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Item Co-occurring Substance Use and Mental Health Needs: Enhancing the Adult Needs and Strengths Assessment (ANSA) to Manage Services(2019-10-04) Walton, Betty A.; Kim, Hea-WonSubstance use disorders (SUD) are common, affecting one in 25 adolescents (ages 12 -17), one in seven young adults (ages 18 to 25), and one in 16 adults (ages 26 and older) during 2017. 1 While 16.7% of adults without SUD experienced mental health (MH) disorders, 45.6% of adults with SUD experienced co-occurring MH disorders.1 Related research found much higher rates of adults with MH or SUD disorders (50-75%) have co-occurring disorders. 2, 3, 4, 5 Co-occurring MH and SUD make treatment more difficult, increase use of health resources, and interfere with individuals’ life functioning.2, 3, 4 In response to the opioid crisis, SUD treatment funding and services are expanding. Effective treatment requires identification of co-occurring disorders (COD). The goal of this study was to examine how well practitioners assess and identify COD in practice.Item Collaborate, Review Data and Change; Repeat(2022-09-27) Walton, Betty; Wendy, HarroldContext. The ANSA and TCOM framework, in conjunction with related information, can support data-informed policy planning and funding initiatives. One state’s collaborative data-informed recovery strategies provide an example. The concept of recovery from mental health and substance use disorders evolved from a deficit focus to include functional and personal recovery. Through a collaborative process SAMHSA, the federal behavior health authority, developed recovery’s working definition: “a process of change through which individuals improve their health and wellness, live a self- directed life, and strive to reach their full potential” in four dimensions (Health - overcoming or managing one’s diseases or symptoms, Home – a stable and safe place to live, Purpose - meaningful daily activities, and Community - relationships and social networks that provide support, friendship, love, and hope. Recently, SAMHSA acknowledged that the 2012 framework needs to evolve and issued a Recovery Challenge to community-based organizations to highlight innovative recovery strategies and practices. The challenge requires active, meaningful involvement of individuals with lived experience. Recovery and TCOM frameworks were cross walked to support training and to inform the state’s recovery support strategies. One strategy was to create a Recovery Support Workgroup (RSW) comprised of a dozen state agencies and community stakeholders. More than 51% of RSW members have lived experience with mental health and/or substance use. This group makes data-informed recommendations to state’s Mental Health and Addiction Planning and Advisory Council. Following a statewide 2019 gap analysis, which identified recovery support needs, the RSW created subgroups to address five recovery support needs: Personal support networks, Peer support services, Hobbies and interests, Prevention and wellness, and Safe and affordable housing. Data Collection Methodology. Multiple data sources informed the subgroups’ efforts: a consumer satisfaction survey, social determinants of health survey a Lived Experience Survey distributed through recovery groups, Medicaid claims diagnoses, recovery data collected at recovery organizations, and ANSA data. All data were associated with recovery dimensions: Health, Home, Community and Purpose. For ANSA data, the process required collaboration among the state’s data management, recovery support services, and the IU CANS/ANSA technical assistance teams. Enhancing ANSA Outcome Management Reports. Outcome Management reports, available to the state team, providers, and the IU CANS/ANSA team, were modified to inform the RSW subgroups by formatting reports by recovery dimensions and additional concerns. Building on existing reports (Resolved Actionable Needs, and item level metrics (Actionable, Continuing, Clinical Progress, Newly Identified, and Worsening), three new recovery focused reports were developed. Sharing and using the data. This collaborative, data-informed recovery initiative has received national attention. A variety of strategies to disseminate and to use the results for planning and managing change will be discussed: What has worked? What has been challenging? What has not work? What are the implications for quality improvement, program evaluation, and research?Item Young Adults' Recovery: Managing Change(2022-09-27) Betty, Walton; Steven, Holland; Saahoon, HongInformed by relevant literature and combined with demographic, assessment, educational, and service information, program evaluations can identify key factor to manage change. An example follows. Background. Transition-aged youth (TAY), ages 18 to 26, have higher rates of Substance Use Disorders (SUD) than adolescents or adults over 26 years old. In 2019, 17% experienced a major depressive disorder with 12.1% having severe impairments. Overall, 30.6% experienced mental illness, and 9.7% had serious mental illness. Although TAY reported lower levels of recovery than older adults, predictors of behavioral health recovery for TAY have seldom been explored. Indiana’s Division of Mental Health and Addiction (DMHA) has funded TAY services since 2019 as an effort to positively impact this population. Methods. Qualitative information from seven currently DMHA funded programs were to support and supplement data analysis. A FFY21 Midwestern sample (n=2575) of treated young adults (ages 18-26) included 688 People of Color (POC; 12% of the sample were Black only, 0.04% Native American only, 0.06% Asian only, 5% other race only, 3% Multiracial, and 6% Hispanic); 0.73% were White only. Half were female. All youth had substance and/or mental health disorders. The Adult Needs and Strengths Assessment (ANSA) identified needs that interfered with functioning and strengths. Transportation, employment, and residential needs were identified early in care. Other need and strength items reflected status when treatment ended. In a secondary analysis of state-level data, a hierarchical linear regression predicted recovery, the rate of improved Total Actionable Items (Resolved/Ever identified needs). Predictive variables were directly entered into four blocks: 1 (race/ethnicity, gender, employment, transportation, housing stability), 2 (depression, anxiety, substance use [SUD]), 3 (involvement in recovery, SUD recovery support, social functioning, optimism), and 4 (duration of treatment, Motivational Enhancement Therapy [MET). Race was converted to POC and gender to ‘female’. Results. Each step of the regression model documented significant contributions of added variables (R2s =.013, .239, .319, .350). POC were less likely to improve than white individuals. Women were more likely than men to improve. Individuals with employment, transportation, or housing needs at the beginning of treatment were more likely to improve. Depression, anxiety, and substance use disorders decreased the likelihood of resolved needs. Poor social functioning and inadequate SUD recovery support at the end of treatment were associated with worse outcomes. Having a positive sense of oneself in the future (optimism) predicted recovery. Active involvement in recovery, longer service duration, and Medication Enhancement Therapy were related to higher rates of recovery. Discussion. In addition to addressing SUD and mental health concerns, young adults’ recovery is related to developmental tasks (employment, recreation, and social relationships), supporting involvement in managing one’s health, and developing resiliency. Attention to social determinants of health, such as transportation, is necessary for access to services and supports. Service adaptations for POC to increase involvement in recovery and equitable outcomes requires consideration and study. Managing change for TAY involves attention to developmental, cultural, behavioral health needs, the concurrent utilization/development of strengths, and monitoring progress.