Cascade of care for office-based buprenorphine treatment in Bronx community clinics.

INTRODUCTION: The cascade of care for opioid use disorder (OUD) has been described at the population level to inform health policy and in health care systems, programs, and communities to guide targeted interventions. Office-based buprenorphine treatment is essential for expanding access to OUD treatment; however, few studies examine the cascade of care specifically for office-based buprenorphine treatment. Our objective was to describe a cascade of care for patients referred for office-based buprenorphine treatment in the primary care setting. METHODS: We conducted a retrospective cohort study of patients with OUD who were referred for office-based buprenorphine treatment within a large, urban health care system between 2018 and 2019. Our primary outcomes included completion of each step of the buprenorphine treatment cascade of care: 1) referred for treatment, 2) scheduled initial visit, 3) completed initial visit, 4) initiated buprenorphine treatment, and 5) retained in treatment at 90 days. We constructed a cascade of care by calculating proportions of patients identified at every step, starting with the total number of patients referred for treatment as the first step. We extracted data from the program's referral database and electronic medical record system. We compared characteristics of patients referred who initiated buprenorphine to those referred who did not initiate buprenorphine treatment using chi-squared tests and t-tests. To account for the hierarchical nature of the data, we conducted a Generalized Estimating Equation (GEE) modeling to test the differences in attrition rates among the steps of the cascade of care. RESULTS: In the 24-month period between 2018 and 2019, 226 patients were referred for office-based buprenorphine treatment at Montefiore's Buprenorphine Treatment Network. Patients' mean age at referral was 47 years, and most were male (68.6%), Hispanic (49.6%), and publicly insured (75.7%). Among all patients, 182 (80.5%) were scheduled for an initial visit, 142 (62.8%) completed the initial visit, 134 (59.3%) initiated buprenorphine treatment, and 95 (42.0%) were retained in treatment at 90 days. 37.2% of all patients referred did not complete the initial visit. A GEE model showed that attrition is significantly steeper in the first two steps of the cascade of care, compared to the later three steps (AOR = 1.95, 95% CI = 1.31-2.91, p < 0.05). Compared to referred patients who did not initiate treatment, those referred who initiated treatment were more likely to be using non-prescribed buprenorphine at time of referral (19.4% vs. 5.4%, p < 0.05) and be self-referred (22.4% vs. 9.8%, p < 0.05). CONCLUSION: Our study is the first to describe a cascade of care for office-based buprenorphine treatment in a large health care system. The study observed the steepest attrition in the first two steps of the cascade of care, where more than a third of patients referred did not complete the initial visit. Patients who were self-referred, or using non-prescribed buprenorphine were more likely to initiate treatment. A cascade of care specific for office-based buprenorphine can inform future efforts to improve linkage to care.

Mobile food vendors in urban neighborhoods-implications for diet and diet-related health by weather and season.

This study describes mobile food vendors (street vendors) in Bronx, NY, considering neighborhood-level correlations with demographic, diet, and diet-related health measures from City data. Vendors offering exclusively "less-healthy" foods (e.g., chips, processed meats, sweets) outnumbered vendors offering exclusively "healthier" foods (e.g., produce, whole grains, nuts). Wet days and winter months reduced all vending on streets, but exclusively "less-healthy" vending most. In summer, exclusively "less-healthy" vending per capita inversely correlated with neighborhood-mean fruit-and-vegetable consumption and directly correlated with neighborhood-mean BMI and prevalences of hypertension and hypercholesterolemia (Spearman correlations 0.90-1.00, p values 0.037 to <0.001). In winter, "less-healthy" vending per capita directly correlated with proportions of Hispanic residents and those living in poverty (Spearman correlations 0.90, p values 0.037). Mobile food vending may contribute negatively to urban food-environment healthfulness overall, but exacerbation of demographic, diet, and diet-related health disparities may vary by weather, season, and neighborhood characteristics.

Business list vs ground observation for measuring a food environment: saving time or waste of time (or worse)?

In food-environment research, an alternative to resource-intensive direct observation on the ground has been the use of commercial business lists. We sought to determine how well a frequently used commercial business list measures a dense urban food environment like the Bronx, NY. On 155 Bronx street segments, investigators compared two different levels for matches between the business list and direct ground observation: lenient (by business type) and strict (by business name). For each level of matching, researchers calculated sensitivities and positive predictive values (PPVs) for the business list overall and by broad business categories: General Grocers (eg, supermarkets), Specialty Food Stores (eg, produce markets), Restaurants, and Businesses Not Primarily Selling Food (eg, newsstands). Even after cleaning the business list (eg, for cases of multiple listings at a single location), and allowing for inexactness in listed street addresses and spellings of business names, the overall performance of the business list was poor. For strict matches, the business list had an overall sensitivity of 39.3% and PPV of 45.5%. Sensitivities and PPVs by broad business categories were not meaningfully different from overall values, although sensitivity for General Grocers and PPV for Specialty Food Stores were particularly low: 26.2% and 32%, respectively. For lenient matches, sensitivities and PPVs were somewhat higher but still poor: 52.4% to 60% and 60% to 75%, respectively. The business list is inadequate to measure the actual food environment in the Bronx. If results represent performance in other settings, findings from prior studies linking food environments to diet and diet-related health outcomes using such business lists are in question, and future studies of this type should avoid relying solely on such business lists.