Technologic and Nontechnologic Barriers to Implementing Behavioral Health Homes in Community Mental Health Settings During the COVID-19 Pandemic.

Background: Persons with serious mental illnesses (SMIs) experience disparities in health care and are more likely to die from physical health conditions than the general population. Behavioral health homes are used in public sector mental health programs to deploy collaborative care to improve physical health for those with SMIs. During the COVID-19 pandemic, these programs faced new challenges in delivering care to this vulnerable group. Purpose: To describe barriers to implementing or sustaining behavioral health homes, experienced by community mental health workers during the COVID-19 pandemic, and the strategies used to address these challenges. Methods: In-depth qualitative interviews were conducted among the behavioral health workforce in Maryland and Michigan community mental health programs. Interview questions were derived from the Consolidated Framework for Implementation Research (CFIR), and responses related to implementing and sustaining health homes during the pandemic were coded and themes were analyzed by using an inductive approach. Results: Overall, 72 staff members across 21 sites in Maryland and Michigan were interviewed. Implementation barriers/strategies identified occurred across multiple CFIR domains (client, mental health system, physical health system). Interviewees discussed technologic and nontechnologic challenges as well as strategies to address technology issues. Strategies were more frequently discussed by providers when the barrier was viewed at the client level (eg, low technology literacy) versus the broader system (eg, canceled primary care visits). Conclusions: Community mental health staff described barriers beyond technology in caring for individuals with SMIs and physical health conditions. Further research should examine how implementation strategies address both technologic and nontechnologic barriers to collaborative care.

Risk of smoking and receipt of cessation services among veterans with mental disorders.

OBJECTIVE: The purpose of this study was to determine rates of smoking and receipt of provider recommendations to quit smoking among patients with mental disorders treated in U.S. Department of Veterans Affairs (VA) treatment settings. METHODS: The authors conducted a secondary analysis of the yearly, cross-sectional 2007 Veterans Health Administration Outpatient Survey of Healthcare Experiences of Patients (N=224,193). Logistic regression was used to determine the independent association of mental health diagnosis and the dependent variables of smoking and receipt of provider recommendations to quit smoking. RESULTS: Patients with mental disorders had greater odds of smoking, compared with those without mental disorders (p<.05). Those with various mental disorders reported similar rates of receiving services (more than 60% to 80% reported receiving selected services), compared with those without these disorders, except that those with schizophrenia had more than 30% lower odds of receiving advice to quit smoking from their physicians (p<.05). Moreover, those who had co-occurring posttraumatic stress disorder or substance use disorders had significantly greater odds of reporting that they received advice to quit, recommendations for medications, and physician discussions of quitting methods, compared with those without these disorders (p<.05). Older patients, male patients, members of ethnic minority groups, those who were unmarried, those who were disabled or unemployed, and those living in rural areas had lower odds of receiving selected services (p<.05). CONCLUSIONS: The majority of patients with mental disorders served by the VA reported receiving cessation services, yet their smoking rates remained high, and selected groups were at risk for receiving fewer cessation services, suggesting the continued need to disseminate cessation services.

Trial of an electronic decision support system to facilitate shared decision making in community mental health.

OBJECTIVES: Involvement of community mental health consumers in mental health decision making has been consistently associated with improvements in health outcomes. Electronic decision support systems (EDSSs) that support both consumer and provider decision making may be a sustainable way to improve dyadic communication in a field with approximately 50% workforce turnover per year. This study examined the feasibility of such a system and investigated proximal outcomes of the system's performance. METHODS: A cluster randomized design was used to evaluate an EDSS at three urban community mental health sites. Case managers (N=20) were randomly assigned to the EDSS-supported planning group or to the usual care planning group. Consumers (N=80) were assigned to the same group as their case managers. User satisfaction with the care planning process was assessed for consumers and case managers (possible scores range from 1 to 5, with higher summary scores indicating more satisfaction). Recall of the care plan was assessed for consumers. Linear regression with adjustment for grouping by worker was used to assess satisfaction scores. A Wilcoxon rank-sum test was used to examine knowledge of the care plan. RESULTS: Compared with case managers in the control group, those in the intervention group were significantly more satisfied with the care planning process (mean ± SD score=4.0 ± .5 versus 3.3 ± .5; adjusted p=.01). Compared with consumers in the control group, those in the intervention group had significantly greater recall of their care plans three days after the planning session (mean proportion of plan goals recalled=75% ± 28% versus 57% ± 32%; p=.02). There were no differences between the clients in the intervention and control groups regarding satisfaction. CONCLUSIONS: This study demonstrated that clients can build their own care plans and negotiate and revise them with their case managers using an EDSS.

Shared decision making in public mental health care: perspectives from consumers living with severe mental illness.

OBJECTIVE: Most theoretical and empirical work regarding decision making in mental health suggests that mental health consumers have better outcomes when their preferences are integrated into quality of life decisions. A wealth of research, however, indicates that providers have difficulty predicting what their clients' priorities are. This study investigates consumer decision-making preferences and understanding of construction of decisions in community mental health. METHODS: People living with severe mental illness being treated in the public mental health care system (N=16) participated in qualitative interviews regarding case management decision making as a part of a larger study investigating a decision support system to facilitate shared decision making. Interviews were transcribed, coded, and cross-case thematic analyses were conducted. RESULTS: Mental health consumers generally endorse a "shared" style of decision making. When asked what "shared" means, however, consumers describe a two-step process which first prioritizes autonomy, and if that is not possible, defers to case managers' judgment. Consumers also primarily focused on the relationship and affective components of decision making, rather than information-gathering or deliberating on options. Finally, when disagreements arose, consumers primarily indicated they handled them. CONCLUSIONS: Mental health consumers may have a different view of decision making than the literature on shared decision making suggests. Mental health consumers may consciously decide to at least verbally defer to their case managers, and remain silent about their preferences or wishes.

The role of staff turnover in the implementation of evidence-based practices in mental health care.

OBJECTIVES: This study examined turnover rates of teams implementing psychosocial evidence-based practices in public-sector mental health settings. It also explored the relationship between turnover and implementation outcomes in an effort to understand whether practitioner perspectives on turnover are related to implementation outcomes. METHODS: Team turnover was measured for 42 implementing teams participating in a national demonstration project examining implementation of five evidence-based practices between 2002 and 2005. Regression techniques were used to analyze the effects of team turnover on penetration and fidelity. Qualitative data collected throughout the project were blended with the quantitative data to examine the significance of team turnover to those attempting to implement the practices. RESULTS: High team turnover was common (M+/-SD=81%+/-46%) and did not vary by practice. The 24-month turnover rate was inversely related to fidelity scores at 24 months (N=40, beta=-.005, p=.01). A negative trend was observed for penetration. Further analysis indicated that 71% of teams noted that turnover was a relevant factor in implementation. CONCLUSIONS: The behavioral health workforce remains in flux. High turnover most often had a negative impact on implementation, although some teams were able to use strategies to improve implementation through turnover. Implementation models must consider turbulent behavioral health workforce conditions.

Using pharmacy data on partial adherence to inform clinical care of patients with serious mental illness.

OBJECTIVE: Low adherence to antipsychotic medications is a risk factor for poor outcomes for people with serious mental illness. Pharmacy data might be used by health systems to identify partially adherent patients for interventions. This study assessed whether using pharmacy data is an accurate screening method for identifying at-risk patients. METHODS: Administrative data were used to identify 1,712 veterans as having schizophrenia or a schizoaffective or bipolar disorder and who had 12-month antipsychotic medication possession ratios (MPRs) of less than .80. Patients' charts were reviewed for alternative explanations for low rates of filling prescriptions for antipsychotic medication. RESULTS: Of 1,712 patients whose pharmacy data indicated partial adherence (MPRs less than .80), 17% (N=297) may have been adherent. Patients with bipolar disorder had higher odds of receiving a false-positive designation (adjusted odds ratio of 1.8, 95% confidence interval of 1.31-2.39). CONCLUSIONS: MPRs constructed from pharmacy data can be a useful first screen for identifying patients who need assistance with medication adherence.