Identifying the Heterogeneity in the Association between Workforce Diversity and Retention in Opioid Treatment among Black clients.

Background: This study investigates the impact of workforce diversity, specifically staff identified as Black/African American, on retention in opioid use disorder (OUD) treatment, aiming to enhance patient outcomes. Employing a novel machine learning technique known as 'causal forest,' we explore heterogeneous treatment effects on retention. Methods: We relied on four waves of the National Drug Abuse Treatment System Survey (NDATSS), a nationally representative longitudinal dataset of treatment programs. We analyzed OUD program data from the years 2000, 2005, 2014 and 2017 (n = 627). Employing the 'causal forest' method, we analyzed the heterogeneity in the relationship between workforce diversity and retention in OUD treatment. Interviews with program directors and clinical supervisors provided the data for this study. Results: The results reveal diversity-related variations in the association with retention across 61 out of 627 OUD treatment programs (less than 10%). These programs, associated with positive impacts of workforce diversity, were more likely private-for-profit, newer, had lower percentages of Black and Latino clients, lower staff-to-client ratios, higher proportions of staff with graduate degrees, and lower percentages of unemployed clients. Conclusions: While workforce diversity is crucial, our findings underscore that it alone is insufficient for improving retention in addiction health services research. Programs with characteristics typically linked to positive outcomes are better positioned to maximize the benefits of a diverse workforce in client retention. This research has implications for policy and program design, guiding decisions on resource allocation and workforce diversity to enhance retention rates among Black clients with OUDs.

What can we learn from COVID-19 to improve opioid treatment? Expert providers respond.

BACKGROUND: The COVID-19 pandemic has had devasting effects on drug abuse treatment systems already stressed by the opioid crisis. Providers within opioid use disorder (OUD) outpatient treatment programs have had to adjust to rapid change and respond to new service delivery provisions such as telehealth and take-home medication. Using the COVID-19 pandemic and subsequent organizational challenges as a backdrop, this study explores providers' perspectives about strategies and policies that, if made permanent, can potentially improve access to and quality of OUD treatment. METHODS: This qualitative study was conducted in Los Angeles County, which has one of the largest substance use disorder (SUD) treatment systems in the United States serving a diverse population, including communities impacted by the opioid crisis. We collected qualitative interview data from 30 high-performing programs (one manager/supervisor per program) where we based high performance on empirical measures of access, retention, and program completion outcomes. The study team completed data collection and analysis using constructivist grounded theory (CGT) to describe the social processes in which the participating managers engaged when faced with the pandemic and subsequent organizational changes. We developed 14 major codes and six minor codes with definitions. The interrater reliability tests showed pooled Cohen's kappa statistic of 93 %. RESULTS: Our results document the impacts of COVID-19 on SUD treatment systems, their programmatic responses, and the strategic innovations they developed to improve service delivery and quality and which managers plan to sustain within their organizations. CONCLUSION: Providers identified three primary areas for strategic innovation designed to improve access and quality: (1) designing better medication utilization, (2) increasing telemedicine capacity, and (3) improving reimbursement policies. These strategies for system transformation enable us to use lessons from the COVID-19 pandemic to direct policy and programmatic reform, such as expanding eligibility for take-home medication and enhancing access to telehealth services.

Structural basis for the ubiquitination of G protein ßγ subunits by KCTD5/Cullin3 E3 ligase.

G protein-coupled receptor (GPCR) signaling is precisely controlled to avoid overstimulation that results in detrimental consequences. Gßγ signaling is negatively regulated by a Cullin3 (Cul3)-dependent E3 ligase, KCTD5, which triggers ubiquitination and degradation of free Gßγ. Here, we report the cryo-electron microscopy structures of the KCTD5-Gßγ fusion complex and the KCTD7-Cul3 complex. KCTD5 in pentameric form engages symmetrically with five copies of Gßγ through its C-terminal domain. The unique pentameric assembly of the KCTD5/Cul3 E3 ligase places the ubiquitin-conjugating enzyme (E2) and the modification sites of Gßγ in close proximity and allows simultaneous transfer of ubiquitin from E2 to five Gßγ subunits. Moreover, we show that ubiquitination of Gßγ by KCTD5 is important for fine-tuning cyclic adenosine 3´,5´-monophosphate signaling of GPCRs. Our studies provide unprecedented insights into mechanisms of substrate recognition by unusual pentameric E3 ligases and highlight the KCTD family as emerging regulators of GPCR signaling.

Exploring Gender and Ethnoracial Differences and Trends in Methamphetamine Treatment.

Introduction: Given the significant rise in methamphetamine use and related mortality in the United States, it is critical to explore differences in treatment trends with particular attention to women and ethnoracial groups in hard-hit areas like Los Angeles County. Methods: We analyzed a large sample across 4 waves: 2011 (105 programs, 10 895 clients), 2013 (104 programs, 17 865 clients), 2015 (96 programs, 16 584 clients), and 2017 (82 programs, 15 388 clients). We completed a comparative analysis to identify differences across subgroups and a trend analysis of treatment episodes by gender and ethnoracial group to differentiate users of methamphetamine and users of other drugs. Results: Treatment clients using methamphetamine increased over time for each gender and race. There were also significant differences across age groups. Women comprised a greater proportion of treatment episodes involving methamphetamine use (43.3%) compared to all other drugs combined (33.6%). Latinas represented 45.5% of methadone-related admissions. Compared with other drug users, methamphetamine users had a lower successful treatment completion rate and were served by programs with less financial and culturally responsive capacity. Conclusions: Findings highlight a sharp increase in treatment admissions for methamphetamine users of all gender and ethnocultural groups. Women, especially Latinas, saw the most significant increases, with a widening gender gap over time. All subgroups of methamphetamine users had a lower treatment completion rate compared with users of other drugs, and critical differences existed in the programs where they received services.

Predicting and responding to change: Perceived environmental uncertainty among substance use disorder treatment programs.

INTRODUCTION: Substance use disorder (SUD) treatment programs offering addiction health services (AHS) must be prepared to adapt to change in their operating environment. These environmental uncertainties may have implications for service delivery, and ultimately patient outcomes. To adapt to a multitude of environmental uncertainties, treatment programs must be prepared to predict and respond to change. Yet, research on treatment programs preparedness for change is sparse. We examined reported difficulties in predicting and responding to changes in the AHS system, and factors associated with these outcomes. METHODS: Cross-sectional surveys of SUD treatment programs in the United States in 2014 and 2017. We used linear and ordered logistic regression to examine associations between key independent variables (e.g., program, staff, and client characteristics) and four outcomes, (1) reported difficulties in predicting change, (2) predicting effect of change on organization, (3) responding to change, and (4) predicting changes to make to respond to environmental uncertainties. Data were collected through telephone surveys. RESULTS: The proportion of SUD treatment programs reporting difficulty predicting and responding to changes in the AHS system decreased from 2014 to 2017. However, a considerable proportion still reported difficulty in 2017. We identified that different organizational characteristics are associated with their reported ability to predict or respond to environmental uncertainty. Findings show that predicting change is significantly associated with program characteristics only, while predicting effect of change on organizations is associated with program and staff characteristics. Deciding how to respond to change is associated with program, staff, and client characteristics, while predicting changes to make to respond is associated with staff characteristics only. CONCLUSIONS: Although treatment programs reported decreased difficulty predicting and responding to changes, our findings identify program characteristics and attributes that could better position programs with the foresight to more effectively predict and respond to uncertainties. Given resource constraints at multiple levels in treatment programs, this knowledge might help identify and optimize aspects of programs to intervene upon to enhance their adaptability to change. These efforts may positively influences processes or care delivery, and ultimately translate into improvements in patient outcomes.

Understanding the role of financial capacity in the delivery of opioid use disorder treatment.

Opioid treatment programs must have adequate financial capacity to sustain operations and deliver a high standard of care for individuals suffering from opioid use disorder. However, there is limited consistency in the health services literature about the concept and relationship of organizational financial capacity and key outcome measures (wait time and retention). In this study, we explored five common measures of financial capacity that can be applied to opioid treatment programs: (a) reserve ratio, (b) equity ratio, (c) markup, (d) revenue growth, and (e) earned revenue. We used these measures to compare financial capacity among 135 opioid treatment programs across four data collection points: 2011 (66 programs), 2013 (77 programs), 2015 (75 programs), and 2017 (69 programs). We examined the relationship between financial capacity and wait time and retention. Findings from the literature review show inconsistencies in the definition and application of concepts associated with financial capacity across business and social service delivery fields. The analysis shows significant differences in components of financial capacity across years. We observed an increase in average earned revenue and markup in 2017 compared to prior years. The interaction between minorities and markup was significantly associated with higher likelihood of waiting (IRR = 1.077, p < .05). Earned revenue (IRR = 0.225, p < .05) was related to shorter wait time in treatment. The interaction between minorities and equity ratio is also significantly associated with retention (IRR = 0.796, p < .05). Our study offers a baseline view of the role of financial capacity in opioid treatment and suggests a framework to determine its effect on client-centered outcomes.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer's Disease.

Alzheimer's disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer's disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein-protein network characterized by inverse RNA/DNA methylation correlation and enriched for "Regulation of insulin-like growth factor transport", with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.

Identifying gender differences in risk profiles and in opioid treatment outcomes in Los Angeles County.

Policies and programs that aim to minimize wait time to enter opioid use disorder (OUD) treatment and maximize retention respond to potential differences in female and male clients' risk profiles. We conducted multigroup latent class analysis using significant individual risk factors. Our sample included 13,453 opioid treatment episodes from 135 unique substance use disorder treatment programs in Los Angeles County, California, in four waves: 2011 (66 programs, 1035 clients), 2013 (77 programs, 3671 clients), 2015 (75 programs, 4625 clients), and 2017 (69 programs, 4106 clients). Groups at risk of waiting longer included clients who were female, had mental health issues, received medication for OUD, had criminal justice involvement, received mandated referrals, had children in child protective services, and had caretaker responsibilities. All clients with children in protective services were likely to wait longer than those not in protective services, but women waited longer. Findings highlight that: (a) women and men in OUD treatment have significant health and social problems; (b) female and male clients have distinct risk profiles; and (c) targeted services responding to risk profiles may improve treatment access and engagement. Findings have implications for health policy and program evaluation and planning in the delivery of treatment services considering gendered risk factors.

Workforce Diversity and disparities in wait time and retention among opioid treatment programs.

BACKGROUND: Workforce diversity is a key strategy to improve treatment engagement among members of racial and ethnic minority groups. In this study, we seek to determine whether workforce diversity plays a role in reducing racial and ethnic differences in wait time to treatment entry and retention in different types of opioid use disorder treatment programs. METHODS: We conducted comparative and predictive analysis in a subsample of outpatient opioid treatment programs (OTPs), who completed access and retention survey questions in four waves of the National Drug Abuse Treatment System Survey (162 OTPs in 2000, 173 OTPs in 2005, 282 OTPs in 2014, and 300 OTPs in 2017). We sought to assess the associations between workforce diversity on wait time and retention, accounting for the role of Medicaid expansion and the moderating role of program ownership type (i.e., public, non-profit, for-profit) among OTPs located across the United States. RESULTS: We found significant differences in wait time to treatment entry and retention in treatment across waves. Average number of waiting days decreased in 2014 and 2017; post Medicaid expansion per the Affordable Care Act, while retention rates varied across years. Key findings show that programs with high diversity, measured by higher percent of African American staff and a higher percent of African American clients, were associated with longer wait times to enter treatment, compared to low diversity programs. Programs with higher percent of Latino staff and a higher percent of Latino clients were associated with lower retention in treatment compared with low diversity programs. However, program ownership type (public, non-profit and for-profit) played a moderating role. Public programs with higher percent of African American staff were associated with lower wait time, while non-profit programs with higher percent of Latino staff were related to higher retention. CONCLUSIONS: Findings show decreases in wait time over the years with significant variation in retention during the same period. Concordance in high workforce and client diversity was associated with higher wait time and lower retention. But these relations inverted (low wait time and high retention) in public and non-profit programs with high staff diversity. Findings have implications for building resources and service capacity among OTPs that serve a higher proportion of minority clients.

Disparities in opioid treatment access and retention among women based on pregnancy status from 2006 to 2017.

Background: The purpose of this study is to assess differences in wait time and retention in opioid use disorder (OUD) treatment among a sample of pregnant and non-pregnant women from low-income urban communities in Los Angeles, California. Methods: Data were collected in 9 waves consisting of consecutive years from 2006 to 2011, and then including 2013, 2015, and 2017. The sample consisted of 12,558 women, with 285 being pregnant and 12,273 being non-pregnant. We compared pregnant women with non-pregnant women at admission on key characteristics and relied on two multilevel negative binomial regressions analyses to examine factors related to access (days on the waiting list) and retention (days in treatment). Results: We detected disparities existed in access and retention. Pregnant women spent less time waiting to initate treatment than non-pregnant women and, once in treatment, had longer treatment episodes. Among pregnant women, clients identifying as Latina or Other waited longer to enter treatment compared to clients identifying as non-Latina White or Black. Women entering residential waited longer than those entering methadone or counseling services. Pregnant women were more likely to be in treatment longer if they had mental health issues, greater parenting responsibilities (number of children less than 18), and greater SUD severity (number of prior treatment episodes). Conclusions: Findings suggest pregnant women's access and retention can be improved through Medicaid coverage and through the implementation of a standard of care that includes MOUD (methadone) along with ancillary health and social services.

Disparities in expected driving time to opioid treatment and treatment completion: findings from an exploratory study.

BACKGROUND: Commuting time to treatment has been shown to affect healthcare outcomes such as engagement and initiation. The purpose of this study is to extend this line of research to investigate the effects of driving time to opioid programs on treatment outcomes. METHODS: We analyzed discharge survey data from 22,587 outpatient opioid use disorder treatment episodes (mainly methadone) in Los Angeles County and estimated the associated driving time to each episode using Google Maps. We used multivariable logistic regressions to examine the association between estimated driving time and odds of treatment completion after adjusting for possible confounders. RESULTS: Findings show an average driving time of 11.32 min and an average distance of 11.18 km. We observed differences in estimated driving time across age, gender, and socioeconomic status. Young, male, less formally educated, and Medi-Cal-ineligible clients drove longer to treatment. A 10-min drive was associated with a 33% reduction in the completion of methadone treatment plans (p < .01). CONCLUSION: This systemwide analysis provides novel time estimates of driving-based experiences and a strong relationship with completion rates in methadone treatment. Specifically, the result showing reduced treatment completion rates for drive times longer than 10 min may inform policies regarding the ideal geographic placement of methadone-based treatment programs and service expansion initiatives.

Using machine learning to advance disparities research: Subgroup analyses of access to opioid treatment.

OBJECTIVE: To operationalize an intersectionality framework using a novel statistical approach and with these efforts, improve the estimation of disparities in access (i.e., wait time to treatment entry) to opioid use disorder (OUD) treatment beyond race. DATA SOURCE: Sample of 941,286 treatment episodes collected in 2015-2017 in the United States from the Treatment Episodes Data Survey (TEDS-A) and a subset from California (n = 188,637) and Maryland (n = 184,276), states with the largest sample of episodes. STUDY DESIGN: This retrospective subgroup analysis used a two-step approach called virtual twins. In Step 1, we trained a classification model that gives the probability of waiting (1 day or more). In Step 2, we identified subgroups with a higher probability of differences due to race. We tested three classification models for Step 1 and identified the model with the best estimation. DATA COLLECTION: Client data were collected by states during personal interviews at admission and discharge. PRINCIPAL FINDINGS: Random forest was the most accurate model for the first step of subgroup analysis. We found large variation across states in racial disparities. Stratified analysis of two states with the largest samples showed critical factors that augmented disparities beyond race. In California, factors such as service setting, referral source, and homelessness defined the subgroup most vulnerable to racial disparities. In Maryland, service setting, prior episodes, receipt of medication-assisted opioid treatment, and primary drug use frequency augmented disparities beyond race. The identified subgroups had significantly larger racial disparities. CONCLUSIONS: The methodology used in this study enabled a nuanced understanding of the complexities in disparities research. We found state and service factors that intersected with race and augmented disparities in wait time. Findings can help decision makers target modifiable factors that make subgroups vulnerable to waiting longer to enter treatment.

DeepLINK: Deep learning inference using knockoffs with applications to genomics.

We propose a deep learning-based knockoffs inference framework, DeepLINK, that guarantees the false discovery rate (FDR) control in high-dimensional settings. DeepLINK is applicable to a broad class of covariate distributions described by the possibly nonlinear latent factor models. It consists of two major parts: an autoencoder network for the knockoff variable construction and a multilayer perceptron network for feature selection with the FDR control. The empirical performance of DeepLINK is investigated through extensive simulation studies, where it is shown to achieve FDR control in feature selection with both high selection power and high prediction accuracy. We also apply DeepLINK to three real data applications to demonstrate its practical utility.

Gender disparities in access and retention in outpatient methadone treatment for opioid use disorder in low-income urban communities.

The purpose of this study was to detect and understand gender disparities in access and retention among outpatient methadone treatment programs located in low-income urban communities in Los Angeles, California. The study collected client- and program-level data in 4 waves in 2011, 2013, 2015, and 2017 from 34 publicly funded methadone treatment programs serving 11,169 clients with opioid use disorder (OUD). The sample included 29.8% female and 70.2% male clients, where 10.6% identified as Black or African American, 41.5% as Latino, 44.2% as non-Latino white, and 3.8% as Other. We conducted two multilevel negative binomial regression models to examine direct and moderated relationships related to both access (days on the waitlist) and retention (days in treatment) while accounting for clients clustered within programs. Gender disparities existed in both access and retention where women spent more time than men waiting to enter treatment but then remained in treatment longer. Further, female clients identifying as African American, Latino, and Other were at greater risk for shorter treatment duration than those who identified as non-Latino white and men. Overall, OUD clients receiving methadone treatment in low-income neighborhoods experienced barriers to access and retention in treatment associated with mental illness, family responsibilities, and use severity. OUD clients with MediCal insurance eligibility were consistently more likely to gain access to and remain in methadone treatment. Overall, findings call for improving treatment access and retention for women with OUD who receive methadone in outpatient methadone treatment programs through comprehensive, gender-specific, and evidence-based programming.

Gender disparities in opioid treatment progress in methadone versus counseling.

BACKGROUND: In the United States, the high dropout rate (75%) in opioid use disorder (OUD) treatment among women and racial/ethnic minorities calls for understanding factors that contribute to making progress in treatment. Whereas counseling and medication for OUD (MOUD, e.g. methadone, buprenorphine, naltrexone) is considered the gold standard of care in substance use disorder (SUD) treatment, many individuals with OUD receive either counseling or methadone-only services. This study evaluates gender disparities in treatment plan progress in methadone- compared to counseling-based programs in one of the largest SUD treatment systems in the United States. METHODS: Multi-year and multi-level (treatment program and client-level) data were analyzed using the Integrated Substance Abuse Treatment to Eliminate Disparities (iSATed) dataset collected in Los Angeles County, California. The sample consisted of 4 waves: 2011 (66 SUD programs, 1035 clients), 2013 (77 SUD programs, 3686 clients), 2015 (75 SUD programs, 4626 clients), and 2017 (69 SUD programs, 4106 clients). We conducted two multi-level negative binomial regressions, one per each outcome (1) making progress towards completing treatment plan, and (2) completing treatment plan. We included outpatient clients discharged on each of the years of the study (over 95% of all clients) and accounted for demographics, wave, homelessness and prior treatment episodes, as well as clients clustered within programs. RESULTS: We detected gender differences in two treatment outcomes (progress and completion) considering two outpatient program service types (MOUD-methadone vs. counseling). Clients who received methadone vs. counseling had lower odds of completing their treatment plan (OR = 0.366; 95% CI = 0.163, 0.821). Female clients receiving methadone had lower odds of both making progress (OR = 0.668; 95% CI = 0.481, 0.929) and completing their treatment plan (OR = 0.666; 95% CI = 0.485, 0.916) compared to male clients and receiving counseling. Latina clients had lower odds of completing their treatment plan (OR = 0.617; 95% CI = 0.408, 0.934) compared with non-Latina clients. CONCLUSIONS: Clients receiving methadone, the most common and highly effective MOUD in reducing opioid use, were less likely to make progress towards or complete their treatment plan than those receiving counseling. Women, and in particular those identified as Latinas, were least likely to benefit from methadone-based programs. These findings have implications for health policy and program design that consider the need for comprehensive and culturally responsive services in methadone-based programs to improve outpatient treatment outcomes among women.

Advancing theory on the multilevel role of leadership in the implementation of evidence-based health care practices.

BACKGROUND: Top managers' transformational leadership is associated with significant influence on subordinates. Yet little is known about the extent to which top managers' transformational leadership influences middle managers' implementation leadership and, ultimately, frontline staff delivery of evidence-based health care practices. PURPOSE: To test a multilevel leadership model examining the extent to which top managers' transformational leadership, as mediated by implementation leadership of middle managers (i.e., those who supervise direct clinical services), affects staff attitudes toward evidence-based practices (EBPs) and their implementation. METHODOLOGY/APPROACH: We used data collected in 2013 from 427 employees in 112 addiction health services programs in Los Angeles County, California. We relied on hierarchical linear models with robust standard errors to analyze multilevel data, individuals nested in programs. We conducted two path models to estimate multilevel relationships with two EBPs: contingency management and medication-assisted treatment. RESULTS: Findings partially supported our theory-driven multilevel leadership model. Specifically, results demonstrated that middle managers' implementation leadership mediated the relationship between top managers' transformational leadership and attitudes toward EBPs. At the same time, they showed the mediated relationship for delivery of contingency management treatment was only marginally significant (standardized indirect effect = .006, bootstrap p = .091). We did not find a mediation effect for medication-assisted treatment. DISCUSSION: Findings advance leadership theory in health care, highlighting the importance of middle managers' implementation leadership in transmitting the influence of top managers' transformational leadership on staff attitudes toward EBPs. The full path model shows the extent to which transformational leadership may influence staff implementation of innovative practices as mediated through staff attitudes toward EBPs and middle managers' implementation leadership. PRACTICE IMPLICATIONS: Our findings have implications for developing a multilevel leadership approach to implementation in health care. Leadership development should build on different competencies based on managers' level but align managers' priorities on the same implementation goals.

Organizational factors associated with practitioners' support for treatment of opioid use disorder in the emergency department.

BACKGROUND: Despite the significant increase in emergency room visits for opioid overdose, only few emergency departments (ED) have implemented best practices to treat people with opioid use disorders (OUD). Some implementation gaps may be due to practitioner factors; such as support for medication-assisted treatment (MAT) for OUD in the ED. In this study, we explore the relationship between inner setting characteristics of the EDs (e.g., leadership, readiness for change, organizational climate) and practitioner support for OUD treatment and attitudes towards people with OUD. METHODS: We surveyed 241 ED practitioners (e.g., physicians, nurses, social workers) at one of the largest EDs in the United States. We used analysis of variance and chi-square global tests to compare responses from ED practitioners in differing roles. We also conducted five multivariate logistic regressions to explore associations between ED inner setting characteristics and five antecedents of implementation; ED practitioner (1) supports MAT for OUD in the ED, (2) supports best practices to treat OUD, (3) has self-efficacy to treat OUD, (4) has stereotypes of people who use drugs, and (5) has optimism to treat people with OUD. RESULTS: We found nurses were more likely than physicians to support MAT for OUD in the ED and delivering other best practices to treat OUD. At the same time, nurses had greater bias than physicians against working with patients suffering from OUD. We also found the ED's climate for innovation and practitioners' readiness for change were positively associated with support for MAT for OUD in the ED and using best practices to treat OUD. CONCLUSIONS: Findings suggest that professional roles and some ED inner setting factors play an important role in antecedents of implementation of OUD treatment in the ED. To prepare EDs to effectively respond to the current opioid overdose epidemic, it is critical to further understand the impact of these organizational factors on the implementation of evidence-based OUD treatment practices in the nation.

Drivers of continued implementation of cultural competence in substance use disorder treatment.

The purpose of this study was to examine whether the key characteristics of organizational decision makers predicted continued implementation of five different practices that represent organizational cultural competence in one of the largest and most diverse substance use disorder (SUD) treatment systems in the United States. We analyzed data collected from SUD treatment programs at four-time points: 2011 (N = 115), 2013 (N = 111), 2015 (N = 106), and 2017 (N = 94). We conducted five mixed-effect linear regression models, one per each outcome to examine the extent to which program director's transformational leadership and ethnic background (Latino) predicted (1) knowledge of minority community needs; (2) development of resources and linkages to serve minorities; (3) reaching out to minority communities; (4) hiring and retention of staff members from minority backgrounds; and (5) development of policies and procedures to effectively respond to the service needs of minority patients. Results show that two of the five practices continued implementation at same degree (resources and linkages and policies and procedures), one practice increased degree of implementation (knowledge), while two practices reduced degree of implementation (staffing and outreach to communities) over the six-year period. Directorial leadership was positively associated with the continued implementation of all five practices. Latino directors were associated with an increase in knowledge of minority communities, but a decrease in resources and linkages and policies and procedures to serve minorities. On the other hand, interactions showed that leadership among Latino directors increased staffing over time and led to increases in resources and linkages and policies and procedures overtime. Overall, continued implementation of culturally responsive practices was uneven in the SUD treatment system studied. But program directors' transformational leadership and ethnic background played a critical role in increasing the implementation of key practices over time. Findings have implications for developing and testing culturally grounded leadership interventions for program directors to ensure the continued and increased implementation of practices that are necessary to improve standards of care in minority health.

Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.

Accurate prognosis of patients with cancer is important for the stratification of patients, the optimization of treatment strategies, and the design of clinical trials. Both clinical features and molecular data can be used for this purpose, for instance, to predict the survival of patients censored at specific time points. Multi-omics data, including genome-wide gene expression, methylation, protein expression, copy number alteration, and somatic mutation data, are becoming increasingly common in cancer studies. To harness the rich information in multi-omics data, we developed GDP (Group lass regularized Deep learning for cancer Prognosis), a computational tool for survival prediction using both clinical and multi-omics data. GDP integrated a deep learning framework and Cox proportional hazard model (CPH) together, and applied group lasso regularization to incorporate gene-level group prior knowledge into the model training process. We evaluated its performance in both simulated and real data from The Cancer Genome Atlas (TCGA) project. In simulated data, our results supported the importance of group prior information in the regularization of the model. Compared to the standard lasso regularization, we showed that group lasso achieved higher prediction accuracy when the group prior knowledge was provided. We also found that GDP performed better than CPH for complex survival data. Furthermore, analysis on real data demonstrated that GDP performed favorably against other methods in several cancers with large-scale omics data sets, such as glioblastoma multiforme, kidney renal clear cell carcinoma, and bladder urothelial carcinoma. In summary, we demonstrated that GDP is a powerful tool for prognosis of patients with cancer, especially when large-scale molecular features are available.