Showing papers by "Seth A. Berkowitz published in 2023"

Evaluation of a Produce Prescription Program for Patients With Diabetes: A Longitudinal Analysis of Glycemic Control

Abstract: OBJECTIVE Produce prescriptions have shown promise in improving diabetes care, although most studies have used small samples or lacked controls. Our objective was to evaluate the impacts of a produce prescription program on glycemic control for patients with diabetes. RESEARCH DESIGN AND METHODS Participants included a nonrandom enrollment of 252 patients with diabetes who received a produce prescription and 534 similar control participants from two clinics in Hartford, Connecticut. The start of the COVID-19 pandemic in March 2020 coincided with program implementation. Produce prescription enrollees received vouchers ($60 per month) for 6 months to purchase produce at grocery retail. Controls received usual care. The primary outcome was change in glycated hemoglobin (HbA1c) between treatment and control at 6 months. Secondary outcomes included 6-month changes in systolic (SBP) and diastolic blood pressure (DBP), BMI, hospitalizations, and emergency department admissions. Longitudinal generalized estimating equation models, weighted with propensity score overlap weights, assessed changes in outcomes over time. RESULTS At 6 months, there was no significant difference in change in HbA1c between treatment and control groups, with a difference of 0.13 percentage points (95% CI −0.05, 0.32). No significant difference was observed for change in SBP (3.85 mmHg; −0.12, 7.82), DBP (−0.82 mmHg; −2.42, 0.79), or BMI (−0.22 kg/m2; −1.83, 1.38). Incidence rate ratios for hospitalizations and emergency department visits were 0.54 (0.14, 1.95) and 0.53 (0.06, 4.72), respectively. CONCLUSIONS A 6-month produce prescription program for patients with diabetes, implemented during the onset of the COVID-19 pandemic, was not associated with improved glycemic control.

Financing Health Care System Interventions Addressing Social Risks.

Abstract: This Viewpoint discusses the benefits and drawbacks of health care involvement in social risk interventions and presents proposals to finance such involvement.

Health Care’s New Emphasis on Social Determinants of Health

Abstract: SummaryThis special double issue of NEJM Catalyst Innovations in Care Delivery, guest edited by Seth A. Berkowitz, MD, MPH, shows how health care organizations are actively addressing the social determinants of health and health-related social needs.

Food Insecurity Was Associated With Greater Family Health Care Expenditures In The US, 2016-17.

Abstract: Food insecurity has been associated with the health care expenditures of individuals, but it can affect the entire family. Evaluating the relationship between food insecurity and family expenditures provides a better understanding of the financial implications of food insecurity interventions. Our primary objective was to evaluate the association between food insecurity in one year (2016) and family health care expenditures-for all members, for children only, and for adults only-in the next year (2017). We also evaluated whether this association varied across types of insurance coverage within families: all private, all public, or mixed (including uninsured). Using nationally representative data, we found that food-insecure families had 20 percent greater total health care expenditures than food-secure families, for an annual difference of $2,456. Food insecurity was associated with greater expenditures across all family insurance patterns, including the 19.1 percent of families with mixed coverage. Our findings suggest that in families with mixed coverage, positive impacts of food insecurity interventions on health care use may accrue to family members other than the targeted beneficiaries and those who have different insurance, benefiting the entire family but potentially discouraging investments on the part of any one payer.

Sample-Specific Debiasing for Better Image-Text Models

Abstract: Self-supervised representation learning on image-text data facilitates crucial medical applications, such as image classification, visual grounding, and cross-modal retrieval. One common approach involves contrasting semantically similar (positive) and dissimilar (negative) pairs of data points. Drawing negative samples uniformly from the training data set introduces false negatives, i.e., samples that are treated as dissimilar but belong to the same class. In healthcare data, the underlying class distribution is nonuniform, implying that false negatives occur at a highly variable rate. To improve the quality of learned representations, we develop a novel approach that corrects for false negatives. Our method can be viewed as a variant of debiased constrastive learning that uses estimated sample-specific class probabilities. We provide theoretical analysis of the objective function and demonstrate the proposed approach on both image and paired image-text data sets. Our experiments demonstrate empirical advantages of sample-specific debiasing.

Diet and Food and Nutrition Insecurity and Cardiometabolic Disease

Abstract: Poor nutrition is the leading cause of poor health, health care spending, and lost productivity in the United States and globally, which acts through cardiometabolic diseases as precursors to cardiovascular disease, cancer, and other conditions. There is great interest in how the social determinants of health (the conditions in which people are born, live, work, develop, and age) impact cardiometabolic disease. Food insecurity is an example of a powerful social determinant of health that impacts health outcomes. Nutrition insecurity, a distinct but related concept to food insecurity, is a direct determinant of health. In this article, we provide an overview of how diet in early life relates to cardiometabolic disease and then continue to focus on the concepts of food insecurity and nutrition insecurity. In the discussions herein we make important distinctions between the concepts of food insecurity and nutrition insecurity and provide a review of their concepts, histories, measurement and assessment devices, trends and prevalence, and links to health and health disparities. The discussions here set the stage for future research and practice to directly address the negative consequences of food and nutrition insecurity.

Health Care Professionals Take Individual and Organizational Responsibility for Addressing Social Needs

Abstract: SummaryA survey of the NEJM Catalyst Insights Council finds strong interest in addressing social determinants of health and health-related social needs, but establishing programs and funding remains difficult.

Comparing per-protocol effect estimates for population health RCTs: A re-analysis of the Feeding America Intervention Trial for Health for Diabetes Mellitus.

Abstract: Journal Article Accepted manuscript Comparing per-protocol effect estimates for population health RCTs: A re-analysis of the Feeding America Intervention Trial for Health for Diabetes Mellitus Get access Catherine X Li, Catherine X Li Department of Epidemiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USASchool of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA Correspondence Address: Catherine X. Li, Department of Epidemiology, Gillings School of Global Public Health, UNC Campus Box 7435, Chapel Hill, NC 27599-7435 (email: Catherine.li@unc.edu) Search for other works by this author on: Oxford Academic PubMed Google Scholar Stephen R Cole, Stephen R Cole Department of Epidemiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar Hilary K Seligman, Hilary K Seligman Division of General Internal Medicine, University of California San Francisco, San Francisco, CA, USACenter for Vulnerable Populations, University of California San Francisco, San Francisco, CA, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar Seth A Berkowitz Seth A Berkowitz Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USADivision of General Medicine and Clinical Epidemiology, Department of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar American Journal of Epidemiology, kwad156, https://doi.org/10.1093/aje/kwad156 Published: 07 July 2023 Article history Received: 03 June 2022 Revision received: 22 April 2023 Published: 07 July 2023

Gaps in the welfare state: A role-based model of poverty risk in the U.S.

Abstract: Background Research clearly demonstrates that income matters greatly to health. However, income distribution and its relationship to poverty risk is often misunderstood. Methods We provide a structural account of income distribution and poverty risk in the U.S., rooted in the ‘roles’ that individuals inhabit with relation to the ‘factor payment system’ (market distribution of income to individuals through wages and asset ownership). Principal roles are child, older adult, and, among working-age adults, disabled individual, student, unemployed individual, caregiver, or paid laborer. Moreover, the roles of other members of an individual’s household also influence an individual’s income level. This account implies that 1) roles other than paid laborer will be associated with greater poverty risk, 2) household composition will be associated with poverty risk, and 3) income support policies for those not able to engage in paid labor are critical for avoiding poverty. We test hypotheses implied by this account using 2019 and 2022 U.S. Census Current Population Survey data. The exposure variables in our analyses relate to roles and household composition. The outcomes relate to income and poverty risk. Results In 2019, 40.1 million individuals (12.7% of the population) experienced poverty under the U.S. Census’ Supplemental Poverty Measure. All roles other than paid laborer were associated with greater poverty risk (p < .001 for all comparisons). Household composition, particularly more children and disabled working-age adults, and fewer paid laborers, was also associated with greater poverty risk (p < .001 for all comparisons). Five key policy areas—child benefits, older-age pensions, disability and sickness insurance, unemployment insurance, and out-of-pocket healthcare spending—represented gaps in the welfare state strongly associated with poverty risk. Conclusions The role one inhabits and household composition are associated with poverty risk. This understanding of income distribution and poverty risk may be useful for social policy.

Permanent Supportive Housing Receipt and Health Care Use Among Adults With Disabilities.

Abstract: This study assessed whether permanent supportive housing (PSH) participation is associated with health service use among a population of adults with disabilities, including people transitioning into PSH from community and institutional settings. Our primary data sources were 2014 to 2018 secondary data from a PSH program in North Carolina linked to Medicaid claims. We used propensity score weighting to estimate the average treatment effect on the treated of PSH participation. All models were stratified by whether individuals were in institutional or community settings prior to PSH. In weighted analyses, among individuals who were institutionalized prior to PSH, PSH participation was associated with greater hospitalizations and emergency department (ED) visits and fewer primary care visits during the follow-up period, compared with similar individuals who largely remained institutionalized. Individuals who entered PSH from community settings did not have significantly different health service use from similar comparison group members during the 12-month follow-up period.

Potential gaps in income support policies for those in poor health: The case of the earned income tax credit—A cross sectional analysis

Abstract: The federal Earned Income Tax Credit (EITC) is the primary income support program for low-income workers in the U.S., but its design may hinder its effectiveness when poor health limits, but does not preclude, work. Cross-sectional analysis of nationally-representative U.S. Census Current Population Survey (CPS) data covering 2019. Working-age adults eligible to receive federal EITC were included in this study. Poor health, as indicated by self-report of at least one problem with hearing, vision, cognitive function, mobility, dressing and bathing, or independence, was the exposure. The main outcome was federal EITC benefit category, categorized as no benefit, phase-in (income too low for the maximum benefit), plateau (maximum benefit), phase-out (income above threshold for maximum benefit), or earnings too high to receive any benefit. We estimated EITC benefit category probabilities by health status using multinomial logistic regression. We further examined whether other government benefits provided additional income support to those in poor health. 41,659 participants (representing 87.1 million individuals) were included. 2,724 participants (representing 5.6 million individuals) reported poor health. In analyses standardized over age, gender, race, and ethnicity, those in poor health, compared with those not in poor health, were more likely to be in the no benefit (2.40% vs. 0.30%, risk difference 2.10 percentage points [95%CI 1.75 to 2.46 percentage points]), and phase-in (9.28% vs. 2.74%, risk difference 6.54 percentage points [95%CI 5.82 to 7.26 percentage points]) categories. Differences in resources by health status persisted even after accounting for other government benefits. EITC program design creates an important gap in income support for those for whom poor health limits work, which is not closed by other programs. Filling this gap is an important public health goal.

Estimated Costs of Intervening in Health-Related Social Needs Detected in Primary Care.

Abstract: Importance Health-related social needs are increasingly being screened for in primary care practices, but it remains unclear how much additional financing is required to address those needs to improve health outcomes. Objective To estimate the cost of implementing evidence-based interventions to address social needs identified in primary care practices. Design, Setting, and Participants A decision analytical microsimulation of patients seen in primary care practices, using data on social needs from the National Center for Health Statistics from 2015 through 2018 (N = 19 225) was conducted. Primary care practices were categorized as federally qualified health centers (FQHCs), non-FQHC urban practices in high-poverty areas, non-FQHC rural practices in high-poverty areas, and practices in lower-poverty areas. Data analysis was performed from March 3 to December 16, 2022. Intervention Simulated evidence-based interventions of primary care-based screening and referral protocols, food assistance, housing programs, nonemergency medical transportation, and community-based care coordination. Main Outcomes and Measures The primary outcome was per-person per-month cost of interventions. Intervention costs that have existing federally funded financing mechanisms (eg, the Supplemental Nutrition Assistance Program) and costs without such an existing mechanism were tabulated. Results Of the population included in the analysis, the mean (SD) age was 34.4 (25.9) years, and 54.3% were female. Among people with food and housing needs, most were program eligible for federally funded programs, but had low enrollment (eg, due to inadequate program capacity), with 78.0% of people with housing needs being program eligible vs 24.0% enrolled, and 95.6% of people with food needs being program eligible vs 70.2% enrolled. Among those with transportation insecurity and care coordination needs, eligibility criteria limited enrollment (26.3% of those in need being program eligible for transportation programs, and 5.7% of those in need being program eligible for care coordination programs). The cost of providing evidence-based interventions for these 4 domains averaged $60 (95% CI, $55-$65) per member per month (including approximately $5 for screening and referral management in clinics), of which $27 (95% CI, $24-$31) (45.8%) was federally funded. While disproportionate funding was available to populations seen at FQHCs, populations seen at non-FQHC practices in high-poverty areas had larger funding gaps (intervention costs not borne by existing federal funding mechanisms). Conclusions and Relevance In this decision analytical microsimulation study, food and housing interventions were limited by low enrollment among eligible people, whereas transportation and care coordination interventions were more limited by narrow eligibility criteria. Screening and referral management in primary care was a small expenditure relative to the cost of interventions to address social needs, and just under half of the costs of interventions were covered by existing federal funding mechanisms. These findings suggest that many resources are necessary to address social needs that fall largely outside of existing federal financing mechanisms.