Abstract 16364: Effect of Social Determinants on Outcomes in a High-risk Cardio-obstetrics Population

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Corinne Carland ◽  
Danielle Panelli ◽  
Christine Lee ◽  
Elizabeth Sherwin ◽  
Eleanor Levin ◽  
...  
Keyword(s):  
Heart Disease ◽  
High Risk ◽  
Social Determinants ◽  
Household Income ◽  
Neonatal Death ◽  
Median Income ◽  
Lower Income ◽  
Median Household Income ◽  
Significant Difference ◽  
Zip Code

Introduction: Cardiovascular disease is the leading cause of maternal mortality. The hemodynamic changes that occur during pregnancy make this a particularly vulnerable time for women with heart disease. Additionally, it is known that social determinants have an effect on certain outcomes in pregnancy, although research to quantify this effect is limited. We compared demographics and outcomes for women in upper- and lower-income brackets based on zip codes. Methods: We performed a retrospective cohort study of high-risk pregnant patients with cardiac diagnoses between November 2010 and June 2019. Patients were stratified into upper- and lower-income based on median household income in their zip code (2018 U.S. census). Results: We studied 191 pregnancies. Patients were stratified by zip code into lower (<$118,201/yr, N = 95) and upper median household income (N = 96) groups (Table 1). Women in the lower income bracket had more antepartum hospitalizations (38.3% vs 17.9%), were younger (30.6 vs 33.9 years), Hispanic (42.1% vs 10.4%), and more likely to have public insurance (46.8% vs 21.3%). There was a difference in cardiac diagnoses between the two groups; those with lower income had more structural heart disease (41.1% vs 17.7%) and fewer arrhythmias (25.3% vs 39.6%). In the lower income group, there were 2 maternal deaths and 1 neonatal death before discharge, while in the upper income there was 1 neonatal death. Conclusions: Our study examined the relationship between median income per zip code and pregnancy outcomes, and demographics in women with heart disease. Our observations demonstrate a significant difference in maternal age, race, distribution of cardiac diagnoses, and antepartum hospitalizations. Despite all women being treated at the same facility, antepartum hospitalizations differed based on income bracket. Social determinants of health are important factors that impact outcomes in the cardiac-obstetric population and require further investigation.

scholarly journals Differences in Pertussis Incidence by Income among Oregon Teens during an Outbreak

2015 ◽  
Vol 2015 ◽  
pp. 1-4 ◽  
Author(s):  
Steve G. Robison ◽  
Juventila Liko ◽  
Paul R. Cieslak
Keyword(s):  
Public Health ◽  
Household Income ◽  
Disease Risk ◽  
Incidence Rates ◽  
Care Seeking ◽  
Lower Income ◽  
Median Household Income ◽  
Real Risk ◽  
Zip Code

That disease and poverty are connected is a cornerstone of public health thought. In the case of pertussis, however, it is possible that the expected relationship to poverty is reversed. Grounds exist for considering that increases in income are associated with increases in pertussis rates, both in terms of real risk through social and network features and through the possibility of greater likelihood of care seeking and detection based on income. Using reported adolescent pertussis cases from a 2012 outbreak in Oregon, pertussis incidence rates were determined for areas grouped by zip code into higher, middle, and lower median household income. Adolescents of ages 13–16 years in higher income areas were 2.6 times (95% CI 1.8–3.8) more likely as all others to have reported pertussis during the 2012 outbreak and 3.1 (95% CI 1.4–6.5) times as likely as those in lower income areas. The higher pertussis rates associated with higher income areas were observed regardless of Tdap rate differences. These results suggest that income may be associated with disease risk, likelihood of diagnosis and reporting, or both. Further evaluation of this finding is warranted.

Abstract 14242: Homogeneous Fetal Access to Cardiac Care in a Heterogeneous State

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Laura Garcia Godoy ◽  
Erin J Madriago ◽  
christina ronai
Keyword(s):  
Heart Disease ◽  
Socioeconomic Factors ◽  
Gestational Age ◽  
Rural Areas ◽  
Retrospective Chart Review ◽  
Median Income ◽  
Significant Difference ◽  
Family Decision Making ◽  
Zip Code

Introduction: Timely prenatal diagnosis of congenital heart disease (CHD) allows for families to participate in complex decisions and plan for the care of their child. This study sought to investigate if the timing of the first fetal echocardiogram (FE) and the characteristics of fetal counseling were impacted by parental socioeconomic factors. Hypothesis: We hypothesized that the scheduling of initial FE would be delayed due to distance from hospital, rurality of maternal home and median income. Methods: We performed a retrospective chart review of all fetal patients referred to our institution from 1/1/17 to 12/31/18 with a diagnosis of CHD. We looked at the gestational age at the first FE, age of mother, zip code of residence, rurality index, distance from our hospital and maternal ethnicity. Counseling was evaluated based on documentation in the FE report regarding use of interpreter, time billed for counseling, individuals accompanying mother, and treatment option chosen. Results: 138 maternal-fetal dyads met inclusion criteria, 29 dyads had a diagnosis of single ventricle heart disease. The median gestational age (GA) at first FE was 24 weeks 4 days. The median income was $57,019 ($42,624-$83,695), and the median distance to the hospital was 51 miles (3.2-379.9miles). There was no difference in income, distance from hospital or rurality index and timing of first FE. There was no significant difference between maternal ethnicity and age of mother, GA at initial FE, number of follow-up FEs or family accompanying mother to the visit. There was no difference in maternal ethnicity and use of interpreter with time counseled. Patients who lived in rural areas did have increased counseling time (p<.05). Importantly, there was no difference between socioeconomic factors and ultimate parental choices (termination, palliative delivery or surgery). Conclusions: Oregon comprises a heterogeneous population from a large geographical catchment. While prenatal counseling and family decision making is multifaceted we demonstrated that dyads were referred from across the state and received care in a uniformly timely manner, and once at our center received consistent counseling despite differences in parental socioeconomic factors.

Zip Code-Related Income Disparities in Patients with Colorectal Cancer

2021 ◽  
pp. 000313482110234
Author(s):  
Yasmeen Z. Qwaider ◽  
Naomi M. Sell ◽  
Chloe Boudreau ◽  
Caitlin E. Stafford ◽  
Rocco Ricciardi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Income Group ◽  
Tertiary Hospital ◽  
Lower Proportion ◽  
Stage Iii ◽  
Median Income ◽  
Lower Income ◽  
Income Disparities ◽  
The Mean ◽  
Zip Code

Introduction Screening and early detection reduce morbidity and mortality in colorectal cancer. Our aim is to study the effect of income disparities on the clinical characteristics of patients with colorectal cancer in Massachusetts. Methods Patients were extracted from a database containing all surgically treated colorectal cancers between 2004 and 2015 at a tertiary hospital in Massachusetts. We split patients into 2 groups: “above-median income” and “below-median income” according to the median income of Massachusetts ($74,167). Results The analysis included 817 patients. The above-median income group consisted of 528 patients (65%) and the below-median income group consisted of 289 patients (35%). The mean age of presentation was 64 ± 15 years for the above-median income group and 67 ± 15 years for the below-median income group ( P = .04). Patients with below-median income were screened less often ( P < .001) and presented more frequently with metastatic disease ( P = .02). Patients with above-median income survived an estimated 15 months longer than those with below-median income ( P < .001). The survival distribution was statistically significantly different between the groups for stage III disease ( P = .004), but not stages I, II, or IV ( P = 1, 1, and .2, respectively). For stage III disease, a lower proportion of below-median income patients received chemotherapy (61% vs. 79%, P = .002) and a higher proportion underwent nonelective surgery (5% vs. 2%, P = .007). Conclusions In Massachusetts, patients with colorectal cancer residing in lower income areas are screened less, received adjuvant chemotherapy less, and have worse outcomes, especially when analyzing those who present with stage III disease.

Pregnancy in women with pre-existent ischaemic heart disease: a systematic review with individualised patient data

Heart ◽  
2019 ◽  
Vol 105 (11) ◽  
pp. 873-880 ◽  
Author(s):  
Heleen Lameijer ◽  
Luke J Burchill ◽  
Lucia Baris ◽  
Titia PE Ruys ◽  
Jolien W Roos-Hesselink ◽  
...  
Keyword(s):  
Systematic Review ◽  
Heart Disease ◽  
High Risk ◽  
Ischaemic Heart Disease ◽  
Cardiovascular Complications ◽  
Patient Data ◽  
Pregnancy Risk ◽  
Neonatal Complications ◽  
Coronary Syndrome ◽  
Significant Difference

IntroductionStudies on pregnancy risk in women with ischaemic heart disease (IHD) have mainly excluded pregnancies in women with pre-existent IHD. There is a need for better information about the pregnancy risks in these women and their offspring.MethodsWe performed a systematic review searching the PubMed/MEDLINE public database for pregnancy in women with pre-existent IHD analysing the cardiac, obstetric and fetal/neonatal outcome of pregnancy in women with pre-existing IHD. Individual patient data were requested from large series. The primary outcome endpoints was a composite of ischaemic complications including maternal death, acute coronary syndrome and ventricular tachycardia.Results116 women with pre-existent IHD had 124 pregnancies including one twin pregnancy. They had a 21% chance of having an uncomplicated pregnancy (completed pregnancy without cardiovascular, obstetric or fetal/neonatal complications, n=26). Primary (ischaemic) endpoints occurred in 9% (n=11). Women with atherosclerosis had more cardiovascular complications compared with pregnancies in women with other underlying pathology for IHD (50%vs23%, P=0.02) but no significant difference in occurrence of primary endpoints (13% vs 9%, P=0.53). There were two maternal cardiac deaths (2%), one of which occurred in the 18th week of pregnancy and the other postpartum. Obstetric complications occurred in 58% (n=65) of pregnancies and fetal/neonatal complications in 42% (n=47).ConclusionPregnancies in women with pre-existing IHD are high-risk pregnancies. These women have a high risk of ischaemic cardiovascular complications including 2% maternal mortality. The risk of ischaemic complications is especially high among women with atherosclerotic coronary artery disease.

scholarly journals Usage of a Digital Health Workplace Intervention Based on Socioeconomic Environment and Race: Retrospective Secondary Cross-Sectional Study (Preprint)

2017 ◽  
Author(s):  
Conor Senecal ◽  
R Jay Widmer ◽  
Kent Bailey ◽  
Lilach O Lerman ◽  
Amir Lerman
Keyword(s):  
Socioeconomic Status ◽  
High Risk ◽  
Digital Health ◽  
Demographic Data ◽  
Health Intervention ◽  
Median Income ◽  
Cross Sectional ◽  
Socioeconomic Environment ◽  
One Year ◽  
Zip Code

BACKGROUND Digital health tools have been associated with improvement of cardiovascular disease (CVD) risk factors and outcomes; however, the differential use of these technologies among various ethnic and economic classes is not well known. OBJECTIVE To identify the effect of socioeconomic environment on usage of a digital health intervention. METHODS A retrospective secondary cross-sectional analysis of a workplace digital health tool use, in association with a change in intermediate markers of CVD, was undertaken over the course of one year in 26,188 participants in a work health program across 81 organizations in 42 American states between 2011 and 2014. Baseline demographic data for participants included age, sex, race, home zip code, weight, height, blood pressure, glucose, lipids, and hemoglobin A1c. Follow-up data was then obtained in 90-day increments for up to one year. Using publicly available data from the American Community Survey, we obtained the median income for each zip code as a marker for socioeconomic status via median household income. Digital health intervention usage was analyzed based on socioeconomic status as well as age, gender, and race. RESULTS The cohort was found to represent a wide sample of socioeconomic environments from a median income of US $11,000 to $171,000. As a whole, doubling of income was associated with 7.6% increase in log-in frequency. However, there were marked differences between races. Black participants showed a 40.5% increase and Hispanic participants showed a 57.8% increase in use with a doubling of income, compared to 3% for Caucasian participants. CONCLUSIONS The current study demonstrated that socioeconomic data confirms no relevant relationship between socioeconomic environment and digital health intervention usage for Caucasian users. However, a strong relationship is present for black and Hispanic users. Thus, socioeconomic environment plays a prominent role only in minority groups that represent a high-risk group for CVD. This finding identifies a need for digital health apps that are effective in these high-risk groups.

scholarly journals Analysis of COVID-19 Case Demographics in Gary, Indiana

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yazan Al-Tarshan ◽  
Maryam Sabir ◽  
Cameron Snapp ◽  
Martin Brown ◽  
Roland Walker ◽  
...  
Keyword(s):  
Low Income ◽  
Household Income ◽  
Black Population ◽  
Health Department ◽  
Poverty Line ◽  
Median Household Income ◽  
Predominantly Black ◽  
Chi Square ◽  
Gary Indiana ◽  
Zip Code

Background and Hypothesis  It has been reported in several recent studies that health disparities associated with COVID-19 infection r are prevalent in Black and impoverished populations. The contribution of multiple causes to these disparities is still not completely elucidated. Gary, Indiana has a large Black population (80%), high number of residents living below the poverty line (34%), and high unemployment rate (20%). We hypothesized that Black individuals in Gary have a higher rate of positive cases, hospitalizations, and deaths than non-Black individuals. Also, we hypothesized that (median household income measured by the zip code) is negatively correlated with COVID-19 positive cases, hospitalizations, and deaths.     Methods  In collaboration with the Gary Health Department, we analyzed data on all positive cases in the city from 06/16/2020 through 06/07/2021(totally 5149 cases). We compared this data to the data from 03/16/2020 through 06/16/2020 (totally 724 cases) that we analyzed previously. Data was de-identified and included age, race, ethnicity, and zip code.  The data was analyzed using Pearson's chi-square test and regression analysis.    Results   When compared to the non-Black population in Gary age and population-adjusted rates of hospitalizations and deaths in the Black population are 3-fold (p<9.385E-11) and 2-fold (p<0.0171) higher, respectively. Surprisingly, the non-Black population had a higher infection rate than the Black population (p<2.69E-09). Median household income of a zip code is negatively correlated with COVID-19 hospitalizations in that zip code (R2=0.6345, p=0.03), but is does not affect the .rates of infections and deaths.     Conclusion   Our data show that in Gary, there is a clear health disparity of both income and race, specifically in the context of COVID-19. IUSMNW and Gary health officials can collaborate and utilize this data to reallocate resources to the highly populated, low income, and predominantly Black neighborhoods.  

scholarly journals “Association between Median Household Income, State Medicaid Expansion Status, and COVID-19 Outcomes Across US Counties”

2021 ◽  
Author(s):  
Tsikata Apenyo ◽  
Antonio Vera-Urbina ◽  
Khansa Ahmad ◽  
Tracey H. Taveira ◽  
Wen-Chih Wu
Keyword(s):  
Mortality Risk ◽  
Low Income ◽  
Household Income ◽  
Medicaid Expansion ◽  
Median Household Income ◽  
Incidence And Mortality ◽  
Significant Difference ◽  
Us Counties ◽  
The Relationship ◽  
Income Quartile

AbstractObjectiveThe relationship between socioeconomic status and its interaction with State’s Medicaid-expansion policies on COVID-19 outcomes across United States (US) counties are uncertain. To determine the association between median-household-income and its interaction with State Medicaid-expansion status on COVID-19 incidence and mortality in US countiesMethodsLongitudinal, retrospective analysis of 3142 US counties (including District of Columbia) to study the relationship between County-level median-household-income (defined by US Census Bureau’s Small-Area-Income-and-Poverty-Estimates) and COVID-19 incidence and mortality per 100000 of the population in US counties from January 20, 2020 through December 6, 2020. County median-household-income was log-transformed and stratified by quartiles. Medicaid-expansion status was defined by US State’s Medicaid-expansion adoption as of first reported US COVID-19 infection, January 20, 2020. Multilevel mixed-effects generalized-linear-model with negative binomial distribution and log link function compared quartiles of median-household-income and COVID-19 incidence and mortality, reported as incidence-risk-ratio (IRR) and mortality-risk-ratio (MRR), respectively. Models adjusted for county socio-demographic and comorbidity conditions, population density, and hospitals, with a random intercept for states. Multiplicative interaction tested for Medicaid-expansion*income quartiles on COVID-19 incidence and mortality.ResultsThere was no significant difference in COVID-19 incidence across counties by income quartiles or by Medicaid expansion status. Conversely, significant differences exist between COVID-19 mortality by income quartiles and by Medicaid expansion status. The association between income quartiles and COVID-19 mortality was significant only in counties from non-Medicaid-expansion states but not significant in counties from Medicaid-expansion states (P<0.01 for interaction). For non-Medicaid-expansion states, counties in the lowest income quartile had a 41% increase in COVID-19 mortality compared to counties in the highest income quartile (MRR 1.41, 95% CI: 1.25-1.59).Conclusions and RelevanceMedian-household-income was not related to COVID-19 incidence but negatively related to COVID-19 mortality in US counties of states without Medicaid-expansion. It was unrelated to COVID-19 mortality in counties of states that adopted Medicaid-expansion. These findings suggest that expanded healthcare coverage should be investigated further to attenuate the excessive COVID-19 mortality risk associated with low-income communities.Key FindingsQuestionIs there a relationship between COVID-19 outcomes (incidence and mortality) and household income and status of Medicaid expansion of US counties?FindingsIn this longitudinal, retrospective analysis of 3142 US counties, we found no significant difference in COVID-19 incidence across US counties by quartiles of household income. However, counties with lower median household income had a higher risk of COVID-19 mortality, but only in non-Medicaid expansion states. This relationship was not significant in Medicaid expansion states.MeaningExpanded healthcare coverage through Medicaid expansion should be investigated as an avenue to attenuate the excessive COVID-19 mortality risk associated with low-income communities.

Abstract P449: The Impact of Race and Social Determinants of Health on Imaging Biomarkers in Intracerebral Hemorrhage

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Kristie Bauman ◽  
Shashank Agarwal ◽  
Shadi Yaghi ◽  
Ariane Lewis ◽  
Aaron Lord ◽  
...  
Keyword(s):  
Social Determinants Of Health ◽  
Social Determinants ◽  
Education Level ◽  
Determinants Of Health ◽  
Imaging Biomarkers ◽  
Median Income ◽  
Black Race ◽  
History Of ◽  
The Brain ◽  
Zip Code

Introduction: The association between race and white matter hyperintensities (WMH) and cerebral microbleeds in patients with intracerebral hemorrhage (ICH) is controversial. We examined the relationship between race and social determinants of health with WMH and microbleeds in ICH. Methods: We performed a retrospective study of patients at a tertiary care hospital between 2013 and 2020 who presented with ICH and underwent MRI of the brain. MRIs were evaluated for the presence of microbleeds and WMH severity (defined by the Fazekas scale; severe WMH defined as Fazekas 3). We assessed for an association of sex, race, ethnicity, employment status, median household income by zip code, education level, and insurance status with the severity of WMH or presence of microbleeds. Results: We identified 105 patients (median age 65.5 (IQR 53-76); 51% females; 13.2% Black) with ICH who had an MRI of the brain. Median ICH score was 1 [IQR 0-2] and median hematoma size was 15.9 ml (SD 19.7). High school graduation was the highest education level in 13.2%, and 57.5% had private insurance. Median income by zip code was $87,667 (IQR $65,900-$117,923). Severe WMH was observed in 19.8% and 52.8% of patients had microbleeds. There was no significant difference in sex, insurance status or median income for patients with or without severe WMH nor those with or without microbleeds. Severe WMH was more common among older patients (p=0.001), Black patients (p=0.03), patients with hypertension (p=0.03), and those with lower levels of education (p=0.03). In multivariable analyses, Black race was associated with severe WMH when adjusting for age and history of hypertension (OR 6.13 95% CI 1.14-25.98, p=0.01) but the effect size attenuated and the association disappears when adding education level to the model (OR 3.38 95% CI 0.48-23.76, p = 0.2). Age and history of hypertension were associated with presence of microbleeds (p<0.01 for both), but there was no association between presence of microbleeds and Black race or education level. Conclusion: Although Black race was associated with severe WMH, this association did not remain after adjusting for level of education. Our findings suggest that social determinants of health can modify the association between race and imaging biomarkers of ICH.

scholarly journals Effects of Dapagliflozin on Endothelial Dysfunction in Type 2 Diabetes With Established Ischemic Heart Disease (EDIFIED)

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Nur Aisyah Zainordin ◽  
Sharifah Faradilla Wan Muhamad Hatta ◽  
Fatimah Zaherah Mohamed Shah ◽  
Thuhairah Abdul Rahman ◽  
Nurhuda Ismail ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Heart Disease ◽  
Placebo Group ◽  
High Risk ◽  
Endothelial Function ◽  
Ischemic Heart Disease ◽  
Ischemic Heart ◽  
Surrogate Markers ◽  
Significant Difference

Abstract Objectives To evaluate the effect of the sodium-glucose cotransporter 2 inhibitor (SGLT2-I) dapagliflozin on endothelial function in patients with high-risk type 2 diabetes mellitus (T2DM). Methods This was a prospective, double-blind, randomized, placebo-controlled, clinical trial of patients with T2DM with underlying ischemic heart disease who were receiving metformin and insulin therapy (n = 81). After 12-weeks of additional therapy with either dapagliflozin (n = 40) or placebo (n = 41), systemic endothelial function was evaluated by change in flow-mediated dilation (ΔFMD), change in nitroglycerin-mediated dilation (ΔNMD) and surrogate markers including intercellular adhesion molecule 1 (ICAM-1), endothelial nitric oxide synthase (eNOS), high-sensitivity C-reactive protein (hs-CRP), and lipoprotein(a) (Lp[a]). Glycemic and lipid profiles were also measured. Results The dapagliflozin group demonstrated significant reductions of hemoglobin A1c (HbA1c) and fasting blood glucose (FBG) compared to the placebo group (ΔHbA1c –0.83 ± 1.47% vs –0.16 ± 1.25%, P = 0.042 and ΔFBG vs –0.73 ± 4.55 mmol/L vs –1.90 ± 4.40 mmol/L, P = 0.015, respectively). The placebo group showed worsening of ΔFMD while the dapagliflozin group maintained similar measurements pre- and posttherapy (P = not significant). There was a reduction in ICAM-1 levels in the dapagliflozin group (–83.9 ± 205.9 ng/mL, P &lt; 0.02), which remained unchanged in the placebo group (–11.0 ± 169.1 ng/mL, P = 0.699). Univariate correlation analysis revealed a significant negative correlation between HbA1c and ΔFMD within the active group. Conclusion A 12-week therapy with dapagliflozin, in addition to insulin and metformin therapies, in high-risk patients resulted in significant reductions in HbA1c, FBG, and surrogate markers of the endothelial function. Although the dapagliflozin group demonstrated a significant association between reduction in HbA1c and improvement in FMD, there was no significant difference in FMD between the 2 groups.

Is chimeric antigen receptor T cell (CART) a destination procedure? Lower socioeconomic class who live farther from center have less access to CART.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e18562-e18562
Author(s):  
Nausheen Ahmed ◽  
Ernie Shippey ◽  
Crissy Kus ◽  
Allison Appenfeller ◽  
Marc Steven Hoffmann ◽  
...  
Keyword(s):  
T Cell ◽  
Chimeric Antigen Receptor ◽  
Low Income ◽  
Household Income ◽  
Census Data ◽  
Financial Burden ◽  
Antigen Receptor ◽  
Median Income ◽  
Lower Income ◽  
Post Infusion

e18562 Background: Axicabtagene ciloleucel and tisagenlecleucel are commercially available CD19 chimeric antigen receptor T-cell (CART) therapies for B cell malignancies. Manufacturing pharmaceutical companies require patients to stay within 2 hours of the center for 4 weeks post infusion. Most centers require local lodging for that period if residence is over 30 minutes away. Financial burden may limit access. We therefore hypothesized that those who were likely to receive CART therapies were from higher income neighborhoods or lived closer to the facility. Methods: Since most patients get admitted for CART infusion, we used the Vizient CDB database for CART infusion admissions as well as other admissions. Patients over the age of 18 yrs who got commercially available CART between 2018 to 2020 were included. Distance was calculated in miles from patient zip code to treating center. Using census data, lower income neighborhoods (less than $40,000 median household income) were flagged. Results: 81 centers administered CART. We calculated the distance in miles between the patient and the center for both CART admissions as well as for all-cause inpatient admissions. Most admissions (81.2% all-cause vs 78.6% CART) were from neighborhoods with median income > $40,000. Most of the low-income admissions were from neighborhoods <10 miles (13.3% all admissions vs 15.7% CART). 80.6% of all CART patients came from neighborhoods over 10 miles, with 38.2% living over 60 miles away, while only 15.4% all-cause admissions were from > 60 miles. (p<.0001) While 74.9% of higher income CART patients lived beyond 10 miles from center, only 5.7% CART patients lived beyond 10 miles. Results summarized in Table. Conclusions: Most CART patients lived over 10 miles from the center, however less than 10% of them were from lower income neighborhoods. Neighborhood location relative to center and household income influence access and need to be addressed.[Table: see text]

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