Associations between Patient Experience and Addiction Treatment Facility Services: Results of the Addiction Treatment Locator, Assessment, and Standards Surveys.

OBJECTIVES: Patient experience and presence of evidence-based facility services are 2 dimensions of assessing quality of addiction treatment facilities. However, the relationship between these two is not well described. The objective of this study was to explore associations between patient experience measures and service offerings at addiction treatment facilities. METHODS: We used data from cross-sectional surveys of addiction treatment facilities and persons involved in treatment at corresponding facilities to identify facility services (eg, availability of medications for alcohol use disorder, assistance with obtaining social services, etc) and patient experience measures (overall facility rating, extent helped by treatment, ability to deal with daily problems after treatment), respectively. We used hierarchical multiple logistic regression to test for associations between top-box scores for each patient experience outcome and facility services. RESULTS: We analyzed 9191 patient experience surveys from 149 facilities. Assistance with obtaining social services (adjusted odds ratio [95% confidence interval], 0.43 [0.28-0.66]) was associated with lower overall treatment facility ratings. Childcare (2.00 [1.04-3.84]) was associated with top-box scores for extent helped. Availability of cognitive behavioral therapy (2.67 [1.25-5.73]) and childcare (1.77 [1.08-2.92]) were associated with top-box scores for ability to deal with daily problems after treatment. Assistance with obtaining social services (0.61 [0.41-0.90]) was associated with lower scores for ability to deal with problems after treatment. CONCLUSIONS: Few addiction treatment facility services were associated with patient experience measures. Future work should explore bridging the gap between evidence-based services and positive patient experiences.

Drive Time to Addiction Treatment Facilities Providing Contingency Management across Rural and Urban Census Tracts in 6 US States.

OBJECTIVE: We examined drive times to outpatient substance use disorder treatment providers that provide contingency management (CM) and those that integrate CM with medication for opioid use disorder (MOUD) services in 6 US states. METHODS: We completed cross-sectional geospatial analysis among census tracts in Delaware, Louisiana, Massachusetts, North Carolina, New York, and West Virginia. We excluded census tracts with a population of zero. Using data from the 2020 Shatterproof substance use treatment facility survey, our outcome was the minimum drive time in minutes from the census tract mean center of population to the nearest outpatient CM provider, outpatient CM provider with MOUD services, and federally qualified health centers (FQHC). We stratified census tracts by 2010 Rural-Urban Commuting Area codes and by state. RESULTS: The population was greater than zero in 11,719 of 11,899 census tracts. The median drive time to the nearest CM provider was 12.2 [interquartile range (IQR), 7.0-23.5) minutes and the median drive time to the nearest CM provider increased from 9.7 (IQR, 6.0-15.0) minutes in urban census tracts to 38.8 (IQR, 25.4-53.0) minutes in rural ( H = 3683, P < 0.001). The median drive time increased to the nearest CM provider with MOUD services [14.2 (IQR, 7.9-29.5) minutes, W = 18,877, P < 0.001] and decreased to the nearest FQHC [7.9 (IQR, 4.3-13.6) minutes, W = 11,555,894, P < 0.001]. CONCLUSIONS: These results suggest limited availability of CM, particularly within rural communities and for patients needing concurrent CM and MOUD treatment. Our results suggest greater adoption of CM within FQHCs could reduce urban-rural disparities in CM availability.

Availability of Specific Programs and Medications for Addiction Treatment to Vulnerable Populations: Results from the Addiction Treatment Locator, Assessment, and Standards (ATLAS) Survey.

OBJECTIVES: This study aimed to describe addiction treatment facilities by their offerings of medications for alcohol use disorder (MAUD) and/or for opioid use disorder (MOUD), and by their offering services to groups with barriers to care: uninsured and publicly insured, youth, seniors, individuals preferring to receive care in Spanish, and sexual minority individuals. METHODS: We examined addiction treatment facility survey data in 6 US states. We performed bivariate analyses comparing facilities that offered MAUD, MOUD, and both (main outcomes). We then constructed a multivariable model to identify predictors of offering MAUD, MOUD, or both, including exposures that demonstrate programming for special populations. RESULTS: Among 2474 facilities, 1228 (50%) responded between October 2019 and January 2020. Programs were offered for youth (30%), elderly (40%), Spanish-speaking (37%), and sexual minority populations (39%), with 58% providing MAUD, 67% providing MOUD, and 56% providing both. Among those providing MAUD, MOUD, or both, a majority (>60% for all exposures) offered programming to vulnerable populations. With Delaware as reference, Louisiana (adjusted odds ratio [aOR], 0.28; 95% confidence interval [CI], 0.12-0.67) and North Carolina (aOR, 0.33; 95% CI, 0.15-0.72) facilities had lesser odds of offering both MAUD and MOUD. All exposures identifying facilities offering treatment to vulnerable groups were associated with offerings of MAUD and/or MOUD except for offerings to youth; these facilities had less odds of offering MOUD (aOR, 0.31; 95% CI, 0.31-0.62). CONCLUSIONS: There are facility-level disparities in providing MAUD and MOUD by state, and facilities with youth programming have lesser odds of offering MOUD than other facilities.

Clinical and Sociodemographic Factors Associated with Telemedicine Engagement in an Urban Community Health Center Cohort During the COVID-19 Pandemic.

Objective: To examine chronic diseases, clinical factors, and sociodemographic characteristics associated with telemedicine utilization among a safety-net population. Materials and Methods: We conducted a retrospective cohort study of adults seeking care in an urban, multisite community health center in the Northeast United States. We included adults with ≥1 outpatient in-person visit during the pre-COVID-19 period (March 1, 2019-February 29, 2020) and ≥1 outpatient visit (in-person or telemedicine) during the COVID-19 period (March 1, 2020-February 29, 2021). Multivariable logistic regression models estimated associations between clinical and sociodemographic factors and telemedicine use, classified as "any" (≥1 visit) and "high" (≥3 visits). Results: Among 5,793 patients who met inclusion criteria, 4,687 (80.9%) had any (≥1) telemedicine visit and 1,053 (18.2%) had high (≥3) telemedicine visits during the COVID-19 period. Older age and Medicare coverage were associated with having any telemedicine use. Older and White patients were more likely to have high telemedicine use. Uninsured patients were less likely to have high telemedicine use. Patients with increased health care utilization in the pre-COVID-19 period and those with hypertension, diabetes, substance use disorders, and depression were more likely to have high telemedicine engagement. Discussion: Chronic conditions, older patients, and White patients compared with Latinx patients, were associated with high telemedicine engagement after adjusting for prior health care utilization. Conclusion: Equity-focused approaches to telemedicine clinical strategies are needed for safety-net populations. Community health centers can adopt disease-specific telemedicine strategies with high patient engagement.

Demographic and Clinical Correlates of the Cost of Potentially Preventable Hospital Encounters in a Community Health Center Cohort.

This study sought to describe the cost of hospital care for ambulatory care-sensitive conditions (ACSCs) and to identify independent predictors of high-cost hospital encounters related to an ACSC among an urban community health center cohort. The authors conducted a retrospective cohort study of individuals engaged in care in a large, multisite community health center in New Haven, Connecticut, with any Medicaid claims between June 1, 2018 and March 31, 2020. Prevention Quality Indicators of the Agency for Healthcare Research and Quality were used to identify ACSCs. The primary outcome was a high-cost episode of care for an ACSC (in the top quartile within a 7-day period). Multivariable logistic regression was used to identify independent predictors of high-cost episodes by ACSCs among sociodemographic and clinical variables as covariates. Among 8019 included individuals, a total of 751 episodes of hospital care involving ACSCs were identified. The median episode cost was $793, with the highest median cost of care related to heart failure ($4992), followed by diabetes ($1162), and chronic obstructive pulmonary disease ($1141). In adjusted analyses, male gender (P < 0.01), increasing age (P = 0.02), and ACSC type (P < 0.01) were associated with higher costs of care; race/ethnicity was not. Community health centers in urban settings seeking to reduce the cost of care of potentially preventable hospitalizations may target disease-/condition-specific groups, particularly individuals of increasing age with congestive heart failure and diabetes mellitus. These findings may inform return-on-investment calculations for care coordination and other enabling services programming.

Screening for Social Determinants of Health Among Children: Patients' Preferences for Receiving Information to Meet Social Needs and a Comparison of Screening Instruments.

To characterize optimal strategies for screening for social determinants of health (SDOH) among children, the authors performed a cross-sectional study of parents and adolescents ages ≥13 years in a community health center. Participants were queried about how they prefer to receive information about social needs resources and 2 screening instruments were compared: Well Child Care, Evaluation, Community Resources, Advocacy, Referral, Education (WE CARE) and Accountable Health Communities (AHC). In July 2019, 154 parents and 21 adolescents were surveyed. Surveys were administered via tablet and required 5.6 minutes (standard deviation [SD] 3.9 minutes) for parents and 3.9 minutes (SD 1.4 minutes) for adolescents to complete. Parents identified technology (text message, email) and informational printouts as preferred mechanisms for information receipt (58% and 32% of participants, respectively); adolescents preferred text message (57%) and printouts (19%). Few (<10% overall) preferred in-person consultation with a care coordinator. Adolescent/parent pairs (n = 19 pairs) agreed, on average across SDOH, 82% of the time for WE CARE and 85% for AHC. AHC elicited more positive screens than WE CARE for housing insecurity (12% of parents versus 7%) and food insecurity (47% versus 16%) but fewer positive screens than WE CARE for difficulties paying for utilities (27% versus 39%). Routine screening for SDOH in children requires 2-3 minutes per screening instrument. Screening can target parents of young children and either adolescents themselves or their parents. Families prefer to receive information about meeting social needs via technologically-based methods as opposed to in-person consultation with enabling services providers.

Construction of a Pediatrics Risk Score to Predict High Health Care Costs Among a Community Health Center Cohort.

Risk-stratification strategies are needed for ambulatory pediatric populations. The authors sought to develop age-specific risk scores that predict high health care costs among an urban population. A retrospective cohort study was performed of children ages 1-18 years who received care at Fair Haven Community Health Care (FHCHC), a community health center in New Haven, Connecticut. Cost was estimated from charges in the electronic health record (EHR), which is shared with the only hospital system in the city. Using multivariable logistic regression models, independent predictors of being in the top decile of total charges during the 2017 calendar year were identified, drawing from covariates collected from the EHR prior to 2017. Random forest modeling was used to verify the feature importance of significant covariates and model performance from 2017 cost data were compared to those using 2018 cost data. Regression models were used to construct age-specific nomograms to predict cost. Among 8960 children who received care at FHCHC in the 18 months prior to 2017, covariate frequencies clustered in age groups 1-5 years, 6-11 years, and 12-18 years, so 3 age-specific models were constructed. Prior utilization variables predicted future costs, as did younger children who received specialty care and older children with behavioral health diagnoses. Final models for each age group had C statistics ≥0.68 using both 2017 and 2018 cost data. Prediction models can draw from elements accessible in the EHR to predict cost of ambulatory pediatric patients. Strategies to impact utilization among high-risk children are needed.

Two Novel Urban Health Primary Care Residency Tracks That Focus On Community-Level Structural Vulnerabilities.

BACKGROUND: Although residency programs are well situated for developing a physician workforce with knowledge, skills, and attitudes that incorporate the strengths and reflect the priorities of community organizations, few curricula explicitly do so. AIM: To develop urban health primary care tracks for internal medicine and combined internal medicine-pediatrics residents. SETTING: Academic hospital, community health center, and community-based organizations. PARTICIPANTS: Internal medicine and combined internal medicine-pediatrics residents. PROGRAM DESCRIPTION: The program integrates community-based experiences with a focus on stakeholder engagement into its curriculum. A significant portion of the training (28 weeks out of 3 years for internal medicine and 34 weeks out of 4 years for medicine-pediatrics) occurs outside the hospital and continuity clinic to support residents' understanding of structural vulnerabilities. PROGRAM EVALUATION: Sixteen internal medicine and 14 medicine-pediatrics residents have graduated from our programs. Fifty-six percent of internal medicine graduates and 79% of medicine-pediatrics graduates are seeking primary care careers, and eight overall (27%) have been placed in community organizations. Seven (23%) hold leadership positions. DISCUSSION: We implemented two novel residency tracks that successfully placed graduates in community-based primary care settings. Integrating primary care training with experiences in community organizations can create primary care leaders and may foster collective efficacy among medical centers and community organizations.