The role of stroke care infrastructure on the effectiveness of a hub-and-spoke telestroke model in South Carolina.

OBJECTIVE: To examine the relationship between stroke care infrastructure and stroke quality-of-care outcomes at 29 spoke hospitals participating in the Medical University of South Carolina (MUSC) hub-and-spoke telestroke network. MATERIALS AND METHODS: Encounter-level data from MUSC's telestroke patient registry were filtered to include encounters during 2015-2022 for patients aged 18 and above with a clinical diagnosis of acute ischemic stroke, and who received intravenous tissue plasminogen activator. Unadjusted and adjusted generalized estimating equations assessed associations between time-related stroke quality-of-care metrics captured during the encounter and the existence of the two components of stroke care infrastructure-stroke coordinators and stroke center certifications-across all hospitals and within hospital subgroups defined by size and rurality. RESULTS: Telestroke encounters at spoke hospitals with stroke coordinators and stroke center certifications were associated with shorter door-to-needle (DTN) times (60.9 min for hospitals with both components and 57.3 min for hospitals with one, vs. 81.2 min for hospitals with neither component, p <.001). Similar patterns were observed for the percentage of encounters with DTN time of ≤60 min (63.8% and 68.9% vs. 32.0%, p <.001) and ≤45 min (34.0% and 38.4% vs. 8.42%, p <.001). Associations were similar for other metrics (e.g., door-to-registration time), and were stronger for smaller (vs. larger) hospitals and rural (vs. urban) hospitals. CONCLUSIONS: Stroke coordinators or stroke center certifications may be important for stroke quality of care, especially at spoke hospitals with limited resources or in rural areas.

Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care.

Importance: Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income. Objective: To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity. Evidence Review: The Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback. Findings: The panel developed a conceptual framework to apply guiding principles across an algorithm's life cycle, centering health and health care equity for patients and communities as the goal, within the wider context of structural racism and discrimination. Multiple stakeholders can mitigate and prevent bias at each phase of the algorithm life cycle, including problem formulation (phase 1); data selection, assessment, and management (phase 2); algorithm development, training, and validation (phase 3); deployment and integration of algorithms in intended settings (phase 4); and algorithm monitoring, maintenance, updating, or deimplementation (phase 5). Five principles should guide these efforts: (1) promote health and health care equity during all phases of the health care algorithm life cycle; (2) ensure health care algorithms and their use are transparent and explainable; (3) authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trustworthiness; (4) explicitly identify health care algorithmic fairness issues and trade-offs; and (5) establish accountability for equity and fairness in outcomes from health care algorithms. Conclusions and Relevance: Multiple stakeholders must partner to create systems, processes, regulations, incentives, standards, and policies to mitigate and prevent algorithmic bias. Reforms should implement guiding principles that support promotion of health and health care equity in all phases of the algorithm life cycle as well as transparency and explainability, authentic community engagement and ethical partnerships, explicit identification of fairness issues and trade-offs, and accountability for equity and fairness.

Medicare Data Linkages for Conducting Patient-Centered Outcomes Research on Economic Outcomes.

BACKGROUND: Medicare patients and other stakeholders often make health care decisions that have economic consequences. Research on economic variables that patients have identified as important is referred to as patient-centered outcomes research (PCOR) and can generate evidence that informs decision-making. Medicare fee-for-service (FFS) claims are widely used for research and are a potentially valuable resource for studying some economic variables, particularly when linked to other datasets. OBJECTIVE: The aim of this study was to identify and assess the characteristics of federally funded administrative and survey data sources that can be linked to Medicare claims for conducting PCOR on some economic outcomes. RESEARCH DESIGN: A targeted internet search was conducted to identify a list of relevant data sources. A technical panel and key informant interviews were used for guidance and feedback. RESULTS: We identified 12 survey and 6 administrative sources of linked data for Medicare FFS beneficiaries. A majority provide longitudinal data and are updated annually. All linked sources provide some data on social determinants of health and health equity-related factors. Fifteen sources capture direct medical costs (beyond Medicare FFS payments); 5 capture indirect costs (eg, lost wages from absenteeism), and 7 capture direct nonmedical costs (eg, transportation). CONCLUSIONS: Linking Medicare FFS claims data to other federally funded data sources can facilitate research on some economic outcomes for PCOR. However, few sources capture direct nonmedical or indirect costs. Expanding linkages to include additional data sources, and reducing barriers to existing data sources, remain important objectives for increasing high-quality, patient-centered economic research.

Federal Data for Conducting Patient-centered Outcomes Research on Economic Outcomes.

BACKGROUND: Patients are increasingly interested in data on the economic burdens and impacts of health care choices; caregivers, employers, and payers are also interested in these costs. Although there have been various federal investments into patient-centered outcomes research (PCOR), an assessment of the coverage and gaps in federally funded data for PCOR economic evaluations has not been produced to date. OBJECTIVES: To classify relevant categories of PCOR economic costs, to assess current federally funded data for coverage of these categories, and to identify gaps for future research and collection. RESEARCH DESIGN: A targeted internet search was conducted to identify a list of relevant outcomes and data sources. The study team assessed data sources for coverage of economic outcomes. A technical panel and key informant interviews were used for evaluation and feedback. RESULTS: Four types of formal health care sector costs, 3 types of informal health care sector costs, and 10 types of non-health care sector costs were identified as relevant for PCOR economic evaluations. Twenty-nine federally funded data sources were identified. Most contained elements on formal costs. Data on informal costs (eg, transportation) were less common, and non-health care sector costs (eg, productivity) were the least common. Most data sources were annual, cross-sectional, nationally representative individual-level surveys. CONCLUSIONS: The existing federal data infrastructure captures many areas of the economic burden of health and health care, but gaps remain. Research from multiple data sources and potential future integrations may offset gaps in individual data sources. Linkages are promising strategies for future research on patient-centered economic outcomes.

Food Skills Education and Low-Income Adults' Healthy Food Choices.

BACKGROUND: The Cooking Matters food skills education program equips low-income families with the skills and knowledge to shop for and cook healthy meals within budget and time constraints. AIMS: To explore whether participation in Cooking Matters is associated with healthier food choices using a 6-item scale, comprised of a variety of food categories. METHODS: Cooking Matters participants (n = 332) and a comparison group (n = 336) completed surveys at baseline, 3-, and 6-month follow-up. RESULTS: Cooking Matters participants experienced greater improvements in healthy choices overall (p < 0.0001) and for each of the six underlying items at 3 month follow-up. Improvements were sustained at 6-month follow-up overall and for all categories, except low-fat milk (p = 0.1168). DISCUSSION: Participation in Cooking Matters was associated with improvements in overall healthy food choices across a variety of food groups and maintained at 6-month follow-up. Enabling healthy food choices is an important step toward improved diet quality.

Sugar-Sweetened Beverage Consumption in Children: The Interplay of Household SNAP and WIC Participation.

INTRODUCTION: Although sugar-sweetened beverage (SSB) consumption is associated with Supplemental Nutrition Assistance Program (SNAP) and Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participation, no national studies have examined the interplay between these programs. This study compares children's sugar-sweetened beverage consumption across households enrolled in one, both, or neither program. METHODS: A total of 4 waves (2009-2010 to 2015-2016) of the National Health and Nutrition Examination Survey were combined to obtain a sample of 4,772 children aged 0-19 years living in households eligible for both SNAP and WIC (households with income ≤130% of the Federal Poverty Level). Children were grouped as living in 4 household types: SNAP only; WIC only; SNAP + WIC; and neither program. Beverages with any added sugars were classified as SSBs. Two-part regression models examined the adjusted association between SSB consumption and program participation. Analyses were conducted in 2020. RESULTS: Compared with the SNAP‒only group, children in all other household types had lower odds of SSB consumption (AOR=0.44, p=0.002 for WIC only; AOR=0.69, p=0.020 for SNAP + WIC; AOR=0.61, p=0.025 for neither program). The lower probability of SSB consumption for children from WIC‒participating households was mostly driven by children aged 0-5 years, with the differences weakening for children aged 6-12 years and completely disappearing for those aged 12-19 years. No significant differences were observed for the amount of added sugar consumed by SSB consumers. CONCLUSIONS: Household WIC participation-whether jointly with SNAP or alone-may confer protection against SSB consumption. Unlike SNAP, WIC, by design, provides participating households with more information and opportunities to access and consume healthier diets. Understanding how SNAP and WIC interact can help policymakers improve the design and nutritional benefit of the U.S. food safety net.

Food Insecurity Among Health Care Workers In The US.

Food insecurity, or the lack of access to an adequate supply of nutritious food, is associated with poor health outcomes including diabetes, heart disease, and depression. Food insecurity research has grown in the past two decades and has spurred efforts in the US health care system to "screen and intervene" for patient food insecurity. Using nationally representative data from the period 2013-18, this study is the first to our knowledge to investigate the prevalence of food insecurity for the health care workforce, an industry that ranges from low-skill, low-wage hourly jobs to highly specialized salaried positions. We found that relative to health diagnosing and treating practitioners, the odds of being food insecure were 5.1 times higher for health care support workers and 2.5 times higher for health technologists and technicians. The health care industry is the largest and fastest-growing US employer, and it is vital that leaders and policy makers address food insecurity among the health care workforce.

Prevalence and Risk Factors for Food Insecurity Among Low-Income US Military Veterans.

OBJECTIVE: Ensuring access to sufficient foods at all times is critical to veterans' health and well-being. Food insecurity has not been well explored in the veteran population. We examined the prevalence and predictors of food insecurity among low-income veterans, because the highest rates of food insecurity are among low-income households. We also examined rates of Supplemental Nutrition Assistance Program (SNAP) participation among subgroups at the highest risk of food insecurity. METHODS: We used univariate analyses and 2011-2017 National Health Interview Survey (NHIS) data on veterans aged ≥21 with family incomes <200% of the federal poverty level to estimate the prevalence of food insecurity. We used bivariate analyses to identify correlates of food insecurity and estimate SNAP participation rates among subgroups of low-income veterans. Percentages were weighted using NHIS survey weights. RESULTS: Of 5146 low-income veterans, 22.5% reported being food insecure in the previous month. Food insecurity was significantly associated with being aged <65 (33.0% aged 45-64 and 29.7% aged 21-44) compared with 15.0% and 6.4% among veterans aged 65-74 and ≥75, respectively (P < .001); unemployed compared with employed or not in the labor force (39.4%, 22.7%, and 20.2%, respectively; P < .001); in fair or poor health compared with good, very good, or excellent heath (31.8% vs 18.2%; P < .001); and having experienced serious psychological distress in the past month (56.3%) compared with not having experienced such distress (19.7%; P < .001). Although overall SNAP participation among low-income veterans was estimated to be 27.0%, participation rates were highest among veterans who had experienced serious psychological distress (44.1%), were unemployed (39.2%), and were renting their home (39.0%). CONCLUSIONS: Some low-income veterans are at greater risk of food insecurity than other veterans. Postseparation programs, civilian support services, and veterans' health providers should be aware of the characteristics that place veterans at highest risk of food insecurity.

Association Between Supplemental Nutrition Assistance Program Participation and Cost-Related Medication Nonadherence Among Older Adults With Diabetes.

Importance: Understanding if the association of social programs with health care access and utilization, especially among older adults with costly chronic medical conditions, can help in improving strategies for self-management of disease. Objective: To examine whether participation in the Supplemental Nutrition Assistance Program (SNAP) is associated with a reduced likelihood of low-income older adults with diabetes (aged ≥65 years) needing to forgo medications because of cost. Design, Setting, and Participants: This repeated cross-sectional, population-based study included 1302 seniors who participated in the National Health Interview Survey from 2013 through 2016. Individuals in the study were diagnosed with diabetes or borderline diabetes, were eligible to receive SNAP benefits, were prescribed medications, and incurred more than zero US dollars in out-of-pocket medical expenses in the past year. The data analysis was performed from October 2017 to April 2018. Exposures: Self-reported participation in SNAP. Main Outcomes and Measures: Cost-related medication nonadherence derived from responses to whether in the past year, older adults with diabetes delayed refilling a prescription, took less medication, and skipped medication doses because of cost. To estimate the association between participation in SNAP and cost-related medication nonadherence, we used 2-stage, regression-adjusted propensity score matching, conditional on sociodemographic and health and health care-related characteristics of individuals. Estimated propensity scores were used to create matched groups of participants in SNAP and eligible nonparticipants. After matching, a fully adjusted weighted model that included all covariates plus food security status was used to estimate the association between SNAP and cost-related medication nonadherence in the matched sample. Results: The final analytic sample before matching included 1385 older adults (448 [32.3%] men, 769 [55.5%] non-Hispanic white, and 628 [45.3%] aged ≥75 years), with 503 of them participating in SNAP (36.3%) and 178 reporting cost-related medication nonadherence (12.9%) in the past year. After matching, 1302 older adults were retained (434 [33.3%] men, 716 [55.0%] non-Hispanic white, and 581 [44.6%] aged ≥75 years); treatment and comparison groups were similar for all characteristics. Participants in SNAP had a moderate decrease in cost-related medication nonadherence compared with eligible nonparticipants (5.3 percentage point reduction; 95% CI, 0.5-10.0 percentage point reduction; P = .03). Similar reductions were observed for subgroups that had prescription drug coverage (5.8 percentage point reduction; 95% CI, 0.6-11.0) and less than $500 in out-of-pocket medical costs in the previous year (6.4 percentage point reduction; 95% CI, 0.8-11.9), but not for older adults lacking prescription coverage or those with higher medical costs. Results remained robust to several sensitivity analyses. Conclusions and Relevance: The findings suggest that participation in SNAP may help improve adherence to treatment regimens among older adults with diabetes. Connecting these individuals with SNAP may be a feasible strategy for improving health outcomes.

Cost-Related Medication Nonadherence for Older Adults Participating in SNAP, 2013-2015.

OBJECTIVES: To estimate the impact of Supplemental Nutrition Assistance Program (SNAP) participation on cost-related medication nonadherence (CRN) for older adults in the United States, with a particular focus on those who are food insecure and those threatened by hunger. METHODS: We used propensity score matching to create matched intervention and comparison groups of SNAP-eligible US adults aged 60 years and older with data from the 2013-2015 National Health Interview Survey. Intervention group participants were identified on the basis of self-reported SNAP participation in the past year. RESULTS: SNAP participants were 4.8 percentage points less likely to engage in CRN than eligible nonparticipants (P < .01). The effect of SNAP is about twice as large for older adults threatened by hunger (9.1 percentage points; P < .01), and considerable even for those who are food insecure (7.4 percentage points; P < .05). CONCLUSIONS: Findings point to a spillover "income effect" as SNAP may help older adults better afford their medications, conceivably by reducing out-of-pocket food expenditures. When prescribing treatment plans, health systems and payers have a vested interest in connecting older patients to SNAP and other resources that may help address barriers to care.