Measurement-based Care Research Articles

Role of Institutional Support for Evidence-Based Psychotherapy in Satisfaction and Burnout Among Veterans Affairs Therapists.

Burnout is widespread among psychotherapists and leads to negative mental and other health outcomes, absenteeism, and turnover. Job resources, including institutional support for evidence-based practices, can buffer against burnout and may improve satisfaction among therapists. The Veterans Health Administration (VHA) is the nation's largest integrated health system and employs 23,000 therapists, including psychologists, social workers, and counselors. The authors assessed associations between perceived institutional support for evidence-based treatment and satisfaction and burnout among VHA therapists. This analysis used data from the VHA's national 2018 Mental Health Provider Survey. Responding therapists (N=5,341) answered questions about the quality of mental health care and job satisfaction. Multilevel logistic regression models were used to predict burnout and satisfaction. The authors tested availability of evidence-based treatment and measurement-based care (MBC) as predictors; analyses were adjusted for therapist workload, demographic characteristics, and potential clustering by facility. VHA therapists had less burnout and more job satisfaction when they perceived receiving institutional support for evidence-based psychotherapy (EBP) and MBC, irrespective of whether the analyses were adjusted for workload. Less difficulty in scheduling EBP was significantly associated with decreased likelihood of burnout (OR=0.83, p<0.001) and increased satisfaction (OR=1.09, p=0.008). Less difficulty ending psychotherapy was significantly associated with decreased likelihood of burnout (OR=0.89, p=0.002) and increased satisfaction (OR=1.12, p=0.004). Support for evidence-based practices, including EBP and MBC, was closely linked to VHA therapists' satisfaction and burnout. Expanding support for therapists to provide evidence-based treatment may benefit therapists, patients, and the health care system.

Stigma towards opioid use disorder in primary care remain a barrier to integrating software-based measurement based care

BackgroundOpioid use disorder (OUD) is a deadly illness that remains undertreated, despite effective pharmacological treatments. Barriers, such as stigma, treatment affordability, and a lack of training and prescribing within medical practices result in low access to treatment. Software-delivered measurement-based care (MBC) is one way to increase treatment access. MBC uses systematic patient symptom assessments to inform an algorithm to support clinicians at critical decision points.MethodFocus groups of faculty clinicians (N = 33) from 3 clinics were conducted to understand perceptions of OUD diagnosis and treatment and whether a computerized MBC model might assist with diagnosis and treatment. Themes from the transcribed focus groups were identified in two phases: (1) content analysis focused on uncovering general themes; and (2) systematic coding and interpretation of the data.ResultsAnalysis revealed six major themes utilized to develop the coding terms: “distinguishing between chronic pain and OUD,” “current practices with patients using prescribed or illicit opioids or other drugs,” “attitudes and mindsets about providing screening or treatment for OUD in your practice,” “perceived resources needed for treating OUD,” “primary care physician role in patient care not specific to OUD,” and “reactions to implementation of proposed clinical decision support tool.”ConclusionResults revealed that systemic and attitudinal barriers to screening, diagnosing, and treating OUD continue to persist. Providers tended to view the software-based MBC program favorably, indicating that it may be a solution to increasing accessibility to OUD treatment; however, further interventions to combat stigma would likely be needed prior to implementation of these programs.Trial RegistrationClinicalTrials.gov; NCT04059016; 16 August 2019; retrospectively registered; https://clinicaltrials.gov/ct2/show/NCT04059016.

Gender differences in transdiagnostic domains and function of adults measured by DSM-5 assessment scales at the first clinical visit: a cohort study

BackgroundMeasurement-based care has been called for as best practice in psychiatric care and learning health systems and use of transdiagnostic measures was suggested as part of the DSM-5. Our objective is to examine gender differences in first visit socioeconomic, transdiagnostic, and functional characteristics of a dynamic, real-world measurement-based care cohort.MethodsTransdiagnostic, functional, and clinical measures were collected from 3,556 patients at first visit in an ambulatory psychiatric clinic. All patients were evaluated at the first visit by board-certified psychiatrists or licensed clinical psychologists. Demographic variables and clinical diagnoses were collected from the Electronic Medical Record. Self-report measures were collected that assessed transdiagnostic symptoms (DSM-5 Level 1 Cross-cutting Measure and Level 2 symptom scales), disability, alcohol use, attention deficit hyperactivity disorder (ADHD) symptoms, depression, anxiety, mania, suicidal thoughts and behaviors, and trauma exposure.ResultsMen and women did not differ in age, BMI, household income, high school graduation rate, race, or ethnicity, but women were more likely to be formerly married and less likely to have commercial insurance. Compared to men, women reported significantly higher overall psychopathology on the transdiagnostic Level 1 Cross-cutting measure and had higher depression, anxiety, sleep, anger, ADHD combined presentation, and suicidality severity. Women also had higher disability scores than men. However, men reported higher alcohol, tobacco and substance use, and more risky behavior than women. Trauma exposure differed significantly by gender; men reported more exposure to accidents, war-related trauma, serious accidents, and major disasters and women reported more unwanted sexual contact.ConclusionsThis cross-sectional study of a transdiagnostic, ecologically-valid real-word measurement-based care cohort demonstrates gender differences in socioeconomic factors, trauma exposure, transdiagnostic symptoms, and functioning.

Using a Quality Improvement Approach to Implement Measurement-Based Care (MBC) in Outpatient General Psychiatry.

Measurement-based care (MBC) is the clinical practice of using patient-reported symptom measurement to inform treatment decisions. MBC has been shown to improve patient outcomes and quality of care in outpatient psychiatry. Despite these benefits, MBC is not routinely used in most psychiatric outpatient settings. This quality improvement (QI) project aimed to achieve 75% completion of symptom scales using an online MBC platform in a general psychiatry clinic in Toronto, Canada, by June 2022. The QI team used the Model for Improvement methodology. The main outcome measure was completion of symptom scales using an online MBC platform. Process measures included counts of invitations to join the MBC platform, counts of online MBC account creation, and counts of symptom scale assignment by clinicians. Balancing measures included administrative task completion and physician workload assessment. Stakeholder interviews explored barriers and facilitators to MBC utilization. Completion of symptom scales increased from 7/65 (10.8%) preintervention to 40/70 (57.1%) during the 26-week intervention. Clinician reminders and coaching clinicians about how to incorporate MBC into the care process facilitated uptake of MBC. Stakeholders identified several barriers to implementation, particularly physician attitudes toward MBC and perceived administrative burden. Completion of symptom scales increased over the course of this QI initiative. Successful implementation of MBC in general psychiatry outpatient settings requires the availability of a broad range of measurement scales given the diversity of mental health diagnoses. Implementation must also consider health equity, including access to technology and availability of symptom scales in multiple languages.

EMPOWERED trial: protocol for a randomised control trial of digitally supported, highly personalised and measurement-based care to improve functional outcomes in young people with mood disorders

ObjectivesMany adolescents and young adults with emerging mood disorders do not achieve substantial improvements in education, employment, or social function after receiving standard youth mental health care. We have developed...

5.4 Utilizing Measurement-Based Care in a Partial Hospitalization Program

5.4 Utilizing Measurement-Based Care in a Partial Hospitalization Program

3.69 Psychometric Properties of the Keep it Simple Functional Analysis (KISFA): A New Tool to Simplify Measurement-Based Care

3.69 Psychometric Properties of the Keep it Simple Functional Analysis (KISFA): A New Tool to Simplify Measurement-Based Care

B-264 Identification of Potential Biomarkers Related to Major Depressive Disorder Using a Meta-Analysis Approach

Abstract Background Major depressive disorder (MDD), also known as depression, has become the most prevalent mood disorder today. Currently, the diagnosis remains a major challenge given the disease heterogeneity and have been made by associating signs and symptoms with other diagnostic criteria. Several treatment options are available for MDD. However, less than 35% of patients achieve remission while 60% may show some degree of resistance to treatment even when receiving antidepressant treatment according to consensus guidelines and using measurement-based care. Between difficulties associated with the management of MDD, the lack of consensus on classification, diagnosis, and treatment stands out. Because of the incomplete understanding of MDD pathogenesis, it is urgent to develop studies that can help in the elucidation of the mechanisms related to the disease and the identification of biomarkers that allow its correct classification. Thus, this work aimed to perform a meta-analysis study to identify potential molecular biomarkers from different NGS databases. Methods Datasets from seven association studies stored in the IEU Open GWAS Project Database were selected. The meta-analysis was performed using the METAL tool (https://genome.sph.umich.edu/wiki/METAL_Documentation), which combines the relevance of the p-values, sample size, and the direction of the effect size. The criteria adopted for selecting the datasets were: (1) Specification of “depression”, “major depressive disorder” or “major depression” as the only phenotype; and (2) description of allele frequency data. The threshold for results significance was defined as P-value ≤5 × 10−8. After performing the analyses, only the SNPs whose direction of effect was the same in all original studies were evaluated, considering only the set of SNPs that were not significant in the original studies. Results After performing the meta-analysis, 348 new SNPs with P-value ≤5 × 10−8 were identified and, of those, 133 SNPs were mapped next to 17 genes. None of these genes was previously associated with depression. However, the GABBR1 gene, which encodes a type B GABA receptor subunit, has been associated with alcoholism, while the SORCS3 gene has been associated with attention deficit/hyperactivity disorder and Alzheimer’s disease. Conclusions The meta-analysis findings could help elucidate genes and polymorphisms involved in MDD pathogenesis. Due to MDD heterogeneity is nearly impossible to restrict and select a single disease biomarker. It is worth noting that only the identification of genetic polymorphisms involved in MDD development cannot be the only source of potential biomarkers for MDD. Indeed, it is necessary to extend the analysis to other components, such as regulatory regions, epigenetics, metabolites, etc. However, this work provide new insights into the identification of MDD potential biomarkers that can be better investigated in association to others factors related to the disease.

Translating the Transdiagnostic: Aligning Assessment Practices With Research Advances.

Researchers and clinicians working within the Diagnostic and Statistical Manual of Mental Disorders: Fifth Edition, Text Rev (DSM-5-TR) framework face a difficult question: what does it mean to have an evidence-based assessment of a nonevidence-based diagnostic construct? Alternative nosological approaches conceptualize psychopathology as (a) hierarchical, allowing researchers to move between levels of description and (b) dimensional, eliminating artificial dichotomies between disorders and the dichotomy between mental illness and mental well-being. In this article, we provide an overview of ongoing efforts to develop validated measures of transdiagnostic nosologies (i.e., the Hierarchical Taxonomy of Psychopathology; HiTOP) with applications for measurement-based care. However, descriptive models like HiTOP, which summarize patterns of covariation among psychopathology symptoms, do not address dynamic processes underlying the problems associated with psychopathology. Ambulatory assessment, well-suited to examine such dynamic processes, has also developed rapidly in recent decades. Thus, the goal of the current article is twofold. First, we provide a brief overview of developments in constructing valid measures of the HiTOP model as well as developments in ambulatory assessment practices. Second, we outline how these parallel developments can be integrated to advance measurement-based treatment. We end with a discussion of some major challenges for future research to address to integrate advances more fully in transdiagnostic and ambulatory assessment practices.

"You mean it's more than just an eating disorder?": Commentary on Wade et al. (2023).

Drawing from literature on measurement-based care and prognostic indices in eating disorder (ED) treatment, Wade et al. offer an algorithm for treating co-occurring mental-health conditions (i.e., psychiatric comorbidity) in people with EDs, and for studying effects of comorbidity-oriented treatments. Advocating session-by-session measurement to inform adaptive treatment, their proposal outlines a process for adjusting conventional ED treatment to situations in which comorbidity impedes treatment progress. The plan is methodical and responsive to evidence suggesting that peoples' early in-treatment change has more power, prognostically, than do indices of comorbidity. In the absence of data to inform practices in some areas, the authors intentionally leave key questions unanswered until future results are in. But this means that they reserve comment on how to determine that comorbidity is interfering with treatment response, or to select the best-fitting of available comorbidity-oriented options. Likewise, the proposal draws most of its inspiration from literature on individual (mainly cognitive-behavioral) psychotherapy and, as a result, does not fully represent biopsychosocial perspectives, or elaborate upon the place in comorbidity management of biological treatments, family, and carer involvement, or more complex integrated approaches. Considerations on how to apply the latter methods would broaden the plan's scope.

Understanding the Barriers to and Facilitators of Anxiety Management in Residents of Long-Term Care.

Older adults, 65 years of age and older, living in long-term care (LTC) commonly experience anxiety. This study aimed to understand care providers' perspectives on the barriers to and facilitators of managing anxiety in residents of LTC. Ten semi-structured interviews with care providers in LTC were completed. Framework analysis methods were used to code, thematically analyze, designate codes as barriers or facilitators, and map the codes to the Theoretical Domains Framework. Themes were categorized as acting at the resident, provider, or system level, and were labelled as either barriers to or facilitators of anxiety care. Key barriers to anxiety care at each level were resident cognitive impairment or co-morbidities; lack of staff education, staff treatment uptake and implementation; as well as the care delivery environment and access to resources. There is a need to prioritize measurement-based care for anxiety, have increased access to non-pharmacological treatments, and have a care delivery environment that supports anxiety management to improve the care for anxiety that is delivered to residents.

Measurement-Based Care for Depression: Personalized Management Approaches for Optimized Treatment Outcomes

Use of measurement-based care (MBC) in depression includes the systematic administration of validated clinical measurement tools to guide the screening, assessment, treatment, and monitoring of clinical outcomes in patients with depression. In clinical practice, MBC can be used to screen for and assess severity of depressive symptoms, and guide treatment selection and change in type of treatment when clinical improvement is insufficient. In addition to identifying depressive symptoms, MBC can also help detect co-existing psychiatric conditions to inform more precise treatment selection. Furthermore, the MBC approach entails regular assessments of symptom severity, adherence, and side effects, which facilitates timely and vigorous dose adjustments of antidepressants to improve clinical outcomes. MBC can also be used to monitor specific symptoms that are associated with poor depression outcomes to allow acute-phase prognostication of treatment outcomes. The authors conclude that the MBC approach has many evidence-based benefits compared to the usual care and should be incorporated into the clinical care of patients with depression. [ Psychiatr Ann. 2023;53(9):395–399.]

Measurement-Based Care Implementation Challenges and Opportunities in Real-World Practice

Measurement-based care is an evidence-based practice shown to improve patient outcomes in a variety of psychiatric disorders compared to usual care. Despite the evidence, measurement-based care is not routinely implemented in real-world clinical practice. This report uses an implementation science framework to review the literature regarding perceived barriers and facilitators to real-world measurement-based care implementation at the patient, clinician, organizational, and systems level. Further, we highlight the importance of treatment guideline implementation in parallel with measurement-based care, which helps ensure clinician action responsive to symptom measurement. [ Psychiatr Ann . 2023;53(9):405–409.]

To Measure or Not to Measure: Perspectives of Measurement-Based Care From the Trenches

Measurement-based care has improved patient health outcomes by adding precision to clinical decision making at the patient level, when implemented correctly, across health care systems. Payors and system administrators also use measurements to assess program performance and inform resource allocation. This article describes frustrations and unintended consequences experienced by patients, psychiatric providers, administrators, and health systems when exuberant measurement, often without clearly stated goals, is promulgated with insufficient consideration as to the purpose, selection, and timing of these measurements by administrators and health systems. We propose some principles to inform when, how, by whom, and what to measure in managing the care of psychiatric patients. [ Psychiatr Ann . 2023;53(9):410–414.]

Using audit and feedback to guide tailored implementations of measurement-based care in community mental health: a multiple case study

BackgroundAudit and feedback (A&F) is an implementation strategy that can facilitate implementation tailoring by identifying gaps between desired and actual clinical care. While there are several theory-based propositions on which A&F components lead to better implementation outcomes, many have not been empirically investigated, and there is limited guidance for stakeholders when applying A&F in practice. The current study aims to illustrate A&F procedures in six community mental health clinics, with an emphasis on reporting A&F components that are relevant to theories of how feedback elicits behavior change.MethodsSix clinics from a larger trial using a tailored approach to implement measurement-based care (MBC) were analyzed for feedback content, delivery mechanisms, barriers to feedback, and outcomes of feedback using archival data. Pattern analysis was conducted to examine relations between A&F components and changes in MBC use.ResultsSeveral sites utilized both aggregate and individualized data summaries, and data accuracy concerns were common. Feedback cycles featuring individual-level clinician data, data relevant to MBC barriers, and information requested by data recipients were related to patterns of increased MBC use.ConclusionsThese findings support extant theory, such as Feedback Intervention Theory. Mental health professionals wishing to apply A&F should consider establishing reciprocal feedback mechanisms on the quality and amount of data being received and adopting specific roles communicating and addressing data quality concerns.Trial registrationClinicalTrials.gov Identifier: NCT02266134.

Towards shortening the Brief Addiction Monitor-Revised (BAM-R)

IntroductionThe Brief Addiction Monitor-Revised (BAM-R) is a widely used, 17-item assessment of substance use, risk, and protective factors associated with recovery from substance use disorders. Despite wide adoption in the U.S. Department of Veterans Affairs (VA) and recommendations for use in measurement-based care (MBC), administration may not be feasible in many MBC settings due to time constraints. The purpose of this study was to derive a shortened version of the BAM-R for use in fast-paced healthcare settings. MethodsBAM-R data from 32,002 Veterans were obtained through the VA's Corporate Data Warehouse. We used logistic regression models to identify items for removal based on prediction of two clinical outcomes (90-day substance use disorder (SUD) treatment retention and 12-month mortality) and item-level sensitivity to change during substance use treatment. ResultsAlthough no intake BAM-R items predicted SUD treatment retention or mortality, effect sizes for item-level sensitivity to change during substance use treatment varied from small to large. Seven items were judged as relevant for MBC of SUD. Among all BAM-R items, Heavy Alcohol Use, Self-Help, Drug Use, Craving, and Mood items demonstrated the greatest magnitude of sensitivity to change. ConclusionsAlthough additional research is recommended before a shortened BAM-R can be implemented in non-specialty MBC settings, we identified 5 BAM-R items with perceived clinical utility and scores that demonstrated evidence of sensitivity to change. Shortening the BAM-R increases feasibility of use, though more work is needed to optimize measurement for SUD MBC.

Session Reactions Scale-3: Initial psychometric evidence

ABSTRACT Objective: This study aimed to develop an updated brief self-report post-session measure, suitable for collecting systematic feedback on clients’ session reactions in the context of measurement-based care (MBC). Method: The Session Reactions Scale-3 (SRS-3; 33 items) was developed by extending and adjusting the Revised Session Reactions Scale. In Study 1, the psychometric properties of the SRS-3 were tested on N = 242 clients. In Study 2, a brief version of the SRS-3 (SRS-3-B; 15 items) was developed using a combination of conceptual, empirical, and pragmatic criteria. In Study 3, the psychometric properties of the SRS-3-B were tested on a new sample of N = 265 clients. Results: Exploratory factor analysis supported the use of the SRS-3-B as a two-factor (helpful reactions, hindering reactions) or unidimensional (overall session evaluation) instrument. The SRS-3-B was meaningfully related to another process measure (Individual Therapy Process Questionnaire) both on the item and factor levels. Conclusions: The SRS-3-B is a reliable process measure to elicit rich and clinically meaningful feedback from clients within the MBC context and as a research instrument to assess the helpful and hindering aspects of therapy sessions.

User-Centered Design of a Digitally Enabled Care Pathway in a Large Health System: Qualitative Interview Study.

Major depressive disorder (MDD) is a leading cause of disability worldwide. Management of chronic conditions such as MDD can be improved by enhanced patient engagement, measurement-based care (MBC), and shared decision-making (SDM). A user-centered design approach can improve the understanding of the patient journey and care team workflows and thus aid the development of digital health care innovations optimized for the needs of patients living with MDD and their primary care teams. This study aims to use qualitative research methods for the user-centered design of a digitally enabled MDD care platform, PathwayPlatform, intended to enhance patient engagement, MBC, and SDM. Insights were gathered through 2 stages of qualitative interviews by a study team with expertise in qualitative research and user-centered design methods. Thematic analysis was used to generate an overarching understanding of a set of shared experiences, thoughts, or behaviors across a broad qualitative data set, including transcripts of interviews, to allow both inductive and deductive insights to emerge. Thematic analysis of interviews was supported by Dedoose (SocioCultural Research Consultants, LLC), a qualitative data analysis software tool that enables systematized coding. Findings and insights were presented based on code frequency, salience, and relevance to the research project. In stage 1, interviews were conducted with 20 patients living with MDD and 15 health care providers from September 2018 to January 2019 to understand the experiences with and perceptions about the initial functionality of the Pathway app while also exploring the perceptions about potential additional features and functionality. Feedback about care team workflows and treatment approaches was collected in stage-2 interviews with 36 health care providers at 8 primary care sites. Inductive and deductive thematic analyses revealed several themes related to app functionality, patient-provider engagement, workflow integration, and patient education. Both patients and their care teams perceived the remote tracking of patient-reported outcomes via digital tools to be clinically useful and reliable and to promote MBC and SDM. However, there was emphasis on the need to enhance the flow of real-time data shared with the care team, improve trend visualizations, and integrate the data within the existing clinical workflow and educational programs for patients and their care teams. User feedback was incorporated into the iterative development of the Pathway app. Ongoing communication with patients living with MDD and their care teams provided an opportunity for user-centric developmental iterations of the Pathway Platform. Key insights led to further development of the patient-facing and care team-facing visit preparation features, collaborative goal-setting and goal-tracking features, patient-reported outcome summaries, and trend visualizations. The result is an enhanced digital platform with the potential to improve treatment outcomes and provide patients living with MDD additional support throughout their treatment journey.

Patient-facing, Semi-automated, solutions to enhance patient participation in measurement-based care practice standards in a tele-mental health specialty clinic for populations at higher risk for self-harm

PurposeCollecting validated surveys that describe symptom severity (measurement based care) during evidence-based psychotherapy is crucial to allow a therapist to tailor the speed and intensity of treatment. COVID clinic closures mandated we create a flexible, remote system to conduct measurement-based care, which was accomplished via RedCap. MethodsRedCap was used to create a semi-automated workflow allowing all clinically-indicated evidence-based surveys (including the PHQ-9) to be delivered via email to patients; with results automatically sent to their provider. Importantly, indications of suicidal ideation were automatically escalated to the provider. ResultsPHQ-9 completion improved, while provider burden for collecting surveys was greatly reduced; however, depending largely upon initial provider-patient ‘training’, overall compliance could still be significantly improved. ConclusionThis workflow gave providers additional information compared to the typical telemedicine environment, and in fact, improved data collection rates over our in-person environment. However, when patients did not complete measures on their own, the burden on providers increased.

Inspire self report scale (ISRS): A feasibility study of a Novel self report scale for people with schizophrenia spectrum disorders

Clinician-rated symptom scales are the current standard for outcome measures in Schizophrenia Spectrum Disorders (SSD) research. There has been growing interest in the development of self-report measures for people with SSD to support measurement-based care and inclusive research. We developed the Inspire Self Report Scale (ISRS), which measures the current magnitude of well-being, mood symptoms, psychosis, negative symptoms and cognition using 10 questions on a Likert or Visual analogue scale (VAS). The main aim of this report was to investigate the correlation and concordance between patient self-report and clinician ratings on the ISRS during a clinical encounter. When ratings were discordant, we sought to identify whether the participant's or psychiatrist's rating was more accurate. The results indicated a moderately strong statistically significant correlation between participant and clinician ratings. There was a moderate concordance between participant and clinician ratings on the ISRS. When the results were discordant, the participant ratings were assessed to be more accurate than the clinician rating over 70% of the time. The ISRS has distinct utility compared to existing scales due to the measurement of present symptom severity, capturing multiple clinical domains, and time efficiency and ease of use. Thus, it may be useful in clinical and research settings.