Resident Experiences With a Place-Based Collaboration to Address Health and Social Inequities: A Survey of Visitors to the East Harlem Neighborhood Health Action Center.

In 2016 and 2017, the New York City Department of Health and Mental Hygiene established Neighborhood Health Action Centers (Action Centers) in disinvested communities of color as part of a place-based model to advance health equity. This model includes co-located partners, a referral and linkage system, and community space and programming. In 2018, we surveyed visitors to the East Harlem Action Center to provide a more comprehensive understanding of visitors' experiences. The survey was administered in English, Spanish, and Mandarin. Respondents were racially diverse and predominantly residents of East Harlem. The majority had been to the East Harlem Action Center previously. Most agreed that the main service provider for their visit made them feel comfortable, treated them with respect, spoke in a way that was easy to understand, and that they received the highest quality of service. A little more than half of returning visitors reported engaging with more than one Action Center program in the last 6 months. Twenty-one percent of respondents reported receiving at least one referral at the Action Center. Two thirds were aware that the Action Center offered a number of programs and services and half were aware that referrals were available. Additional visits to the Action Center were associated with increased likelihood of engaging with more than one program and awareness of the availability of programs and referral services. Findings suggest that most visitors surveyed had positive experiences, and more can be done to promote the Action Center and the variety of services it offers.

Building a Culture of Health at the Neighborhood Level Through Governance Councils.

To explore facilitators and barriers to developing and sustaining collaboration among New York City Department of Health and Mental Hygiene's Neighborhood Health Action Centers and co-located partners, who share information and decision-making through a Governance Council structure of representative members. Semi-structured interviews were conducted in 2018 with 43 Governance Council members across the three Action Centers of East Harlem (13), Tremont (15), and Brownsville (15), New York City. Governance Council members identified collaboration through information- and resource-sharing, consistent meetings and continuous communication as valuable for fostering a culture of health in their communities. Immediate benefits included building relationships, increased access to resources, and increased reach and access to community members. Challenges included difficulty building community trust, insufficient advertisement of services, and navigation of government bureaucracy. The Governance Councils forged collaborative relationships among local government, community-based organizations and clinical providers to improve health and well-being in their neighborhoods. Sharing space, resources and information is feasible with a movement towards shared leadership and decision-making. This may result in community-driven and tailored solutions to historical inequities. In shared leadership models, some internal reform by Government partners may be required.

Computer self-administered screening for substance use in university student health centers.

Objective: To characterize the prevalence of tobacco, alcohol, and drug use and the acceptability of screening in university health centers. Participants: Five hundred and two consecutively recruited students presenting for primary care visits in February and August, 2015, in two health centers. Methods: Participants completed anonymous substance use questionnaires in the waiting area, and had the option of sharing results with their medical provider. We examined screening rates, prevalence, and predictors of sharing results. Results: Past-year use was 31.5% for tobacco, 67.1% for alcohol (>4 drinks/day), 38.6% for illicit drugs, and 9.2% for prescription drugs (nonmedical use). A minority (43.8%) shared screening results. Sharing was lowest among those with moderate-high risk use of tobacco (OR =0.37, 95% CI 0.20-0.69), alcohol (OR =0.48, 95% CI 0.25-0.90), or illicit drugs (OR =0.38, 95% CI 0.20-0.73). Conclusions: Screening can be integrated into university health services, but students with active substance use may be uncomfortable discussing it with medical providers.

Performance of the Tobacco, Alcohol, Prescription Medication, and Other Substance Use (TAPS) Tool for Substance Use Screening in Primary Care Patients.

BACKGROUND: Substance use, a leading cause of illness and death, is underidentified in medical practice. OBJECTIVE: The Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS) tool was developed to address the need for a brief screening and assessment instrument that includes all commonly used substances and fits into clinical workflows. The goal of this study was to assess the performance of the TAPS tool in primary care patients. DESIGN: Multisite study, conducted within the National Drug Abuse Treatment Clinical Trials Network, comparing the TAPS tool with a reference standard measure. (ClinicalTrials.gov: NCT02110693). SETTING: 5 adult primary care clinics. PARTICIPANTS: 2000 adult patients consecutively recruited from clinic waiting areas. MEASUREMENTS: Interviewer- and self-administered versions of the TAPS tool were compared with a reference standard, the modified World Mental Health Composite International Diagnostic Interview (CIDI), which measures problem use and substance use disorder (SUD). RESULTS: Interviewer- and self-administered versions of the TAPS tool had similar diagnostic characteristics. For identifying problem use (at a cutoff of 1+), the TAPS tool had a sensitivity of 0.93 (95% CI, 0.90 to 0.95) and specificity of 0.87 (CI, 0.85 to 0.89) for tobacco and a sensitivity of 0.74 (CI, 0.70 to 0.78) and specificity of 0.79 (CI, 0.76 to 0.81) for alcohol. For problem use of illicit and prescription drugs, sensitivity ranged from 0.82 (CI, 0.76 to 0.87) for marijuana to 0.63 (CI, 0.47 to 0.78) for sedatives; specificity was 0.93 or higher. For identifying any SUD (at a cutoff of 2+), sensitivity was lower. LIMITATIONS: The low prevalence of some drug classes led to poor precision in some estimates. Research assistants were not blinded to participants' TAPS tool responses when they administered the CIDI. CONCLUSION: In a diverse population of adult primary care patients, the TAPS tool detected clinically relevant problem substance use. Although it also may detect tobacco, alcohol, and marijuana use disorders, further refinement is needed before it can be recommended broadly for SUD screening. PRIMARY FUNDING SOURCE: National Institute on Drug Abuse.