Goal 4: Advance Mental Health Services to Strengthen Public Health
Through mental health services research, investigators seek generalizable strategies for increasing access to and continuity with evidence-based interventions, fostering high quality equitable care, and improving clinical and recovery outcomes for millions of people with mental illnesses. To increase the public health impact of services studies, investigators test ways to develop or adapt, implement, scale-up, and sustain effective service delivery strategies and interventions for varied populations across multiple service and community settings in a cost-effective manner. This work requires new research designs, measures, and statistical approaches for evaluating system-wide interventions and measuring population-level effects. Increasingly, input from interested parties is sought to improve the reach and sustainability of evidence-based practices. New models of health care financing and delivery of care, along with evolving technologies such as electronic health records, health informatic systems, and multipurpose mobile computing devices, present unique opportunities for conducting deployment-focused services research in real-world settings. Such research may help to improve mental health care by determining the effectiveness of service strategies and optimizing the organization and sustained delivery of evidence-based preventive and treatment interventions; speeding the implementation of research-based innovations in community settings; and, ultimately ensuring optimal outcomes for individuals at risk for and affected by mental illnesses, particularly those from underserved communities and underrepresented minoritized groups.
The following Objectives further define this Goal:
Practice-based research, conducted within primary, specialty, and non-traditional health care and other community settings, is uniquely suited to address questions concerning clinical epidemiology; access to care, quality, effectiveness, and continuity of services; and, clinical, functional, and societal outcomes associated with mental health interventions. Weaving systematic data collection into routine care is an efficient means for capturing information about clinical populations, provider behavior, system-level performance, and outcomes for key subgroups. NIMH also supports the collection of data that measures social determinants of health, such as socioeconomic status, education access and quality, and neighborhood and built environment for reducing health disparities and improving health care outcomes. In addition, NIMH recognizes a need for more research on the impact of various financing strategies to ensure care for all, especially children and adolescents at risk for and with developmental precursors of mental illnesses and people with serious mental illness, neurodevelopmental conditions, and complex health needs.
To test approaches for improving the efficiency, effectiveness, and reach of mental health services, NIMH will support research that employs the following Strategies:
Interest areas include:
- Examining mental illness prevalence, service use, intervention response, and relapse events via data from large, diverse, and representative population samples or practice-based research networks, to identify new opportunities for individual-, provider-, organizational-, community-, or system-level interventions.
- Promoting data-driven approaches for improving screening and detection, as well as referral to care, for low base-rate events (e.g., suicidal behavior, first episode psychosis); monitoring real-time trends in incidence, prevalence, and severity; and, identifying novel service delivery targets for preventive interventions or treatment engagement.
Interest areas include:
- Developing pragmatic, valid, and reliable measures of engagement, intervention fidelity and quality, and outcomes that can be applied at the person, clinic, system, community, and/or population level to advance measurement-based care.
- Comparing performance feedback methods and quality improvement processes for adoption across a range of systems and age groups to advance the principles of learning health care.
- Applying computational modeling and data analytics to electronic health records, administrative claims data, and information from other sources to study mental health needs, social determinants, and services over time, and to identify mutable targets for improving service access, delivery, quality, and outcomes.
Interest areas include:
- Comparing alternative financing mechanisms that promote high quality, clinically effective, affordable, and efficient mental health care across settings and populations and discourage low-value services.
- Optimizing public and commercial financing mechanisms that cover integrated care packages for individuals with complex needs (e.g., combination psychopharmacology, psychotherapy, rehabilitative therapy, care coordination interventions).
- Studying the impact of national, state, provincial/county-level, or other health care system rules, regulations, and policies on participation in provider reimbursement and/or waiver programs.
- Understanding the role of financing and economic factors on developing and supporting a mental health workforce qualified to deliver evidence-based mental health services.
- Understanding the impact of economic factors affecting patients’ access to and ability to seek high-quality mental health services on mental health outcomes.
The delay between research findings and implementation in real-world settings is often lengthy, and delayed uptake of effective mental health interventions and services is widespread. NIMH recognizes the need for research to develop and test strategies that speed dissemination, adoption, and implementation of evidence-based interventions and sustain these practices over time. Strategies that reduce the lag between research discovery and science-driven practice could radically alter the quality and outcomes of care provided for all individuals with mental illnesses.
To accelerate deployment-focused intervention and services research, NIMH encourages strong partnerships among scientists, those who directly benefit from evidence-based approaches (e.g., service users, providers, caregivers), and other public and private interested parties. Effective partnerships with and among these individuals are crucial for identifying salient services research questions, developing realistic interventions and services, and testing adoptable, scalable, and sustainable approaches that promote continuous improvement of mental health care.
To speed adoption, implementation, and continuous improvement of evidence-based mental health services, NIMH will support studies that employ the following Strategies:
Interest areas include:
- Conducting dissemination and implementation studies that reflect active partnerships between scientists and key end users and other interested parties, such as service users, providers, and payers, across all phases of the research process.
- Investigating strategies that promote rapid incorporation of practice-based research findings into health and other system decision making, clinical practice guidelines, and reimbursement and other policies for mental health services.
- Addressing workforce issues related to implementation and sustainment of evidence-based approaches in health care and other settings (e.g., training providers in new treatment models and technologies; maintaining provider competence; involving paraprofessionals and peer providers; retaining qualified providers; managing staff turnover without compromising the quality of services; and, studying policies that impede or facilitate high quality care).
Interest areas include:
- Examining and monitoring client, caregiver, provider, organizational-level, and community factors, including social determinants of health, that affect the usability and transportability of interventions and services (i.e., the degree to which the evidence-informed intervention can be implemented with fidelity).
- Adapting interventions and services with demonstrated effectiveness in one setting to determine fit for use in other contexts such as low-resource settings or non-specialty community/practice settings where mental health care is or could be delivered (e.g., primary care, schools, child and adult welfare, criminal and juvenile justice settings, long-term care facilities, geriatric service programs).
- Employing hybrid effectiveness-implementation designs to enhance the delivery of evidence-based mental health practices and improve implementation outcomes (e.g., fidelity, acceptability, feasibility, appropriateness, penetration, and sustainability of services within a single study).
Interest areas include:
- Developing and validating novel tools, smart technologies, real-time analytics, and ecologically valid measures to monitor the engagement of intervention targets in services interventions.
- Examining and adapting the attributes of evidence-based interventions (e.g., intensity, duration, frequency) and implementation (e.g., fidelity, feasibility, acceptability) that affect their generalizability to practice settings.
- Developing and testing decision-support algorithms for matching services within a health system (e.g., pharmacotherapy, psychotherapy, rehabilitation, care coordination, transition planning) to clients’ needs over time, including stepped-care algorithms that span non-specialty and mental health specialty services.
- Developing and testing strategies (e.g., shared decision making or behavioral economic approaches to behavior change) to enhance prevention and treatment engagement and adherence.
Service delivery models provide a framework for mental health care, which account for various settings, providers, and resources. Available data indicate that many current service delivery models are inadequate to meet the mental health service needs in the United States and around the globe. To provide high quality care to groups who are underrepresented in mental health research and have inequitable access to mental health care, researchers may need to adapt evidence-based models to account for moderators, including social determinants of health, which are known to impact intervention effectiveness. Services research and implementation science strategies that test adaptations should be designed to determine whether the adapted strategy counteracts moderators that have been shown to impede effectiveness and clinical outcomes.
NIMH is committed to supporting research that reduces disparities and advances equity in mental health services and outcomes. As such, we need innovative and sustainable service delivery models that address disparities that stem from historical, social, and economic inequities that disproportionately affect minoritized and marginalized populations and people with serious mental illness, to include people experiencing instability in housing, employment, income, and food. People with serious mental illness are among the first and most disproportionately affected by these social and economic insecurities. We must develop and test novel components of care across multiple settings where mental health services are needed and use developmentally and culturally appropriate tools to better reach populations in need and substantially improve the delivery of evidence-based mental health care.
To improve the outcomes of individuals receiving mental health services and to ensure equity of outcomes in all populations, NIMH will support research to develop innovative services delivery models that employs the following Strategies:
Interest areas include:
- Testing innovative approaches for reducing empirically documented disparities in care access, quality, and outcomes for racial and ethnic minority groups; individuals limited by English language proficiency, educational, or cultural barriers; sexual and gender minorities; individuals living with disabilities; individuals living in rural areas; socioeconomically disadvantaged persons; and, other underserved groups.
- Combining data from multiple sources of information (e.g., electronic health records, administrative claims data, epidemiologic surveys, census data, qualitative methods) to identify underserved groups and to explore novel approaches for coordinating health/community service resources and improving overall health outcomes.
- Conducting research to better understand, predict, and reduce mental health workforce shortages across pediatric, adolescent, adult, and geriatric services; reduce the shortage of culturally and linguistically competent care providers for racial and ethnic minorities; reduce the workforce shortages in certain geographic areas (e.g., rural and underserved communities); and, promote care that is respectful and affirming of an individual’s sexual orientation, gender identity, and disability status.
Interest areas include:
- Developing and testing innovative strategies to promote early identification and engagement in prevention and mental health or supportive services for children, adolescents, and adults, especially for those experiencing early symptoms of mental illness.
- Characterizing care pathways to identify mutable barriers, facilitators, and social and structural determinants to improving access to care across the lifespan, including children at risk for autism or mental illnesses, transition-age youth with autism or emerging mental illnesses, and adults with autism or mental illnesses.
- Addressing workforce shortages, instilling hope and re-moralization, improving engagement with care and reach of interventions using paraprofessionals, peer providers, and nontraditional staff.
Interest areas include:
- Using technology to improve prevention and early detection of mental illnesses, connect clients across all ages to evidence-based care, increase reach of and engagement with services for underserved populations, and improve client-level outcomes.
- Developing and testing clinician-facing “dashboards” or other system-level technologies that can be used to support providers in their use of measurement-based care, to facilitate and optimize system-level quality monitoring and improvement, and to improve clinical workflows.
- Developing and testing implementation strategies for evidence-based practices (e.g., ensuring availability, accessibility, effectiveness, scalability, sustainability) in low-resource settings or non-specialty settings where significant unmet need exists (e.g., the criminal and juvenile justice systems, employment settings, military or veteran organizations, schools, and the child welfare system).
- Building novel service delivery models that capitalize on systems that are already engaging individuals with mental health needs (e.g., schools, social services, or other community-based settings, online/virtual communities).
Interest areas include:
- Developing and testing service delivery models for people with comorbid conditions (e.g., medical comorbidities, co-occurring substance use disorder), such as care decision models that integrate treatment for mental illnesses and medical conditions, and service delivery interventions to reduce modifiable health risks associated with premature mortality in people with serious mental illness. These innovative service delivery models should be feasible in a wide range of settings, including low-resource settings, and acceptable to a wide variety of health disparity populations, since racial and ethnic minorities and other health disparity populations have greater prevalence of comorbidities.27
- Developing and validating decision-support tools to assess mental health and functional needs, medical risk factors, and mental health/medical treatment availability in non-specialty settings where children and adolescents are served, and to facilitate treatment planning.
- Using existing and developing novel technologies (e.g., mobile devices, information systems, artificial intelligence) to significantly improve access, engagement, quality, effectiveness, and efficiency of integrated mental health services, while making sure that these advances benefit people with a wide range of backgrounds, socioeconomic status, ethnicity, race, disability, and geographical area of residence.
- Investigating strategies for active symptom management that reduce the symptom burden in individuals with serious mental illness and multiple chronic conditions.
Progress for Goal 4
Bringing knowledge to practice, improvements to services, and better outcomes to individuals.
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