Trends in Medically Integrated Dispensing Among Oncology Practices.

PURPOSE: The integration of pharmacies with oncology practices-known as medically integrated dispensing or in-office dispensing-could improve care coordination but may incentivize overprescribing or inappropriate prescribing. Because little is known about this emerging phenomenon, we analyzed historical trends in medically integrated dispensing. METHODS: Annual IQVIA data on oncologists were linked to 2010-2019 National Council for Prescription Drug Programs pharmacy data; data on commercially insured patients diagnosed with any of six common cancer types; and summary data on providers' Medicare billing. We calculated the national prevalence of medically integrated dispensing among community and hospital-based oncologists. We also analyzed the characteristics of the oncologists and patients affected by this care model. RESULTS: Between 2010 and 2019, the percentage of oncologists in practices with medically integrated dispensing increased from 12.8% to 32.1%. The share of community oncologists in dispensing practices increased from 7.6% to 28.3%, whereas the share of hospital-based oncologists in dispensing practices increased from 18.3% to 33.4%. Rates of medically integrated dispensing varied considerably across states. Oncologists who dispensed had higher patient volumes (P < .001) and a smaller share of Medicare beneficiaries (P < .001) than physicians who did not dispense. Patients treated by dispensing oncologists had higher risk and comorbidity scores (P < .001) and lived in areas with a higher % Black population (P < .001) than patients treated by nondispensing oncologists. CONCLUSION: Medically integrated dispensing has increased significantly among oncology practices over the past 10 years. The reach, clinical impact, and economic implications of medically integrated dispensing should be evaluated on an ongoing basis.

Agent-based modeling insights into the optimal distribution of the Fresh Fruit and Vegetable Program.

The Fresh Fruit and Vegetable Program (FFVP) program provides a free fresh fruit or vegetable snack to children in low-income schools between two and five times a week. This is an important nationwide program, but current funding levels are insufficient to reach all eligible schools. Thus, there is a need to develop insight on contextual factors that may impact the effectiveness of FFVP in facilitating the development of childhood food preferences. An agent-based model of preference formation is used to understand how exposure to FFVP in early elementary school may affect preferences for healthy food by 6th grade. Preferences are modeled using the temporal difference learning algorithm used by Hammond et al. (2012). This model simulates habit formation in the context of food by modeling preference formation in terms of positive or negative feedback about the food most recently consumed. The model is designed to provide insights into how different patterns of exposure to FFVP affect preferences, and how living in a food desert changes the effect of FFVP. We use data on 35,981 students from Arkansas elementary schools (from 2008 to 2016) and information about the commercial food environment in Arkansas communities to populate the model. We find that early FFVP exposure is more beneficial than late exposure conditional on the number of years exposed. We also find that FFVP is more beneficial for children who grow up in environments lacking healthy food.

Income Segregation and Access to Healthy Food.

INTRODUCTION: Differences in diet quality across socioeconomic groups are a key contributor to health gradient. An agent-based model was developed to explore how income segregation affects food access for poor households under idealized circumstances where the poor have the same knowledge of and preferences for healthy food as the nonpoor. METHODS: The agent-based model featured households with heterogeneous incomes and automobile ownership characteristics on the basis of 2016 U.S. Census Bureau data. Households had identical preferences and were perfectly informed about the prices and availability of food products in different grocery stores. The model featured 2 fully informed competing grocery stores that chose their locations, product lines, and prices to maximize profits. The model was simulated for different levels of income segregation. The model in this article was created and analyzed in 2019. RESULTS: With no segregation, the rich and the poor households had comparatively equal access to grocery stores (in terms of travel distance) and healthy food (in terms of availability). With high segregation, poor households were forced to travel farther for groceries and may find healthy food unavailable at the grocery stores closest to their homes. Incentivizing grocery stores to locate equitably would require offering them substantial subsidies. CONCLUSIONS: The model demonstrates that even under idealized conditions of perfect information and fully rational consumers, income segregation leads to adverse consequences for healthy food access by the poor. Agent-based modeling is useful to explore important hypothetical scenarios and should be considered as one of many worthwhile complementary frameworks to study complex topics.