Search

Introduction: Behavioral measurement‐based care (MBC) can improve patient outcomes and has also been advanced as a critical learning health system (LHS) tool for identifying and mitigating potential disparities in mental health treatment. However, little is known about the uptake of remote behavioral MBC in safety net settings, or possible disparities occurring in remote MBC implementation. Methods: This study uses electronic health record data to study variation in completion rates at the clinic and patient level of a remote MBC symptom measure tool during the first 6 months of implementation at three adult outpatient psychiatry clinics in a safety net health system. Provider‐reported barriers to MBC adoption were also measured using repeated surveys at one of the three sites. Results: Out of 1219 patients who were sent an MBC measure request, uptake of completing at least one measure varied by clinic: General Adult Clinic, 38% (n = 262 of 696); Substance Use Clinic, 28% (n = 73 of 265); and Transitions Clinic, 17% (n = 44 of 258). Compared with White patients, Black and Portuguese or Brazilian patients had lower uptake. Older patients also had lower uptake. Spanish language of care was associated with much lower uptake at the patient level. Significant patient‐level disparities in uptake persisted after adjusting for the clinic, mental health diagnoses, and number of measure requests sent. Providers cited time within visits and bandwidth in their workflow as the greatest consistent barriers to discussing MBC results with patients. Conclusions: There are significant disparities in MBC uptake at the patient and clinic level. From an LHS data infrastructure perspective, safety net health systems may need to address the need for possible ways to adapt MBC to better fit their populations and clinical needs, or identify targeted implementation strategies to close data gaps for the identified disparity populations. [ABSTRACT FROM AUTHOR]

A meta-analysis was conducted to evaluate the effectiveness of client-clinician matching on the basis of race-ethnicity on overall functioning, service retention, and total number of sessions attended for African American and Caucasian American adult populations in mental health services. The analysis included 10 published and unpublished studies between 1991 and 2001. A random effects meta-analysis model showed no significant differences between client-clinician dyads matched racially-ethnically and those dyads not matched with respect to overall functioning, service retention, and total number of sessions attended. The finding was consistent for both African American and Caucasian American clients. Further implications of the findings are discussed. The authors also encourage more complete reporting of data suitable for quantitative research synthesis.

A meta-analytic approach to growth curve analysis is described and illustrated by applying it to the evaluation of the Arizona Pilot Project, an experimental project for financing the treatment of the severely mentally ill. In this approach to longitudinal data analysis, each individual subject for which repeated measures are obtained is initially treated as a separate case study for analysis. This approach has at least two distinct advantages. First, it does not assume a balanced design (equal numbers of repeated observations) across all subjects; to accommodate a variable number of observations for each subject, individual growth curve parameters are differentially weighted by the number of repeated measures on which they are based. Second, it does not assume homogeneity of treatment effects (equal slopes) across all subjects. Individual differences in growth curve parameters representing potentially unequal developmental rates through time are explicitly modeled. A meta-analytic approach to growth curve analysis may be the optimal analytical strategy for longitudinal studies where either (1) a balanced design is not feasible or (2) an assumption of homogeneity of treatment effects across all individuals is theoretically indefensible. In our evaluation of the Arizona Pilot Project, individual growth curve parameters were obtained for each of the 13 rationally derived subscales of the New York Functional Assessment Survey, over time, by linear regression analysis. The slopes, intercepts, and residuals obtained for each individual were then subjected to meta-analytic causal modeling. Using factor analytic models and then general linear models for the latent constructs, the growth curve parameters of all individuals were systematically related to each other via common factors and predicted based on hypothesized exogenous causal factors. The same two highly correlated common factors were found for all three growth curve parameters analyzed, a general psychological factor and a general functional factor. The factor patterns were found to be nearly identical across the separate analyses of individual intercepts, slopes, and residuals. Direct effects on the unique factors of each subscale of the New York Functional Assessment Survey were tested for each growth curve parameter by including the common factors as hierarchically prior predictors in the structural model for each of the indicator variables, thus statistically controlling for any indirect effect produced on the indicator through the common factors. The exogenous predictors modeled were theoretically specified orthogonal contrasts for Method of Payment (comparing Arizona Pilot Project treatment or 'capitation' to traditional or 'fee-for-service' care as a controI), Treatment Administration Site (comparing various locations within treatment or control groups), Pretreatment Assessment (comparing general functional level at intake as assigned by an Outside Assessment Team), and various interactions among these main effects. The intercepts, representing the initial status of individual subjects on both the two common factors and the 13 unique factors of the subscales of the New York Functional Assessment Survey, were found to vary significantly across many of the various different treatment conditions, treatment administration sites, and pretreatment functional levels. This indicated a severe threat to the validity of the originally intended design of the Arizona Pilot Project as a randomized experiment. When the systematic variations were statistically controlled by including intercepts as hierarchically prior predictors in the structural models for slopes, recasting the experiment as a nonequivalent groups design, the effects of the intercepts on the slopes were found to be both statistically significant and substantial in magnitude. Furthermore, the contrasts for Pretreatment Assessment scores also predicted statistically significant proportions of variance in both the two common factors and the 13 unique factors of the subscales of the New York Functional Assessment Survey for all three growth curve parameters, confirming an influence of the initial status of individual subjects on treatment effect. This empirical example illustrates both the mechanics and the many practical benefits of a meta-analytic approach to growth curve analysis in program evaluation.

Objective: This study reviews patient encounters at a Boston-area community hospital Psychiatric Emergency Services (PES) following the Boston Marathon bombings, with the goal of describing the impact of terrorist attacks on PES encounters. Methods: All PES encounters for 2 months preceding and 2 months following the bombing were identified in the electronic medical record. Demographics, current and past psychiatric problems, and trauma history were assessed for all records. Encounters seen post-bombing were compared with those before the bombing. Results: Demographics, current and past psychiatric problems, and trauma history were not significantly different before versus after the bombing; 36 of 440 (8.2%) post-bombing encounters directly mentioned the bombings. New-onset posttraumatic stress disorder (PTSD) symptoms caused by the bombing occurred in only 4 encounters (0.9%). Conclusions: PES encounters after a terrorist event are likely to mirror those seen before a terrorist event, with only a minority of encounters presenting for new PTSD or acute stress disorder. [ABSTRACT FROM AUTHOR]

The evidence-based practice movement rests on the premise that the scientific evidence regarding treatment should be used judiciously to inform treatment decisions. This article focuses on the most fundamental question regarding evidence-based practice: What is evidence? To address this question, the authors first review several of the definitions, criteria, and strategies that have been used to define scientific evidence. Second, a number of critical issues that have been raised regarding the nature of treatment evidence are discussed. Finally, suggestions for further consideration in the process of synthesizing evidence for clinicians are offered.