Trends in the availability of comprehensive services within outpatient substance use treatment facilities from 2018 to 2022.

Background: Little is known regarding the extent to which substance use disorder (SUD) treatment facilities adopt comprehensive services to meet patients' medical and social needs.Objective: To examine trends in the availability of comprehensive services within outpatient SUD treatment facilities from 2018 to 2022.Methods: We used data from the Mental Health and Addiction Treatment Tracking Repository, a national database of SUD treatment facilities (n = 13,793). We examined the availability of four domains of comprehensive services and four types of SUD treatment services from 2018 to 2022. We conducted bivariate and multivariate logistic regression predicting the availability of a comprehensive service model (defined as having at least one service from each service domain), controlling for organizational and community characteristics.Results: Comprehensive services were increasingly offered from 2018 to 2022. In unadjusted and adjusted models, facilities which were externally accredited (OR: 1.50; 95%CI: 1.30-1.74), accepted Medicaid (OR: 1.51; 95%CI: 1.30-1.74), performed community outreach (OR: 2.05; 95%CI: 1.80-2.33), provided naloxone and overdose education (OR: 3.50; 95%CI: 3.06-3.99), had a robust SUD treatment infrastructure (OR: 2.33; 95%CI; 2.08-2.62), and were located in a county with a lower percentage of White residents (OR: 0.99; 95%CI: 0.99-0.99), a higher percentage of residents in poverty (OR: 1.02; 95%CI: 1.00-1.03), and the Northeast compared with the South (OR: 1.21; 95%CI: 1.01-1.45), had significantly higher odds of adopting a comprehensive service model.Conclusion: Findings highlight the importance of factors reflecting experience with organizational change efforts and enhanced external support. Policymakers working to enhance the uptake of comprehensive services should focus on obtaining the financial and technical support necessary to develop these models.

Hospital use of common Z-codes for Medicare fee-for-service beneficiaries, 2017-2021.

Recognizing the impact of the social determinants of health (SDOH) on health outcomes, in 2016, the Centers for Medicare and Medicaid Services recommended the use of International Classification of Diseases, 10th Revision (ICD-10), Z-codes to capture patients' health-related social needs. We examined changes in Z-code utilization to document health-related social needs for Medicare fee-for-service recipients among US hospitals between 2017 and 2021 across 5 common SDOH domains. We found that, while 56.9% of hospitals had at least 1 Z-code recorded in at least 1 patient per year, apart from those referring to housing needs, rates of Z-code adoption were low. Additionally, hospitals that were general medical, part of a teaching institution, affiliated with larger health systems, and of medium to large size had greater odds of utilizing Z-codes. Findings from this study highlight the need for continued efforts in promoting the consistent use of standardized SDOH capturing methods like Z-code documentation, such as provider training.

Comparing Rates of Undiagnosed Hypertension and Diabetes in Patients With and Without Substance Use Disorders.

BACKGROUND: Individuals with substance use disorders (SUDs) have increased risk for developing chronic conditions, though few studies assess rates of diagnosis of these conditions among patients with SUDs. OBJECTIVE: To compare rates of undiagnosed hypertension and diabetes among patients with and without an SUD. DESIGN: Cross-sectional analysis using electronic health record (EHR) data from 58 primary care clinics at a large, urban, healthcare system in New York. PARTICIPANTS: Patients who had at least two primary care visits from 2019-2022 were included in our patient sample. Patients without an ICD-10 hypertension diagnosis or prescribed hypertension medications and with at least two blood pressure (BP) readings ≥ 140/90 mm were labeled 'undiagnosed hypertension,' and patients without a diabetes diagnosis or prescribed diabetes medications and with A1C/hemoglobin ≥ 6.5% were labeled 'undiagnosed diabetes.' MAIN MEASURES: We calculated the mean number of patients with and without an ICD-10 SUD diagnosis who were diagnosed and undiagnosed for each condition. We used multivariate logistic regression to assess the association between being undiagnosed for each condition, and having an SUD diagnosis, patient demographic characteristics, clinical characteristics (body mass index, Elixhauser comorbidity count, diagnosed HIV and psychosis), the percentage of visits without a BP screening, and the total number of visits during the time period. KEY RESULTS: The percentage of patients with undiagnosed hypertension (2.74%) and diabetes (22.98%) was higher amongst patients with SUD than patients without SUD. In multivariate models, controlling for other factors, patients with SUD had significantly higher odds of having undiagnosed hypertension (OR: 1.81; 95% CI: 1.48, 2.20) and undiagnosed diabetes (OR: 1.93; 1.72, 2.16). Being younger, female, and having an HIV diagnosis was also associated with significantly higher odds for being undiagnosed. CONCLUSIONS: We found significant disparities in rates of undiagnosed chronic diseases among patients with SUDs, compared with patients without SUDs.

Initiatives to Support the Transition of Patients With Substance Use Disorders From Acute Care to Community-based Services Among a National Sample of Nonprofit Hospitals.

BACKGROUND: Hospitals are a key touchpoint to reach patients with substance use disorders (SUDs) and link them with ongoing community-based services. Although there are many acute care interventions to initiate SUD treatment in hospital settings, less is known about what services are offered to transition patients to ongoing care after discharge. In this study, we explore what SUD care transition strategies are offered across nonprofit US hospitals. METHODS: We analyzed administrative documents from a national sample of US hospitals that indicated SUD as a top 5 significant community need in their Community Health Needs Assessment reports (2019-2021). Data were coded and categorized based on the nature of described services. We used data on hospitals and characteristics of surrounding counties to identify factors associated with hospitals' endorsement of transition interventions for SUD. RESULTS: Of 613 included hospitals, 313 prioritized SUD as a significant community need. Fifty-three of these hospitals (17%) offered acute care interventions to support patients' transition to community-based SUD services. Most (68%) of the 53 hospitals described transition strategies without further detail, 23% described scheduling appointments before discharge, and 11% described discussing treatment options before discharge. No hospital characteristics were associated with offering transition interventions, but such hospitals were more likely to be in the Northeast, in counties with higher median income, and states that expanded Medicaid. CONCLUSIONS: Despite high need, most US hospitals are not offering interventions to link patients with SUD from acute to community care. Efforts to increase acute care interventions for SUD should identify and implement best practices to support care continuity.

Rural-urban disparities in the availability of hospital-based screening, medications for opioid use disorder, and addiction consult services.

INTRODUCTION: Hospitals are an ideal setting to stage opioid-related interventions with patients who are hospitalized due to overdose or other substance use-related complications. Transitional opioid programs-which initiate care and provide linkages upon discharge, such as screening, initiation of medications for opioid use disorder, and addiction consult services-have become the gold standard, but implementation has been uneven. The purpose of this study was to assess disparities in the availability of hospital-based transitional opioid programs, across rural and urban hospital settings in the United States. METHODS: Using hospital administrative data paired with county-level demographic data, we conducted bivariate and regression analyses to assess rural-urban differences in the availability of transitional opioid services including screening, addiction consult services, and MOUD in U.S general medical centers, controlling for hospital- and community-level factors. Our sample included 2846 general medical hospitals that completed the 2021 American Hospital Association (AHA) Annual Survey of Hospitals. Our primary outcomes were five self-reported measures: whether the hospital provided screening in the ED; provided screening in the inpatient setting; whether the hospital provided addiction consult services in the ED; provided addiction consult services in the inpatient setting; and whether the hospital provided medications for opioid use disorder. RESULTS: Rural hospitals did not have lower odds of screening for OUD or other SUDs than urban hospitals, but both micropolitan rural counties and noncore rural counties had significantly lower odds of having addiction consult services in either the ED (OR: 0.74, 95 % CI: 0.58, 0.95; OR: 0.68, 95 % CI: 0.50, 0.91) or inpatient setting (OR: 0.76, 95 % CI: 0.59, 0.97; OR: 0.68, 95 % CI: 0.50, 0.93), respectively, or of offering MOUD (OR: 0.69, 95 % CI: 0.52, 0.90; OR: 0.52, 95 % CI: 0.37, 0.74). CONCLUSIONS: Our study suggests that evidence-based interventions, such as medications for opioid use disorder and addiction consult services, are less often available in rural hospitals, which may contribute to rural-urban disparities in health outcomes secondary to OUD. A priority for population health improvement should be developing implementation strategies to support rural hospital adoption of transitional opioid programs.

Strategies to support substance use disorder care transitions from acute-care to community-based settings: a scoping review and typology.

BACKGROUND: Acute-care interventions that identify patients with substance use disorders (SUDs), initiate treatment, and link patients to community-based services, have proliferated in recent years. Yet, much is unknown about the specific strategies being used to support continuity of care from emergency department (ED) or inpatient hospital settings to community-based SUD treatment. In this scoping review, we synthesize the existing literature on patient transition interventions, and form an initial typology of reported strategies. METHODS: We searched Pubmed, Embase, CINAHL and PsychINFO for peer-reviewed articles published between 2000 and 2021 that studied interventions linking patients with SUD from ED or inpatient hospital settings to community-based SUD services. Eligible articles measured at least one post-discharge treatment outcome and included a description of the strategy used to promote linkage to community care. Detailed information was extracted on the components of the transition strategies and a thematic coding process was used to categorize strategies into a typology based on shared characteristics. Facilitators and barriers to transitions of care were synthesized using the Consolidated Framework for Implementation Research. RESULTS: Forty-five articles met inclusion criteria. 62% included ED interventions and 44% inpatient interventions. The majority focused on patients with opioid (71%) or alcohol (31%) use disorder. The transition strategies reported across studies were heterogeneous and often not well described. An initial typology of ten transition strategies, including five pre- and five post-discharge transition strategies is proposed. The most common strategy was scheduling an appointment with a community-based treatment provider prior to discharge. A range of facilitators and barriers were described, which can inform efforts to improve hospital-to-community transitions of care. CONCLUSIONS: Strategies to support transitions from acute-care to community-based SUD services, although critical for ensuring continuity of care, vary greatly across interventions and are inconsistently measured and described. More research is needed to classify SUD care transition strategies, understand their components, and explore which lead to the best patient outcomes.

Rural-urban disparities in health outcomes, clinical care, health behaviors, and social determinants of health and an action-oriented, dynamic tool for visualizing them.

While rural-urban disparities in health and health outcomes have been demonstrated, because of their impact on (and intervenability to improve) health and health outcomes, we sought to examine cross-sectional and longitudinal inequities in health, clinical care, health behaviors, and social determinants of health (SDOH) between rural and non-rural counties in the pre-pandemic era (2015 to 2019), and to present a Health Equity Dashboard that can be used by policymakers and researchers to facilitate examining such disparities. Therefore, using data obtained from 2015-2022 County Health Rankings datasets, we used analysis of variance to examine differences in 33 county level attributes between rural and non-rural counties, calculated the change in values for each measure between 2015 and 2019, determined whether rural-urban disparities had widened, and used those data to create a Health Equity Dashboard that displays county-level individual measures or compilations of them. We followed STROBE guidelines in writing the manuscript. We found that rural counties overwhelmingly had worse measures of SDOH at the county level. With few exceptions, the measures we examined were getting worse between 2015 and 2019 in all counties, relatively more so in rural counties, resulting in the widening of rural-urban disparities in these measures. When rural-urban gaps narrowed, it tended to be in measures wherein rural counties were outperforming urban ones in the earlier period. In conclusion, our findings highlight the need for policymakers to prioritize rural settings for interventions designed to improve health outcomes, likely through improving health behaviors, clinical care, social and environmental factors, and physical environment attributes. Visualization tools can help guide policymakers and researchers with grounded information, communicate necessary data to engage relevant stakeholders, and track SDOH changes and health outcomes over time.

An observational, sequential analysis of the relationship between local economic distress and inequities in health outcomes, clinical care, health behaviors, and social determinants of health.

BACKGROUND: Socioeconomic status has long been associated with population health and health outcomes. While ameliorating social determinants of health may improve health, identifying and targeting areas where feasible interventions are most needed would help improve health equity. We sought to identify inequities in health and social determinants of health (SDOH) associated with local economic distress at the county-level. METHODS: For 3,131 counties in the 50 US states and Washington, DC (wherein approximately 325,711,203 people lived in 2019), we conducted a retrospective analysis of county-level data collected from County Health Rankings in two periods (centering around 2015 and 2019). We used ANOVA to compare thirty-three measures across five health and SDOH domains (Health Outcomes, Clinical Care, Health Behaviors, Physical Environment, and Social and Economic Factors) that were available in both periods, changes in measures between periods, and ratios of measures for the least to most prosperous counties across county-level prosperity quintiles, based on the Economic Innovation Group's 2015-2019 Distressed Community Index Scores. RESULTS: With seven exceptions, in both periods, we found a worsening of values with each progression from more to less prosperous counties, with least prosperous counties having the worst values (ANOVA p < 0.001 for all measures). Between 2015 and 2019, all except six measures progressively worsened when comparing higher to lower prosperity quintiles, and gaps between the least and most prosperous counties generally widened. CONCLUSIONS: In the late 2010s, the least prosperous US counties overwhelmingly had worse values in measures of Health Outcomes, Clinical Care, Health Behaviors, the Physical Environment, and Social and Economic Factors than more prosperous counties. Between 2015 and 2019, for most measures, inequities between the least and most prosperous counties widened. Our findings suggest that local economic prosperity may serve as a proxy for health and SDOH status of the community. Policymakers and leaders in public and private sectors might use long-term, targeted economic stimuli in low prosperity counties to generate local, community health benefits for vulnerable populations. Doing so could sustainably improve health; not doing so will continue to generate poor health outcomes and ever-widening economic disparities.

Substance Use Disorder Program Availability in Safety-Net and Non-Safety-Net Hospitals in the US.

Importance: Safety-net hospitals (SNHs) are ideal sites to deliver addiction treatment to patients with substance use disorders (SUDs), but the availability of these services within SNHs nationwide remains unknown. Objective: To examine differences in the delivery of different SUD programs in SNHs vs non-SNHs across the US and to determine whether these differences are increased in certain types of SNHs depending on ownership. Design, Setting, and Participants: This cross-sectional analysis used data from the 2021 American Hospital Association Annual Survey of Hospitals to examine the associations of safety-net status and ownership with the availability of SUD services at acute care hospitals in the US. Data analysis was performed from January to March 2022. Main Outcomes and Measures: This study used 2 survey questions from the American Hospital Association survey to determine the delivery of 5 hospital-based SUD services: screening, consultation, inpatient treatment services, outpatient treatment services, and medications for opioid use disorder (MOUD). Results: A total of 2846 hospitals were included: 409 were SNHs and 2437 were non-SNHs. The lowest proportion of hospitals reported offering inpatient treatment services (791 hospitals [27%]), followed by MOUD (1055 hospitals [37%]), and outpatient treatment services (1087 hospitals [38%]). The majority of hospitals reported offering consultation (1704 hospitals [60%]) and screening (2240 hospitals [79%]). In multivariable models, SNHs were significantly less likely to offer SUD services across all 5 categories of services (screening odds ratio [OR], 0.62 [95% CI, 0.48-0.76]; consultation OR, 0.62 [95% CI, 0.47-0.83]; inpatient services OR, 0.73 [95% CI, 0.55-0.97]; outpatient services OR, 0.76 [95% CI, 0.59-0.99]; MOUD OR, 0.6 [95% CI, 0.46-0.78]). With the exception of MOUD, public or for-profit SNHs did not differ significantly from their non-SNH counterparts. However, nonprofit SNHs were significantly less likely to offer all 5 SUD services compared with their non-SNH counterparts (screening OR, 0.52 [95% CI, 0.41-0.66]; consultation OR, 0.56 [95% CI, 0.44-0.73]; inpatient services OR, 0.45 [95% CI, 0.33-0.61]; outpatient services OR, 0.58 [95% CI, 0.44-0.76]; MOUD OR, 0.61 [95% CI, 0.46-0.79]). Conclusions and Relevance: In this cross-sectional study of SNHs and non-SNHs, SNHs had significantly lower odds of offering the full range of SUD services. These findings add to a growing body of research suggesting that SNHs may face additional barriers to offering SUD programs. Further research is needed to understand these barriers and to identify strategies that support the adoption of evidence-based SUD programs in SNH settings.

Strategies to support substance use disorder care transitions from acute-care to community-based settings: A Scoping review and typology.

Background: Acute-care interventions that identify patients with substance use disorders (SUDs), initiate treatment, and link patients to community-based services, have proliferated in recent years. Yet, much is unknown about the specific strategies being used to support continuity of care from emergency department (ED) or inpatient hospital settings to community-based SUD treatment. In this scoping review, we synthesize the existing literature on patient transition interventions, and form an initial typology of reported strategies. Methods: We searched Pubmed, Embase, CINAHL and PsychINFO for peer-reviewed articles published between 2000-2021 that studied interventions linking SUD patients from ED or inpatient hospital settings to community-based SUD services. Eligible articles measured at least one post-discharge treatment outcome and included a description of the strategy used to promote linkage to community care. Detailed information was extracted on the components of the transition strategies and a thematic coding process was used to categorize strategies into a typology based on shared characteristics. Facilitators and barriers to transitions of care were synthesized using the Consolidated Framework for Implementation Research. Results: Forty-five articles met inclusion criteria. 62% included ED interventions and 44% inpatient interventions. The majority focused on patients with opioid (71%) followed by alcohol (31%) use disorder. The transition strategies reported across studies were heterogeneous and often not well described. An initial typology of ten transition strategies, including five pre- and five post-discharge transition strategies is proposed. The most common strategy was scheduling an appointment with a community-based treatment provider prior to discharge. A range of facilitators and barriers were described, which can inform efforts to improve hospital-to-community transitions of care. Conclusions: Strategies to support transitions from acute-care to community-based SUD services, although critical for ensuring continuity of care, vary greatly across interventions and are inconsistently measured and described. More research is needed to classify SUD care transition strategies, understand their components, and explore which lead to the best patient outcomes.

Factors associated with the adoption of evidence-based innovations by substance use disorder treatment organizations: A study of HIV testing.

INTRODUCTION: Though prior research shows that a range of important regulatory, market, community, and organizational factors influence the adoption of evidence-based practices (EBPs) among health care organizations, we have little understanding of how these factors relate to each other. To address this gap, we test a conceptual model that emphasizes indirect, mediated effects among key factors related to HIV testing in substance use disorder treatment organizations (SUTs), a critical EBP during the US opioid epidemic. METHODS: We draw on nationally representative data from the 2014 (n = 697) and 2017 (n = 657) National Drug Abuse Treatment System Survey (NDATSS) to measure the adoption of HIV testing among the nation's SUTs and their key organizational characteristics; we also draw on data from the US Census Bureau; Centers for Disease Control; and legislative sources to measure regulatory and community environments. We estimate cross-sectional and longitudinal structural equation models (SEM) to test the proposed model. RESULTS: Our longitudinal model of the adoption of HIV testing by SUTs in the United States identifies a pathway by which community and market characteristics (rurality and the number of other SUTs in the area) are related to key sociotechnical characteristics of these organizations (alignment of clients, staff, and harm-reduction culture) that, in turn, are related to the adoption of this EBP. CONCLUSIONS: Results also show the importance of developing conceptual models that include indirect effects to account for organizational adoption of EBPs.

Rapid Transition to Telehealth and the Digital Divide: Implications for Primary Care Access and Equity in a Post-COVID Era.

Policy Points Telehealth has many potential advantages during an infectious disease outbreak such as the COVID-19 pandemic, and the COVID-19 pandemic has accelerated the shift to telehealth as a prominent care delivery mode. Not all health care providers and patients are equally ready to take part in the telehealth revolution, which raises concerns for health equity during and after the COVID-19 pandemic. Without proactive efforts to address both patient- and provider-related digital barriers associated with socioeconomic status, the wide-scale implementation of telehealth amid COVID-19 may reinforce disparities in health access in already marginalized and underserved communities. To ensure greater telehealth equity, policy changes should address barriers faced overwhelmingly by marginalized patient populations and those who serve them. CONTEXT: The COVID-19 pandemic has catalyzed fundamental shifts across the US health care delivery system, including a rapid transition to telehealth. Telehealth has many potential advantages, including maintaining critical access to care while keeping both patients and providers safe from unnecessary exposure to the coronavirus. However, not all health care providers and patients are equally ready to take part in this digital revolution, which raises concerns for health equity during and after the COVID-19 pandemic. METHODS: The study analyzed data about small primary care practices' telehealth use and barriers to telehealth use collected from rapid-response surveys administered by the New York City Department of Health and Mental Hygiene's Bureau of Equitable Health Systems and New York University from mid-April through mid-June 2020 as part of the city's efforts to understand how primary care practices were responding to the COVID-19 pandemic following New York State's stay-at-home order on March 22. We focused on small primary care practices because they represent 40% of primary care providers and are disproportionately located in low-income, minority or immigrant areas that were more severely impacted by COVID-19. To examine whether telehealth use and barriers differed based on the socioeconomic characteristics of the communities served by these practices, we used the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to stratify respondents as being in high-SVI or low-SVI areas. We then characterized respondents' telehealth use and barriers to adoption by using means and proportions with 95% confidence intervals. In addition to a primary analysis using pooled data across the five waves of the survey, we performed sensitivity analyses using data from respondents who only took one survey, first wave only, and the last two waves only. FINDINGS: While all providers rapidly shifted to telehealth, there were differences based on community characteristics in both the primary mode of telehealth used and the types of barriers experienced by providers. Providers in high-SVI areas were almost twice as likely as providers in low-SVI areas to use telephones as their primary telehealth modality (41.7% vs 23.8%; P <.001). The opposite was true for video, which was used as the primary telehealth modality by 18.7% of providers in high-SVI areas and 33.7% of providers in low-SVI areas (P <0.001). Providers in high-SVI areas also faced more patient-related barriers and fewer provider-related barriers than those in low-SVI areas. CONCLUSIONS: Between April and June 2020, telehealth became a prominent mode of primary care delivery in New York City. However, the transition to telehealth did not unfold in the same manner across communities. To ensure greater telehealth equity, policy changes should address barriers faced overwhelmingly by marginalized patient populations and those who serve them.