-10 showed sensitivity to change over time and demonstrated excellent psychometric properties in the perinatal population. The PSWQ-10 is a reliable, valid, efficient, and straightforward worry-focused instrument that can be readily used in MBC and help clinicians objectively measure worry as a treatment outcome in broad clinical populations.

Applying User Input to the Design and Testing of an Electronic Behavioral Health Information System for Wraparound Care Coordination

Health information technology (HIT) and care coordination for individuals with complex needs are high priorities for quality improvement in health care. However, there is little empirical guidance about how best to design electronic health record systems and related technologies to facilitate implementation of care coordination models in behavioral health, or how best to apply user input to the design and testing process. In this paper, we describe an iterative development process that incorporated user/stakeholder perspectives at multiple points and resulted in an electronic behavioral health information system (EBHIS) specific to the wraparound care coordination model for youth with serious emotional and behavioral disorders. First, we review foundational HIT research on how EBHIS can enhance efficiency and outcomes of wraparound that was used to inform development. After describing the rationale for and functions of a prototype EBHIS for wraparound, we describe methods and results for a series of six small studies that informed system development across four phases of effort-predevelopment, development, initial user testing, and commercialization-and discuss how these results informed system design and refinement. Finally, we present next steps, challenges to dissemination, and guidance for others aiming to develop specialized behavioral health HIT. The research team's experiences reinforce the opportunity presented by EBHIS to improve care coordination for populations with complex needs, while also pointing to a litany of barriers and challenges to be overcome to implement such technologies.

Clinical and economic impact of non-adherence to antidepressants in major depressive disorder: A systematic review

BACKGROUND

Medication non-adherence is one of the major challenges in treating patients with depression. This systematic review aims to determine the clinical and economic outcomes of non-adherence in depression.

METHODS

A systematic search was performed across the following databases: PubMed, EMBASE, DARE, CINAHL, PsycINFO, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews; from database inception to March 31, 2015. Studies must report on the association between adherence and outcomes, and English full texts needed to be available. The quality of each study was assessed using the Newcastle-Ottawa scale.

RESULTS

A total of 11 articles were included, with eight reporting on clinical outcomes, two reporting on economic outcomes, and one reporting on both. The majority of studies were retrospective cohort studies. The mean quality of all included studies was 7, with a range from 3 to 9. Results clearly indicate that patients who were non-adherent were more likely to experience increased risks of relapse and/or recurrence, emergency department visits, and hospitalization rates; increased severity of depression, and a decrease in response and remission rates. The worsening of clinical outcomes in patients who were non-adherent subsequently translated to an increase in healthcare utilization and charges.

LIMITATIONS

No standardized adherence measurement tools were used, and few studies looked at the economic impact of non-adherence in depression.

CONCLUSION

There is a strong association between non-adherence to antidepressants and a worsening of patients' clinical and economic outcomes. Cost-effective interventions should be directed to this group of patients to improve medication adherence.

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

BACKGROUND

Within the past decade, health care service and research priorities have shifted from evidence-based medicine to personalized medicine. In mental health care, a similar shift to personalized intervention may boost the effectiveness and clinical utility of empirically supported therapies (ESTs). 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, although challenging, could markedly alter the nature of mental health care and the benefit provided to youths and families.

Student Perceptions of the Acceptability and Utility of Standardized and Idiographic Assessment in School Mental Health

Evidence-based assessment (EBA) comprises the use of research and theory to select methods and processes that have demonstrated reliability, validity, and clinical usefulness for prescribed populations. EBA can lead to positive clinical change, and recent work has suggested that it is perceived to be useful by school mental health providers. However, virtually nothing is known about student perceptions of assessment use. Semi-structured interviews were conducted with 31 ethnically diverse middle and high school students (71% female) receiving mental health services in school-based health centers. Findings indicated that the majority of students found assessments to be useful, and perceived three primary functions of assessments: structuring the therapy session, increasing students' self-awareness, and improving communication with the provider. Barriers to acceptability were also found for a minority of respondents. Some students found the nature of standardized assessments to be confining, and others expressed that they wanted more feedback from their counselors about their responses. Idiographic assessments demonstrated especially high acceptability in this sample, with students reporting that tracking idiographic outcomes increased self-awareness, spurred problem-solving, and helped them to reach behavioral goals. Implications for school mental health service improvements are discussed.

Mobile mental health interventions following war and disaster

Mobile technologies offer potentially critical ways of delivering mental health support to those experiencing war, ethnic conflict, and human-caused and natural disasters. Research on Internet interventions suggests that effective mobile mental health technologies can be developed, and there are early indications that they will be acceptable to war and disaster survivors, and prove capable of greatly increasing the reach of mental health services. Promising mhealth interventions include video teleconferencing, text messaging, and smartphone-based applications. In addition, a variety of social media platforms has been used during and immediately after disasters to increase agility in responding, and strengthen community and individual resilience. Globally, PTSD Coach has been downloaded over 243,000 times in 96 countries, and together with large-scale use of social media for communication during disasters, suggests the potential for reach of app technology. In addition to enabling improved self-management of post-trauma problems, mobile phone interventions can also enhance delivery of face-to-face care by mental health providers and increase the effectiveness of peer helpers and mutual aid organizations. More research is needed to establish the efficacy of mhealth interventions for those affected by war and disaster. Research should also focus on the identification of active elements and core processes of change, determination of effective ways of increasing adoption and engagement, and explore ways of combining the various capabilities of mobile technologies to maximize their impact.

Implementing measurement-based care (iMBC) for depression in community mental health: a dynamic cluster randomized trial study protocol

Background

Measurement-based care is an evidence-based practice for depression that efficiently identifies treatment non-responders and those who might otherwise deteriorate [1]. However, measurement-based care is underutilized in community mental health with data suggesting fewer than 20 % of behavioral health providers using this practice to inform treatment. It remains unclear whether standardized or tailored approaches to implementation are needed to optimize measurement-based care fidelity and penetration. Moreover, there is some suggestion that prospectively tailored interventions that are designed to fit the dynamic context may optimize public health impact, though no randomized trials have yet tested this notion [2]. This study will address the following three aims: (1) To compare the effect of standardized versus tailored MBC implementation on clinician-level and client-level outcomes; (2) To identify contextual mediators of MBC fidelity; and (3) To explore the impact of MBC fidelity on client outcomes.

Methods/design

This study is a dynamic cluster randomized trial of standardized versus tailored measurement-based care implementation in Centerstone, the largest provider of community-based mental health services in the USA. This prospective, mixed methods implementation-effectiveness hybrid design allows for evaluation of the two conditions on both clinician-level (e.g., MBC fidelity) and client-level (depression symptom change) outcomes. Central to this investigation is the focus on identifying contextual factors (e.g., attitudes, resources, process, etc.) that mediate MBC fidelity and optimize client outcomes.

Discussion

This study will contribute generalizable and practical strategies for implementing systematic symptom monitoring to inform and enhance behavioral healthcare.

Trial registration

Clinicaltrials.gov NCT02266134.

Electronic supplementary material

The online version of this article (doi:10.1186/s13012-015-0313-2) contains supplementary material, which is available to authorized users.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.