Measuring social determinants of health in the All of Us Research Program.

To accelerate medical breakthroughs, the All of Us Research Program aims to collect data from over one million participants. This report outlines processes used to construct the All of Us Social Determinants of Health (SDOH) survey and presents the psychometric characteristics of SDOH survey measures in All of Us. A consensus process was used to select SDOH measures, prioritizing concepts validated in diverse populations and other national cohort surveys. Survey item non-response was calculated, and Cronbach's alpha was used to analyze psychometric properties of scales. Multivariable logistic regression models were used to examine associations between demographic categories and item non-response. Twenty-nine percent (N = 117,783) of eligible All of Us participants submitted SDOH survey data for these analyses. Most scales had less than 5% incalculable scores due to item non-response. Patterns of item non-response were seen by racial identity, educational attainment, income level, survey language, and age. Internal consistency reliability was greater than 0.80 for almost all scales and most demographic groups. The SDOH survey demonstrated good to excellent reliability across several measures and within multiple populations underrepresented in biomedical research. Bias due to survey non-response and item non-response will be monitored and addressed as the survey is fielded more completely.

Association of food insecurity with changes in diet quality, weight, and glycemia over two years in adults with prediabetes and type 2 diabetes on medicaid.

Little is known about longitudinal associations between food insecurity (FI) and diet, weight, and glycemia in people with prediabetes and type 2 diabetes (T2D). In a secondary analysis of Medicaid-enrolled health center patients with prediabetes or T2D in Boston, Massachusetts (N = 188), we examined associations between food security (FS) and measures of diet quality, weight, and hyperglycemia. FS (10-item USDA FS module) was ascertained at baseline, 1-year, and 2-year follow-up and categorized as persistently secure, intermittently insecure, or persistently insecure. Associations between FS category and changes in Healthy Eating Index-2020 (HEI-20), body mass index (BMI), and hemoglobin A1c (A1c) from baseline to year 2 were assessed using multivariate generalized linear models. Participants had median (p25, p75) age of 52 (42, 57); 71.8% were female and 62.8% Hispanic. Over follow-up, 32.4% were persistently food secure, 33.0% intermittently insecure, and 34.5% persistently insecure. Baseline mean (SD) HEI-20, BMI, and A1c were 55.8 (14.5), 35.9 (8.7) kg/m2, 7.1% (1.6) and did not differ by FS category. FS category was not associated with changes in HEI-20, BMI, and A1c at 2 years (all p > 0.05). Results suggest that Medicaid-enrolled adults with prediabetes or T2D, regardless of FS status, would benefit from dietary and weight management interventions.

Screening for Financial Hardship: Comparing Patient Survey Responses Using Two Different Screening Tools.

BACKGROUND: Healthcare delivery organizations are increasingly screening patients for social risks using tools that vary in content and length. OBJECTIVES: To compare two screening tools both containing questions related to financial hardship. DESIGN: Cross-sectional survey. PARTICIPANTS: Convenience sample of adult patients (n = 471) in three primary care clinics. MAIN MEASURES: Participants randomly assigned to self-complete either: (1) a screening tool developed by the Centers for Medicare & Medicaid Services (CMS) consisting of six questions on financial hardship (housing stability, housing quality, food security, transportation security, utilities security); or (2) social and behavioral risk measures recommended by the National Academy of Medicine (NAM), including one question on financial hardship (financial strain). We compared patient acceptability of screening, positive screening rates for financial hardship, patient interest in assistance, and self-rated health. RESULTS: Ninety-one percent of eligible/interested patients completed the relevant survey questions to be included in the study (N = 471/516). Patient acceptability was high for both tools, though more participants reported screening was appropriate when answering the CMS versus NAM questions (87% vs. 79%, p = 0.02). Of respondents completing the CMS tool, 57% (132/232) reported at least one type of financial hardship; on the NAM survey, 52% (125/239) reported financial hardship (p = 0.36). Nearly twice as many respondents indicated interest in assistance related to financial hardship after completing items on the CMS tool than on the NAM question (39% vs. 21%, p < 0.01). CONCLUSIONS: Patients reported high acceptability of both social risk assessment tools. While rates of positive screens for financial hardship were similar across the two measures, more patients indicated interest in assistance after answering questions about financial hardship on the CMS tool. This might be because the screening questions on the CMS tool help patients to appreciate the types of assistance related to financial hardship that may be available after screening. Future research should assess the validity and comparative validity of individual measures and measure sets. Tool selection should be based on setting and population served, screening goals, and resources available.

Assessment of the Massachusetts Flexible Services Program to Address Food and Housing Insecurity in a Medicaid Accountable Care Organization.

Importance: Health systems are increasingly addressing health-related social needs. The Massachusetts Flexible Services program (Flex) is a 3-year pilot program to address food insecurity and housing insecurity by connecting Medicaid accountable care organization (ACO) enrollees to community resources. Objective: To understand barriers and facilitators of Flex implementation in 1 Medicaid ACO during the first 17 months of the program. Design, Setting, and Participants: This mixed-methods qualitative evaluation study from March 2020 to July 2021 used the Reach, Efficacy, Adoption, Implementation, Maintenance/Practical, Robust Implementation, and Sustainability Model (RE-AIM/PRISM) framework. Two Mass General Brigham (MGB) hospitals and affiliated community health centers were included in the analysis. Quantitative data included all MGB Medicaid ACO enrollees. Qualitative interviews were conducted with 15 members of ACO staff and 17 Flex enrollees. Main Outcomes and Measures: Reach was assessed by the proportion of ACO enrollees who completed annual social needs screening (eg, food insecurity and housing insecurity) and the proportion and demographics of Flex enrollees. Qualitative interviews examined other RE-AIM/PRISM constructs (eg, implementation challenges, facilitators, and perceived effectiveness). Results: Of 67 098 Medicaid ACO enrollees from March 2020 to July 2021 (mean [SD] age, 28.8 [18.7] years), 38 442 (57.3%) completed at least 1 social needs screening; 10 730 (16.0%) screened positive for food insecurity, and 7401 (11.0%) screened positive for housing insecurity. There were 658 (1.6%) adults (mean [SD] age, 46.6 [11.8] years) and 173 (0.7%) children (<21 years; mean [SD] age, 10.1 [5.5]) enrolled in Flex; of these 831 people, 613 (73.8%) were female, 444 (53.4%) were Hispanic/Latinx, and 172 (20.7%) were Black. Most Flex enrollees (584 [88.8%] adults; 143 [82.7%] children) received the intended nutrition or housing services. Implementation challenges identified by staff interviewed included administrative burden, coordination with community organizations, data-sharing and information-sharing, and COVID-19 factors (eg, reduced clinical visits). Implementation facilitators included administrative funding for enrollment staff, bidirectional communication with community partners, adaptive strategies to identify eligible patients, and raising clinician awareness of Flex. In Flex enrollee interviews, those receiving nutrition services reported increased healthy eating and food security; they also reported higher program satisfaction than Flex enrollees receiving housing services. Enrollees who received nutrition services that allowed for selecting food based on preferences reported higher satisfaction than those not able to select food. Conclusions and Relevance: This mixed-methods qualitative evaluation study found that to improve implementation, Medicaid and health system programs that address social needs may benefit from providing funding for administrative costs, developing bidirectional data-sharing platforms, and tailoring support to patient preferences.

Food Insecurity and Diet Quality Among Adults on Medicaid With and Without a Mental Illness Diagnosis.

BACKGROUND: Adults with mental illnesses are more likely to have low income and diet-related chronic diseases. OBJECTIVE: This study examined associations of mental illness diagnosis status with food insecurity and diet quality and whether the relationship between food security status and diet quality differed by mental illness diagnosis status in adult Medicaid beneficiaries. DESIGN: This was a secondary cross-sectional analysis of baseline (2019-2020) data collected as part of the LiveWell study, a longitudinal study evaluating a Medicaid food and housing program. PARTICIPANTS/SETTING: Participants were 846 adult Medicaid beneficiaries from an eastern Massachusetts health system. MAIN OUTCOME MEASURES: Food security was measured with the 10-item US Adult Food Security survey module (0 = high food security, 1-2 = marginal food security, 3-10 = low/very low food security). Mental illness diagnoses included health record-documented anxiety, depression, or serious mental illness (eg, schizophrenia, bipolar disorder). Healthy Eating Index (HEI-2015) scores were calculated from 24-hour dietary recalls. STATISTICAL ANALYSES: Multivariable regression analyses adjusted for demographics, income, and survey date. RESULTS: Participants' mean (standard deviation) age was 43.1 (11.3) years, and 75% were female, 54% Hispanic, 33% non-Hispanic White, and 9% non-Hispanic Black. Fewer than half (43%) of participants reported high food security, with almost one third (32%) reporting low or very low food security. The 341 (40%) participants with one or more mental illness diagnosis had greater odds of low/very low food security (adjusted odds ratio [OR], 1.94; 95% confidence interval [CI], 1.38-2.70) and had similar mean HEI-2015 scores (53.1 vs 56.0; P = 0.12) compared with participants with no mental illness diagnosis. Mean adjusted HEI-2015 scores did not significantly differ by high vs low/very low food security for those without a mental illness diagnosis (57.9 vs 54.9; P = 0.052) or those with a mental illness diagnosis (53.0 vs 52.9; P = 0.99). CONCLUSION: In a cohort of adults with Medicaid, those with mental illness diagnoses had higher odds of experiencing food insecurity. Overall, diet quality among adults in this sample was low but did not differ by mental illness diagnosis or food security status. These results highlight the importance of augmenting efforts to improve both food security and diet quality among all Medicaid participants.

Racial and Ethnic Disparities in Opioid Access and Urine Drug Screening Among Older Patients With Poor-Prognosis Cancer Near the End of Life.

PURPOSE: To characterize racial and ethnic disparities and trends in opioid access and urine drug screening (UDS) among patients dying of cancer, and to explore potential mechanisms. METHODS: Among 318,549 non-Hispanic White (White), Black, and Hispanic Medicare decedents older than 65 years with poor-prognosis cancers, we examined 2007-2019 trends in opioid prescription fills and potency (morphine milligram equivalents [MMEs] per day [MMEDs]) near the end of life (EOL), defined as 30 days before death or hospice enrollment. We estimated the effects of race and ethnicity on opioid access, controlling for demographic and clinical factors. Models were further adjusted for socioeconomic factors including dual-eligibility status, community-level deprivation, and rurality. We similarly explored disparities in UDS. RESULTS: Between 2007 and 2019, White, Black, and Hispanic decedents experienced steady declines in EOL opioid access and rapid expansion of UDS. Compared with White patients, Black and Hispanic patients were less likely to receive any opioid (Black, -4.3 percentage points, 95% CI, -4.8 to -3.6; Hispanic, -3.6 percentage points, 95% CI, -4.4 to -2.9) and long-acting opioids (Black, -3.1 percentage points, 95% CI, -3.6 to -2.8; Hispanic, -2.2 percentage points, 95% CI, -2.7 to -1.7). They also received lower daily doses (Black, -10.5 MMED, 95% CI, -12.8 to -8.2; Hispanic, -9.1 MMED, 95% CI, -12.1 to -6.1) and lower total doses (Black, -210 MMEs, 95% CI, -293 to -207; Hispanic, -179 MMEs, 95% CI, -217 to -142); Black patients were also more likely to undergo UDS (0.5 percentage points; 95% CI, 0.3 to 0.8). Disparities in EOL opioid access and UDS disproportionately affected Black men. Adjustment for socioeconomic factors did not attenuate the EOL opioid access disparities. CONCLUSION: There are substantial and persistent racial and ethnic inequities in opioid access among older patients dying of cancer, which are not mediated by socioeconomic variables.

Achieving a Representative Sample of Asian Americans in Biomedical Research Through Community-Based Approaches: Comparing Demographic Data in the All of Us Research Program With the American Community Survey.

BACKGROUND: Underrepresented persons are often not included in biomedical research. It is unknown if the general Asian American population is being represented in All of Us. The purpose of this study was to compare the Asian demographic data in the All of Us cohort with the Asian nationally representative data from the American Community Survey. METHOD: Demographic characteristics and health literacy of Asians in All of Us were examined. Findings were qualitatively compared with the Asian data in the 2019 American Community Survey 1-year estimate. RESULTS: Compared with the national composition of Asians, less All of Us participants were born outside the United States (64% vs 79%), were younger, and had higher levels of education (76% vs 52%). Over 60% of All of Us participants reported high levels of health literacy. CONCLUSION: This study had implications for the development of strategies that ensure diverse populations are represented in biomedical research.

Effects of social support on depression risk during the COVID-19 pandemic: What support types and for whom?

Background: Rates of depression have increased worldwide during the COVID-19 pandemic. One known protective factor for depression is social support, but more work is needed to quantify the extent to which social support could reduce depression risk during a global crisis, and specifically to identify which types of support are most helpful, and who might benefit most. Methods: Data were obtained from participants in the All of Us Research Program who responded to the COVID-19 Participant Experience (COPE) survey administered monthly from May 2020 to July 2020 (N=69,066, 66% female). Social support was assessed using 10 items measuring emotional/informational support (e.g., someone to confide in or talk to about yourself or your problems), positive social interaction support (e.g., someone to do things with to help you get your mind off things), and tangible support (e.g., someone to help with daily chores if sick). Elevated depression symptoms were defined based on having a moderate-to-severe (≥10) score on the Patient Health Questionnaire (PHQ-9). Mixed-effects logistic regression models were used to test associations across time between overall social support and its subtypes with depression, adjusting for age, sex, race, ethnicity, and socioeconomic factors. We then assessed interactions between social support and potential effect modifiers: age, sex, pre-pandemic mood disorder, and pandemic-related stressors (e.g., financial insecurity). Results: Approximately 16% of the sample experienced elevated depressive symptoms. Overall social support was associated with significantly reduced odds of depression (adjusted odds ratio, aOR [95% CI]=0.44 [0.42-0.45]). Among subtypes, emotional/informational support (aOR=0.42 [0.41-0.43]) and positive social interactions (aOR=0.43 [0.41-0.44]) showed the largest protective associations with depression, followed by tangible support (aOR=0.63 [0.61-0.65]). Sex, age, and pandemic-related financial stressors were statistically significant modifiers of the association between social support and depression. Conclusions: Individuals reporting higher levels of social support were at reduced risk of depression during the early COVID-19 pandemic. The perceived availability of emotional support and positive social interactions, more so than tangible support, was key. Individuals more vulnerable to depression (e.g., women, younger individuals, and those experiencing financial stressors) may particularly benefit from enhanced social support, supporting a precision prevention approach.

Communicating to Engage: An Improvisational Theater-Based Communication Training Designed to Support Community-Academic Partnership Development.

PROBLEM: The potential for community-engaged research to address health inequity requires deliberate effort to create trusting and equitable community-academic partnerships. A lack of evidence-based opportunities for cultivating such partnerships remains a barrier. APPROACH: In 2017 and 2018, the authors designed, facilitated, and evaluated a mixed stakeholder training, Communicating to Engage, at 2 urban academic medical centers involved in the All of Us research program, Boston Medical Center and Mass General Brigham. The goal was to bring together researchers and community members to develop communication skills through improvisational theater-based co-learning. The curriculum was inspired by several evidence-based learning frameworks including community-based participatory research principles and improvisational theater techniques. A self-administered survey completed before and after the training session measured participants' communication skills using the Self-Perceived Communication Competence Scale (SPCCS) and comfort with specific communication styles as outlined in the program's training objectives. Paired t tests were used to measure changes in scaled responses among combined participants and separately among self-identified community members and researchers. OUTCOMES: Sixty-nine total participants across 6 workshops completed training evaluations. Overall, pre-post survey analysis demonstrated significant mean score improvement for both the SPCCS and comfort with specific communication styles. In stratified analysis, both community members (n = 26) and researchers (n = 38) reported significant improvement in scores related to comfort with specific communication styles. Only researchers, but not community members, had significant improvement in SPCCS scores. NEXT STEPS: The Communicating to Engage program brought community and researcher stakeholders together and demonstrated improvement in self-perceived communication styles, yet researcher participants benefited more than community participants. Future innovation is necessary to further target community stakeholder communication training needs. Mixed stakeholder improvisational theater-based learning provides deliberate opportunities to build new community-academic partnerships that may enhance health equity initiatives.

Health Care Equity in the Use of Advanced Analytics and Artificial Intelligence Technologies in Primary Care.

The integration of advanced analytics and artificial intelligence (AI) technologies into the practice of medicine holds much promise. Yet, the opportunity to leverage these tools carries with it an equal responsibility to ensure that principles of equity are incorporated into their implementation and use. Without such efforts, tools will potentially reflect the myriad of ways in which data, algorithmic, and analytic biases can be produced, with the potential to widen inequities by race, ethnicity, gender, and other sociodemographic factors implicated in disparate health outcomes. We propose a set of strategic assertions to examine before, during, and after adoption of these technologies in order to facilitate healthcare equity across all patient population groups. The purpose is to enable generalists to promote engagement with technology companies and co-create, promote, or support innovation and insights that can potentially inform decision-making and health care equity.

Addressing Social Determinants of Health Identified by Systematic Screening in a Medicaid Accountable Care Organization: A Qualitative Study.

INTRODUCTION/OBJECTIVES: Systematic screening for social determinants of health (SDOH), such as food and housing insecurity, is increasingly implemented in primary care, particularly in the context of Accountable Care Organizations (ACO). Despite the importance of developing effective systems for SDOH resource linkage, there is limited research examining these processes. The objective of the study was to explore facilitators and barriers to addressing SDOH identified by systematic screening in a healthcare system participating in a Medicaid ACO. METHODS: This qualitative case study took place between January and March 2020. Semi-structured interviews were conducted with fifteen staff (8 community resource staff and 7 managers) from community health centers and hospitals affiliated with a large healthcare system. Interviews were transcribed, coded, and analyzed using the Framework Method. RESULTS: Facilitators for addressing SDOH included maintaining updated resource lists, collaborating with community organizations, having leadership buy-in, and developing a trusting relationship with patients. Barriers to addressing SDOH included high caseloads, time constraints, inefficiencies in tracking, lack of community resources, and several specific patient characteristics. Further, resource staff expressed distress associated with having to communicate to patients that they were unable to address certain needs. CONCLUSIONS: Health system, community, and individual-level facilitators and barriers should be considered when developing programs for addressing SDOH. Specifically, the psychological burden on resource staff is an important and underappreciated factor that could impact patient care and lead to staff burnout.

Predicting Self-Rated Health Across the Life Course: Health Equity Insights from Machine Learning Models.

BACKGROUND: Self-rated health is a strong predictor of mortality and morbidity. Machine learning techniques may provide insights into which of the multifaceted contributors to self-rated health are key drivers in diverse groups. OBJECTIVE: We used machine learning algorithms to predict self-rated health in diverse groups in the Behavioral Risk Factor Surveillance System (BRFSS), to understand how machine learning algorithms might be used explicitly to examine drivers of self-rated health in diverse populations. DESIGN: We applied three common machine learning algorithms to predict self-rated health in the 2017 BRFSS survey, stratified by age, race/ethnicity, and sex. We replicated our process in the 2016 BRFSS survey. PARTICIPANTS: We analyzed data from 449,492 adult participants of the 2017 BRFSS survey. MAIN MEASURES: We examined area under the curve (AUC) statistics to examine model fit within each group. We used traditional logistic regression to predict self-rated health associated with features identified by machine learning models. KEY RESULTS: Each algorithm, regularized logistic regression (AUC: 0.81), random forest (AUC: 0.80), and support vector machine (AUC: 0.81), provided good model fit in the BRFSS. Predictors of self-rated health were similar by sex and race/ethnicity but differed by age. Socioeconomic features were prominent predictors of self-rated health in mid-life age groups. Income [OR: 1.70 (95% CI: 1.62-1.80)], education [OR: 2.02 (95% CI: 1.89, 2.16)], physical activity [OR: 1.52 (95% CI: 1.46-1.58)], depression [OR: 0.66 (95% CI: 0.63-0.68)], difficulty concentrating [OR: 0.62 (95% CI: 0.58-0.66)], and hypertension [OR: 0.59 (95% CI: 0.57-0.61)] all predicted the odds of excellent or very good self-rated health. CONCLUSIONS: Our analysis of BRFSS data show social determinants of health are prominent predictors of self-rated health in mid-life. Our work may demonstrate promising practices for using machine learning to advance health equity.

Assessment of Social Risk Factors and Interest in Receiving Health Care-Based Social Assistance Among Adult Patients and Adult Caregivers of Pediatric Patients.

Importance: Health care organizations are increasingly incorporating social risk screening into patient care. Studies have reported wide variations in patients' interest in receiving health care-based assistance for identified social risks. However, no study to date has examined the factors associated with patients' interest in receiving assistance, including whether interest in receiving assistance varies based on specific patient demographic characteristics. Targeted research on this topic could improve the success of health care-based programs that offer social care services. Objective: To identify participant characteristics associated with interest in receiving health care-based social risk assistance. Design, Setting, and Participants: This cross-sectional study was conducted in 7 primary care clinics and 4 emergency departments in 9 US states between July 2, 2018, and February 13, 2019. A convenience sample of adult patients and adult caregivers of pediatric patients completed a screening survey that measured social risk factors and participants' interest in receiving assistance for identified social risks. Participants were randomly selected to receive 1 of 2 versions of the survey, which differed based on the order in which questions about social risks and interest in receiving assistance were presented. Multivariable logistic regression analyses were used to evaluate the associations between covariates and participants' interest in receiving assistance, stratified by social risk screening results. Data were analyzed from September 8, 2019, to July 30, 2020. Exposures: Social risk screening questions assessed risk factors comprising housing, food, transportation, utilities, and exposure to interpersonal violence. Additional questions assessed participants' interest in receiving assistance and their perspectives on health care-based social risk screening. Main Outcomes and Measures: Participant interest in receiving health care-based social risk assistance. Results: A total of 1021 adult participants with complete survey responses were included in the analysis. Of those, 709 of 1004 participants (70.6%) were female, and 544 of 1007 participants (54.0%) were aged 18 to 44 years. Overall, 353 of 662 participants (53.3%) with positive screening results for 1 or more social risk factors were interested in receiving assistance, whereas 31 of 359 participants (8.6%) with negative screening results for all social risks were interested in receiving assistance. Participants with positive screening results for 1 or more social risk factors had a higher likelihood of being interested in receiving assistance if they answered the question about interest in receiving assistance before they answered the questions about social risk factors (adjusted odds ratio [aOR], 1.48; 95% CI, 1.05-2.07), had positive screening results for a higher number of social risk factors (aOR, 2.40; 95% CI, 1.68-3.42), reported lower household income levels (aOR, 7.78; 95% CI, 2.96-20.44), or self-identified as having non-Hispanic Black ancestry (aOR, 2.22; 95% CI, 1.37-3.60). Among those with negative screening results for all social risk factors, the interest in receiving assistance was higher if the participants reported lower household income levels (aOR, 12.38; 95% CI, 2.94-52.15), previous exposure to health care-based social risk screening (aOR, 2.35; 95% CI, 1.47-3.74), higher perceived appropriateness of social risk screening (aOR, 3.69; 95% CI, 1.08-12.55), or worse health status (aOR, 4.22; 95% CI, 1.09-16.31). Conclusions and Relevance: In this study, multiple factors were associated with participants' interest in receiving social risk assistance. These findings may have implications for how and when social risk assistance is offered to patients. As the health care system's role in addressing social risk factors evolves, an understanding of patients' perspectives regarding screening and their interest in receiving assistance may be important to implementing patient-centered interventions.

Pervasive Discrimination and Allostatic Load in African American and White Adults.

OBJECTIVE: This study aimed to examine associations among race, the accumulation of multiple forms of discriminatory experiences (i.e., "pervasive discrimination"), and allostatic load (AL) in African Americans and whites in midlife. METHODS: Using data collected in 2004 to 2006 from 226 African American and 978 white adults (57% female; mean [SD] age = 54.7 [0.11] years) in the Midlife in the United States II Biomarker Project, a pervasive discrimination score was created by combining three discrimination scales, and an AL score was created based on 24 biomarkers representing seven physiological systems. Linear regression models were conducted to examine the association between pervasive discrimination and AL, adjusting for demographics and medical, behavioral, and personality covariates. A race by pervasive discrimination interaction was also examined to determine whether associations varied by race. RESULTS: African Americans had higher pervasive discrimination and AL scores than did whites. In models adjusted for demographics, socioeconomic status, medications, health behaviors, neuroticism, and negative affect, a pervasive discrimination score of 2 versus 0 was associated with a greater AL score (b = 0.30, SE = 0.07, p < .001). Although associations seemed to be stronger among African Americans as compared with whites, associations did not statistically differ by race. CONCLUSIONS: More pervasive discrimination was related to greater multisystemic physiological dysregulation in a cohort of African American and white adults. Measuring discrimination by combining multiple forms of discriminatory experiences may be important for studying the health effects of discrimination.

Financial Stress and Risk of Coronary Heart Disease in the Jackson Heart Study.

INTRODUCTION: Financial hardship is associated with coronary heart disease risk factors, and may disproportionately affect some African American groups. This study examines whether stress because of financial hardship is associated with incident coronary heart disease in African Americans. METHODS: The Jackson Heart Study is a longitudinal cohort study of cardiovascular disease risks in African Americans in the Jackson, Mississippi metropolitan statistical area. Participant enrollment began in 2000. Analyses were performed in 2017 and included adjudicated endpoints through December 2012. Financial stress was assessed from the Jackson Heart Study Weekly Stress Inventory and categorized into four levels: (1) did not experience financial stress, (2) no stress, (3) mild stress, and (4) moderate to high stress. Incident coronary heart disease was defined as the first event of definite or probable myocardial infarction, definite fatal myocardial infarction, definite fatal coronary heart disease, or cardiac procedure. There were 2,256 individuals in this analysis. RESULTS: Participants with moderate to high (versus no) financial stress were more likely to have incident coronary heart disease events after controlling for demographics, SES, access to care, and traditional clinical risk factors (hazard ratio=2.42, 95% CI=1.13, 5.17). The association between financial stress and coronary heart disease was no longer statistically significant in a model adjusting for three specific risk factors: depression, smoking status, and diabetes (hazard ratio=1.99, 95% CI=0.91, 4.39). CONCLUSIONS: Financial stress may be an unrecognized risk factor for coronary heart disease for African Americans. Additional research should examine these associations in intervention studies that address perceived stress, in addition to other coronary heart disease risk factors, in patients experiencing financial stress.

Diffusion of digital breast tomosynthesis among women in primary care: associations with insurance type.

Digital breast tomosynthesis (DBT) has shown potential to improve breast cancer screening and diagnosis compared to digital mammography (DM). The FDA approved DBT use in conjunction with conventional DM in 2011, but coverage was approved by CMS recently in 2015. Given changes in coverage policies, it is important to monitor diffusion of DBT by insurance type. This study examined DBT trends and estimated associations with insurance type. From June 2011 to September 2014, DBT use in 22 primary care centers in the Dartmouth -Brigham and Women's Hospital Population-based Research Optimizing Screening through Personalized Regimens research center (PROSPR) was examined among women aged 40-89. A longitudinal repeated measures analysis estimated the proportion of DBT performed for screening or diagnostic indications over time and by insurance type. During the study period, 93,182 mammograms were performed on 48,234 women. Of these exams, 16,506 DBT tests were performed for screening (18.1%) and 2537 were performed for diagnosis (15.7%). Between 2011 and 2014, DBT utilization increased in all insurance groups. However, by the latest observed period, screening DBT was used more frequently under private insurance (43.4%) than Medicaid (36.2%), Medicare (37.8%), other (38.6%), or no insurance (32.9%; P < 0.0001). No sustained differences in use of DBT for diagnostic testing were seen by insurance type. DBT is increasingly used for breast cancer screening and diagnosis. Use of screening DBT may be associated with insurance type. Surveillance is required to ensure that disparities in breast cancer screening are minimized as DBT becomes more widely available.

Low-Value Medical Services in the Safety-Net Population.

Importance: National patterns of low-value and high-value care delivered to patients without insurance or with Medicaid could inform public policy but have not been previously examined. Objective: To measure rates of low-value care and high-value care received by patients without insurance or with Medicaid, compared with privately insured patients, and provided by safety-net physicians vs non-safety-net physicians. Design, Setting, and Participants: This multiyear cross-sectional observational study included all patients ages 18 to 64 years from the National Ambulatory Medical Care Survey (2005-2013) and the National Hospital Ambulatory Medical Care Survey (2005-2011) eligible for any of the 21 previously defined low-value or high-value care measures. All measures were analyzed with multivariable logistic regression and adjusted for patient and physician characteristics. Exposures: Comparison of patients by insurance status (uninsured/Medicaid vs privately insured) and safety-net physicians (seeing >25% uninsured/Medicaid patients) vs non-safety-net physicians (seeing 1%-10%). Main Outcomes and Measures: Delivery of 9 low-value or 12 high-value care measures, based on previous research definitions, and composite measures for any high-value or low-value care delivery during an office visit. Results: Overall, 193 062 office visits were eligible for at least 1 measure. Mean (95% CI) age for privately insured patients (n = 94 707) was 44.7 (44.5-44.9) years; patients on Medicaid (n = 45 123), 39.8 (39.3-40.3) years; and uninsured patients (n = 19 530), 41.9 (41.5-42.4) years. Overall, low-value and high-value care was delivered in 19.4% (95% CI, 18.5%-20.2%) and 33.4% (95% CI, 32.4%-34.3%) of eligible encounters, respectively. Rates of low-value and high-value care delivery were similar across insurance types for the majority of services examined. Among Medicaid patients, adjusted rates of use were no different for 6 of 9 low-value and 9 of 12 high-value services compared with privately insured beneficiaries, whereas among the uninsured, rates were no different for 7 of 9 low-value and 9 of 12 high-value services. Safety-net physicians provided similar care compared with non-safety-net physicians, with no difference for 8 out of 9 low-value and for all 12 high-value services. Conclusions and Relevance: Overuse of low-value care is common among patients without insurance or with Medicaid. Rates of low-value and high-value care were similar among physicians serving vulnerable patients and other physicians. Overuse of low-value care is a potentially important focus for state Medicaid programs and safety-net institutions to pursue cost savings and improved quality of health care delivery.

Income Inequities and Medicaid Expansion are Related to Racial and Ethnic Disparities in Delayed or Forgone Care Due to Cost.

BACKGROUND: Monitoring political and social determinants of delayed or forgone care due to cost is necessary to evaluate efforts to reduce racial and ethnic disparities in access to care. Our objective was to examine the extent to which state Medicaid expansion decisions and personal household income may be associated with individual-level racial and ethnic disparities in delayed or forgone care due to cost, at baseline, before the implementation of the Affordable Care Act. METHODS: We used 2012 Behavioral Risk Factor Surveillance System survey data to examine racial and ethnic differences in delayed or forgone care due to cost in states that do and do not plan Medicaid expansion. We examined personal household income as a social factor that could contribute to racial and ethnic disparities in delayed or forgone care. RESULTS: We found that personal income differences were strongly related to disparities in delayed or forgone care in places with and without plans to expand Medicaid. In addition, while delayed or forgone care disparities between non-Hispanic whites and non-Hispanic blacks were lowest in places with plans to expand Medicaid access, disparities between non-Hispanic whites and Hispanics did not differ by state Medicaid expansion plans. CONCLUSIONS: As access to insurance improves for diverse groups, health systems must develop innovative strategies to overcome social determinants of health, including income inequities, as barriers to accessing care for Hispanic and non-Hispanic blacks. Additional efforts may be needed to ensure Hispanic groups achieve the benefits of investments in health care access.