Safety-Net Hospitals, Neighborhood Disadvantage, and Readmissions Under Maryland's All-Payer Program: An Observational Study

The impact of social deprivation on healthcare utilization patterns following rotator cuff repair

BACKGROUND

Disparities in social determinants of health have been linked to worse patient reported outcomes, higher pain, and increased risk of revision surgery following rotator cuff repair. Identification of perioperative predictors of increased healthcare utilization is of particular interest to surgeons to improve outcomes and mitigate the total cost of care. The effect of social deprivation on healthcare utilization has not been fully characterized.

METHODS

This is a retrospective review of a single institution's experience with primary rotator cuff repair between 2012 and 2020. Demographic variables (age, race, gender, American Society of Anesthesiologists (ASA) score) and healthcare utilization (hospital readmission, emergency department visits, follow-up visits, telephone calls) were recorded within 90 days of surgery. The Area Deprivation Index (ADI) was recorded, and patients were separated into terciles according to their relative level of social deprivation. Outcomes were then stratified based on ADI tercile and compared.

RESULTS

A total of 1695 patients were included. The upper, middle, and lower terciles of ADI consisted of 410, 767, and 518 patients, respectively. The most deprived tercile had greater emergency department visitation and office visitation within 90 days of surgery relative to the least and intermediate deprived terciles. Higher levels of social deprivation were independent risk factors for increased emergency department (ED) visitation and follow-up visitation. There was no difference in 90-day readmission rates or telephone calls made between the least, intermediate, and most deprived patients.

CONCLUSIONS

Patients with higher levels of deprivation demonstrated greater postoperative hospital utilization. We hope to use these results to identify risk factors for increased hospital use, guide clinical decision making, increase transparency, and manage patient outcomes following rotator cuff repair surgery.

Geographic Socioeconomic Influences on Disease Activity in Rheumatoid Arthritis in an Academic and Safety Net Hospital System

OBJECTIVE

The objective of this study was to analyze the impact of the Area Deprivation Index (ADI) on disease activity and cardiovascular comorbidity in rheumatoid arthritis (RA).

METHODS

A retrospective analysis of adult patients with RA was conducted to highlight differences in academic and safety net hospital clinics. Demographics, RA medication history, patient portal engagement, primary care presence, emergency or inpatient visits, RA disease activity and functional scores, Charlson Comorbidity Index (CCI), and cardiovascular disease (CVD) presence were captured. The ADI rank was assigned using nine-digit zip codes. Patients were stratified by the upper versus lower ADI decile group and matched by age, sex, race, ethnicity, insurance, and CCI using propensity score analysis.

RESULTS

Patients with RA from the academic practice (n = 542) and the safety net hospital (n = 496) were assessed. In the academic cohort, those with high ADI scores (>8, more deprivation) had higher RA disease activity scores (Routine Assessment of Patient Index Data 3 mean ± SD: high 13.83 ± 6.94 vs low 11.17 ± 7.37, P < 0.0001; Clinical Disease Activity Index mean ± SD: high 11.97 ± 11.74 vs low 9.40 ± 7.97, P < 0.05), more functional impairment (Multidimensional Health Assessment Questionnaire mean ± SD: high 2.99 ± 2.29 vs low 2.34 ± 2.23, P < 0.01), lower MyChart use (P < 0.001), and different smoking history (P < 0.01) compared to those with low ADI scores (<3, less deprivation). In the safety net cohort, there was a statistically significant difference only in smoking status (P < 0.05). CVD was not significantly different in either cohort.

CONCLUSION

The absence of differences in RA disease activity and functional impairment in patients suggests that the ADI may not be as effective at predicting RA disease activity specifically in a safety net health care context. Identifying the discrepancies between the two systems may elucidate areas of improvement for patient care.

Sociodemographic biases in a commercial AI model for intracranial hemorrhage detection

PURPOSE

To evaluate whether a commercial AI tool for intracranial hemorrhage (ICH) detection on head CT exhibited sociodemographic biases.

METHODS

Our retrospective study reviewed 9736 consecutive, adult non-contrast head CT scans performed between November 2021 and February 2022 in a single healthcare system. Each CT scan was evaluated by a commercial ICH AI tool and a board-certified neuroradiologist; ground truth was defined as final radiologist determination of ICH presence/absence. After evaluating the AI tool's aggregate diagnostic performance, sub-analyses based on sociodemographic groups (age, sex, race, ethnicity, insurance status, and Area of Deprivation Index [ADI] scores) assessed for biases. χ2 test or Fisher's exact tests evaluated for statistical significance with p ≤ 0.05.

RESULTS

Our patient population was 50% female (mean age 60 ± 19 years). The AI tool had an aggregate accuracy of 93% [9060/9736], sensitivity of 85% [1140/1338], specificity of 94% [7920/ 8398], positive predictive value (PPV) of 71% [1140/1618] and negative predictive value (NPV) of 98% [7920/8118]. Sociodemographic biases were identified, including lower PPV for patients who were females (67.3% [62,441/656] vs. 72.7% [699/962], p = 0.02), Black (66.7% [454/681] vs. 73.2% [686/937], p = 0.005), non-Hispanic/non-Latino (69.7% [1038/1490] vs. 95.4% [417/437]), p = 0.009), and who had Medicaid/Medicare (69.9% [754/1078]) or Private (66.5% [228/343]) primary insurance (p = 0.003). Lower sensitivity was seen for patients in the third quartile of national (78.8% [241/306], p = 0.001) and state ADI scores (79.0% [22/287], p = 0.001).

CONCLUSIONS

In our healthcare system, a commercial AI tool had lower performance for ICH detection than previously reported and demonstrated several sociodemographic biases.

The Scalding Truth: Geospatial Analysis Identifies Communities at Risk for Pediatric Scald Burns

INTRODUCTION

Pediatric scald burns account for 12% of all U.S. burn center admissions and are the most common type of burn in children. We hypothesized that geospatial analysis of burn registry data could identify specific geographic areas and risk factors to focus injury prevention efforts.

METHODS

The burn registry of a U.S. regional burn center was used to retrospectively identify pediatric scald burn patients ages 0-17, from January 2018 to June 2023. Geocoding of patient home addresses with census tract data was performed. Area Deprivation Index (ADI) was assigned to patients at the census block group level. Burn incident hot spot analysis to identify statistically significant burn incident clusters was done using the Getis Ord Gi∗ statistic.

RESULTS

There were 950 pediatric scald burn patients meeting study criteria. The cohort was 52% male and 36% White, with median age of 3 y and median total body surface area of 1.5%; 23.8% required hospital admission. On multivariable logistic regression, increased child poverty levels (P = 0.004) and children living in single-parent households (P = 0.009) were associated with increased scald burn incidence. Geospatial analysis identified burn hot spots, which were associated with higher ADI (P < 0.001). Black patients were more likely to undergo admission compared to White patients.

CONCLUSIONS

Geospatial analysis of burn registry data identified geographic areas at high risk of pediatric scald burn. ADI, poverty, and children in single-parent households were the greatest predictors of injury. Addressing these inequalities requires targeted injury prevention education, enhanced outpatient support systems and more robust community resources.

Provision of Stroke Care Services by Community Disadvantage Status in the US, 2009-2022

Importance

Stroke center certification is granted to facilities that demonstrate distinct capabilities for treating patients with stroke. A thorough understanding of structural discrimination in the provision of stroke centers is critical for identifying and implementing effective interventions to improve health inequities for socioeconomically disadvantaged populations.

Objective

To determine whether (1) hospitals in socioeconomically disadvantaged communities (defined using the Area Deprivation Index) are less likely to adopt any stroke certification and (2) adoption rates differ between entry-level (acute stroke-ready hospitals) and higher-level certifications (primary, thrombectomy capable, and comprehensive) by community disadvantage status.

Design, Setting, and Participants

This cohort study used newly collected stroke center data merged with data from the American Hospital Association, Healthcare Cost Report Information datasets, and the US Census. All general acute hospitals in the continental US between January 1, 2009, and December 31, 2022, were included. Data analysis was conducted from July 2023 to May 2024.

Main Outcomes and Measures

The primary outcome was the likelihood of hospitals adopting stroke care certification. Cox proportional hazard and competing risk models were used to estimate the likelihood of a hospital becoming stroke certified based on the socioeconomic disadvantage status of the community.

Results

Among the 5055 hospitals studied from 2009 to 2022, 2415 (47.8%) never achieved stroke certification, 602 (11.9%) were certified as acute stroke-ready hospitals, and 2038 (40.3%) were certified as primary stroke centers or higher. When compared with mixed-advantage communities, adoption of any stroke certification was most likely to occur near the most advantaged communities (hazard ratio [HR], 1.24; 95% CI, 1.07-1.44) and least likely near the most disadvantaged communities (HR, 0.43; 95% CI, 0.34-0.55). Adoption of acute stroke-ready certification was most likely in mixed-advantage communities, while adoption of higher-level certification was more likely in the most advantaged communities (HR,1.41; 95% CI, 1.22-1.62) and less likely for the most disadvantaged communities (HR, 0.31; 95% CI, 0.21-0.45). After adjusting for population size and hospital capacity, compared with mixed-advantage communities, stroke certification adoption hazard was still 20% lower for relatively disadvantaged communities (adjusted HR, 0.80; 95% CI, 0.73-0.87) and 42% lower for the most disadvantaged communities (adjusted HR, 0.58; 95% CI, 0.45-0.74).

Conclusions and Relevance

In this cohort study examining hospital adoption of stroke services, when compared with mixed-advantage communities, hospitals located in the most disadvantaged communities had a 42% lower hazard of adopting any stroke certification and relatively disadvantaged communities had a 20% lower hazard of adopting any stroke certification. These findings suggest that there is a need to support hospitals in disadvantaged communities to obtain stroke certification as a way to reduce stroke disparities.

The Effect of Social Deprivation on Hospital Utilization Following Distal Radius Fracture Treatment

Purpose

Social determinants of health disparities have been shown to adversely impact outcomes following distal radius fracture (DRF) treatment. Identifying risk factors for increased hospital use following DRF has been historically difficult; however, it is of utmost concern to orthopedic surgeons to improve outcomes and decrease the total cost of care. The effect of social deprivation following DRF has yet to be fully investigated.

Methods

This is a retrospective cohort analysis of a single institution's experience in treating DRF with either an operative or nonsurgical modality between 2005 and 2020. Patient demographic information and health care utilization (hospital readmission, emergency department [ED] visitation, office visits, and telephone use) were collected from within 90 days of treatment. Area Deprivation Index (ADI) national percentiles were recorded. Patients were stratified into terciles based on their relative level of deprivation, and their outcomes were compared. Secondary analyses included stratifying patients based on treatment modality, race, and legal sex.

Results

In total, 2,149 patients were included. The least, intermediate, and most deprived groups consisted of 552, 1,067, and 530 patients, respectively. Risk factors for hospital readmission included higher levels of relative deprivation. Identifying as Black or African American and nonsurgical management were risk factors for increased ED visitation. No differences in rate of hospital readmission, ED visitation, office visitation, or telephone use were seen based on deprivation level.

Conclusions

High levels of social deprivation, treatment modality, race, and legal sex disparities may influence the amount of hospital resource utilization following DRF treatment. Understanding and identifying risk factors for greater resource utilization can help to mitigate inappropriate use and decrease health care costs. We hope to use these findings to guide clinical decision making, educate patient populations, and optimize outcomes following DRF treatment.

Type of Study/Level of Evidence

Therapeutic III.

Temporary Financial Assistance for Housing Expenditures and Mortality and Suicide Outcomes Among US Veterans

INTRODUCTION

It is unclear whether interventions designed to increase housing stability can also lead to improved health outcomes such as reduced risk of death and suicide morbidity. The objective of this study was to estimate the potential impact of temporary financial assistance (TFA) for housing-related expenses from the US Department of Veterans Affairs (VA) on health outcomes including all-cause mortality, suicide attempt, and suicidal ideation.

METHODS

We conducted a retrospective national cohort study of Veterans who entered the VA Supportive Services for Veteran Families (SSVF) program between 10/2015 and 9/2018. We assessed the association between TFA and health outcomes using a multivariable Cox proportional hazards regression approach with inverse probability of treatment weighting. We conducted these analyses on our overall cohort as well as separately for those in the rapid re-housing (RRH) and homelessness prevention (HP) components of SSVF. Outcomes were all-cause mortality, suicide attempt, and suicidal ideation at 365 and 730 days following enrollment in SSVF.

RESULTS

Our analysis cohort consisted of 41,969 unique Veterans with a mean (SD) duration of 87.6 (57.4) days in the SSVF program. At 365 days following SSVF enrollment, TFA was associated with a decrease in the risk of all-cause mortality (HR: 0.696, p < 0.001) and suicidal ideation (HR: 0.788, p < 0.001). We found similar results at 730 days (HR: 0.811, p = 0.007 for all-cause mortality and HR: 0.881, p = 0.037 for suicidal ideation). These results were driven primarily by individuals enrolled in the RRH component of SSVF. We found no association between TFA and suicide attempts.

CONCLUSION

We find that providing housing-related financial assistance to individuals facing housing instability is associated with improvements in important health outcomes such as all-cause mortality and suicidal ideation. If causal, these results suggest that programs to provide housing assistance have positive spillover effects into other important aspects of individuals' lives.

Socioeconomic status is associated with greater hazard of post-discharge mortality than race, gender, and ballistic injury mechanism in a young, healthy, orthopedic trauma population

OBJECTIVES

To explore the utility of legacy demographic factors and ballistic injury mechanism relative to popular markers of socioeconomic status as prognostic indicators of 10-year mortality following hospital discharge in a young, healthy patient population with isolated orthopedic trauma injuries.

METHODS

A retrospective cohort study was performed to evaluate patients treated at an urban Level I trauma center from January 1, 2003, through December 31, 2016. Current Procedure Terminology (CPT) codes were used to identify upper and lower extremity fracture patients undergoing operative fixation. Exclusion criteria were selected to yield a patient population of isolated extremity trauma in young, otherwise healthy individuals between the ages of 18 and 65 years. Variables collected included injury mechanism, age, race, gender, behavior risk factors, Area Deprivation Index (ADI), and insurance status. The primary outcome was post-discharge mortality, occurring at any point during the study period.

RESULTS

We identified 2539 patients with operatively treated isolated extremity fractures. The lowest two quartiles of socioeconomic status (SES) were associated with higher hazard of mortality than the highest SES quartile in multivariable analysis (Quartile 3 HR: 2.2, 95% CI: 1.2-4.1, p = 0.01; Quartile 4 HR: 2.2, 95% CI: 1.1-4.3, p = 0.02). Not having private insurance was associated with higher mortality hazard in multivariable analysis (HR 2.0, 95% CI: 1.3-3.2, p = 0.002). The presence of any behavioral risk factor was associated with higher mortality hazard in univariable analysis (HR: 1.8, p < 0.05), but this difference did not reach statistical significance in multivariable analysis (HR: 1.4, 95%: 0.8-2.3, p = 0.20). Injury mechanism (ballistic versus blunt), gender, and race were not associated with increased hazard of mortality (p > 0.20).

CONCLUSION

Low SES is associated with a greater hazard of long-term mortality than ballistic injury mechanism, race, gender, and medically diagnosable behavioral risk factors in a young, healthy orthopedic trauma population with isolated extremity injury.

Demographic and socioeconomic disparities in the hybrid ophthalmology telemedicine model

IMPORTANCE

As telemedicine use expands, it is important to evaluate demographic and socioeconomic disparities among patients receiving ophthalmic care through new hybrid telemedicine models.

OBJECTIVE

To evaluate whether there are demographic and socioeconomic disparities in the delivery of the hybrid telemedicine model.

DESIGN

Retrospective, cross-sectional, case-control analysis of patient encounters from April to December 2020.

SETTING

A single, academic, hospital-based eye clinic in Boston, Massachusetts.

METHODS

Electronic medical records of all patient encounters from April to December 2020 were reviewed and categorized into hybrid, virtual-only, and standard in-person visits. Patient-level data for all visits were extracted including age, sex, race/ethnicity, primary language, Area Deprivation Index (ADI), insurance type, and marital status. Visit-level data for all hybrid visits were also extracted from the medical record including the visit dates and patient adherence. Demographics for the cohort of patients with at least one no-show visit were compared with demographics for the cohort of patients who only had completed visits. The primary study outcomes were the differences in demographic characteristics between the hybrid visit show and no-show groups. The secondary outcomes included demographic characteristics of patients who did not complete their hybrid visit versus a time-matched cohort of patients who did not complete their standard in-person visit. Continuous variables for patient characteristics were compared with independent samples t-tests and categorical variables were compared using Pearson chi-square tests. Multivariate logistic regression was used to examine the differences between the cohorts. Variables with missing values other than suppressed ADI values were imputed using multiple imputations by chained equations.

RESULTS

Of a total of 1025 patients who were scheduled for a hybrid visit, 145 (14.1%) patients failed to complete their visit. Primary language and insurance were found to be statistically different between patients who completed and did not complete their hybrid visits. More English speakers and fewer Haitian Creole speakers completed their hybrid visits (p = 0.007) while more patients with private insurance and fewer patients with Medicaid completed their hybrid telemedicine visits (p = 0.026). No associations were found between hybrid telemedicine visit adherence and age, sex, race/ethnicity, marital status, or ADI. When the 145 patients who failed to complete their hybrid visits were compared to a time-matched cohort of patients who failed to complete their standard in-person visit, we found that patients who missed hybrid visits were similar to those who missed standard in-person visits except for patients insured by Medicare. These patients were more likely to miss a hybrid visit than a standard in-person visit (Odds Ratio 2.199, 95% confidence interval 1.136-4.259, p = 0.019). No associations were found between patient nonadherence with hybrid telemedicine versus with standard in-person visits based on age, sex, primary language, race/ethnicity, marital status, or ADI.

CONCLUSION

The hybrid telemedicine model was associated with insurance and language-based disparities. Patients with non-English primary language and Medicaid recipients were more likely to miss a hybrid visit than their counterparts. Our findings support developing deliberate interventions to ensure hybrid telemedicine care is delivered equitably to all patients.

A pragmatic clinical trial assessing the effect of a targeted notification and clinical support pathway on the diagnostic evaluation and treatment of individuals with left ventricular hypertrophy (NOTIFY-LVH)

BACKGROUND

Electronic health records contain vast amounts of cardiovascular data, including potential clues suggesting unrecognized conditions. One important example is the identification of left ventricular hypertrophy (LVH) on echocardiography. If the underlying causes are untreated, individuals are at increased risk of developing clinically significant pathology. As the most common cause of LVH, hypertension accounts for more cardiovascular deaths than any other modifiable risk factor. Contemporary healthcare systems have suboptimal mechanisms for detecting and effectively implementing hypertension treatment before downstream consequences develop. Thus, there is an urgent need to validate alternative intervention strategies for individuals with preexisting-but potentially unrecognized-LVH.

METHODS

Through a randomized pragmatic trial within a large integrated healthcare system, we will study the impact of a centralized clinical support pathway on the diagnosis and treatment of hypertension and other LVH-associated diseases in individuals with echocardiographic evidence of concentric LVH. Approximately 600 individuals who are not treated for hypertension and who do not have a known cardiomyopathy will be randomized. The intervention will be directed by population health coordinators who will notify longitudinal clinicians and offer to assist with the diagnostic evaluation of LVH. Our hypothesis is that an intervention that alerts clinicians to the presence of LVH will increase the detection and treatment of hypertension and the diagnosis of alternative causes of thickened myocardium. The primary outcome is the initiation of an antihypertensive medication. Secondary outcomes include new hypertension diagnoses and new cardiomyopathy diagnoses. The trial began in March 2023 and outcomes will be assessed 12 months from the start of follow-up.

CONCLUSION

The NOTIFY-LVH trial will assess the efficacy of a centralized intervention to improve the detection and treatment of hypertension and LVH-associated diseases. Additionally, it will serve as a proof-of-concept for how to effectively utilize previously collected electronic health data to improve the recognition and management of a broad range of chronic cardiovascular conditions.

TRIAL REGISTRATION

NCT05713916.

Differential Treatment and Outcomes for Patients With Heart Attacks in Advantaged and Disadvantaged Communities

Background Racially and ethnically minoritized groups, people with lower income, and rural communities have worse access to percutaneous coronary intervention (PCI) than their counterparts, but PCI hospitals have preferentially opened in wealthier areas. Our study analyzed disparities in PCI access, treatment, and outcomes for patients with acute myocardial infarction based on the census-derived Area Deprivation Index. Methods and Results We obtained patient-level data on 629 419 patients with acute myocardial infarction in California between January 1, 2006 and December 31, 2020. We linked patient data with population characteristics and geographic coordinates, and categorized communities into 5 groups based on the share of the population in low or high Area Deprivation Index neighborhoods to identify differences in PCI access, treatment, and outcomes based on community status. Risk-adjusted models showed that patients in the most advantaged communities had 20% and 15% greater likelihoods of receiving same-day PCI and PCI during the hospitalization, respectively, compared with patients in the most disadvantaged communities. Patients in the most advantaged communities also had 19% and 16% lower 30-day and 1-year mortality rates, respectively, compared with the most disadvantaged, and a 15% lower 30-day readmission rate. No statistically significant differences in admission to a PCI hospital were observed between communities. Conclusions Patients in disadvantaged communities had lower chances of receiving timely PCI and a greater risk of mortality and readmission compared with those in more advantaged communities. These findings suggest a need for targeted interventions to influence where cardiac services exist and who has access to them.

Socioeconomic Disparities in Patients Receiving Intravitreal Injections for Age-Related Macular Degeneration Amid the COVID-19 Pandemic

Purpose: To determine the effects of socioeconomic factors on visit adherence and the resultant visual outcomes for patients receiving intravitreal injections for neovascular age-related macular degeneration during the COVID-19 pandemic. Methods: In this retrospective case-control study, medical records were reviewed to collect appointment attendance, age, sex, self-reported race/ethnicity, primary language, marital status, insurance, distance from clinic, and Area Deprivation Index (ADI), a measure of socioeconomic disadvantage. Multivariate regression models were created to determine differences in socioeconomic factors between individuals who attended (show group) and those who did not attend (no-show group) appointments. Results: The study enrolled 126 patients in the show group and 115 in the no-show group. On univariate analysis, nonadherence was significantly higher in non-White patients than in White patients (P = .04), urban sites than in suburban sites (P = 1.7 × 10-4), and non-English-speaking patients than in English-speaking patients (P = 4.0 × 10-3). The associations remained significant in multivariate analysis for non-English-speaking patients (P = .03) and urban-site patients (P = .01) after adjusting for age, sex, self-reported race/ethnicity, primary language, marital status, insurance, distance from clinic, site of visit, and ADI. At 6 months and 1 year, a 1-, 2-, and 3-line vision loss was significantly higher in the no-show group than in the show group on univariate and multivariate analysis after adjusting for age, sex, race, lens status, and presence of glaucoma and diabetic retinopathy. Conclusions: Non-English-speaking patients and urban-based patients were less likely to present for intravitreal injection appointments during the initial peak of the COVID-19 pandemic. This disparity translated to worse vision outcomes at 6 months and 1 year.

Neighbourhood Disadvantage and Vision Screening Failure Rates: Analysis of a School-Based Vision Program in Baltimore, Maryland

PURPOSE

To investigate the relationship between neighbourhood disadvantage and vision screening failure rates.

METHODS

This analysis uses aggregate data from pre-kindergarten to eighth grade schools participating in a school-based vision programme in Baltimore, Maryland, from 2016 to 2019. Data on number of students screened and number of students who failed vision screening per grade level were recorded for each school. The Area Deprivation Index (ADI) was obtained for each school using the school's ZIP+4 code. The association between vision screening failure rates by grade and school ADI was analysed using negative binomial regression models, adjusted for grade level and accounting for clustering by school.

RESULTS

Nine hundred seventy-two grades across 117 schools were included in this analysis. Median national ADI percentile across the sample was 71 [interquartile range (IQR): 48-85] (100 = most deprived). The median grade-level screening failure rate across the entire sample was 33% [IQR: 26-41%]. School ADI was not associated with vision screening failure rate (incidence rate ratio (IRR) = 1.01 per 10 percentage point increase in ADI, 95% CI: 0.99, 1.03, p = 0.217).

CONCLUSIONS

In this study, there was no association between vision screening failure rates and school ADI. With one in three students failing screening in a high poverty public school district, these findings suggest a high need for vision services across schools in all neighbourhoods. Future work should investigate the impact of students' home ADI and socioeconomic status on vision screening outcomes.

Impact of socioeconomics and race on clinical follow-up and trial enrollment and adherence in cerebral cavernous malformation

OBJECTIVES

Cerebral cavernous malformation (CCM) affects more than a million Americans but advanced care for symptomatic lesions and access to research studies is largely limited to referral academic centers MATERIALS AND METHODS: A cohort of CCM patients screened for research studies at an accredited center of excellence for CCM was analyzed. Demographics, lesion location, history of hemorrhage, insurance type and area of deprivation index (ADI) were collected. Primary outcomes were clinical follow-up within a year from initial evaluation, and enrollment and adherence in clinical trials among eligible subjects RESULTS: A majority (52.8%) of CCM patients evaluated had a high socioeconomic status (SES) (ADI 1-3), and only 11.5% were African American. Patients who had a symptomatic bleed were more likely to follow-up (p=0.01), and those with brainstem lesion were more likely to enroll/adhere in a clinical trial (p=0.02). Rates of clinical follow-up were similar across different ADI groups, insurance coverage and race. Patients who were uninsured/self-paying, and African Americans were more likely to decline/drop from clinical trials (OR 2.4, 95% CI 0.46-10.20 and OR 2.2, 95% CI 0.33-10.75, respectively), but differences were not statistically significant CONCLUSIONS: Access of disadvantaged patients to center of excellence care and research remains limited despite geographic proximity to their community. Patients with lower SES and African Americans are as likely to follow-up clinically, but there were trends of differences in enrollment/adherence in clinical trials. Mitigation efforts should target systemic causes of low access to specialized care among uninsured and African American patients.

Development and Implementation of a Maryland State Program Providing Hospital Payment Incentives for Reduction in Readmission Disparities

BACKGROUND

Social factors are a key determinant of hospital readmission. We describe the development of the country's first statewide policy providing hospitals with financial incentives to reduce readmission disparities.

OBJECTIVE

To describe the development and evaluation of a novel program that measures hospital-level disparity in readmission and rewards hospitals for improvement.

RESEARCH DESIGN

Observational study using inpatient claims.

PARTICIPANTS

Baseline data included 454,372 all-cause inpatient discharges in 2018 and 2019. Of the included discharges, 34.01% involved Black patients, 40.44% involved female patients, 33.1% involved patients covered by Medicaid, and 11.76% involved patients who were readmitted. Mean age was 55.18.

MEASURES

The key measure was the percentage change over time within the hospital in readmission disparity. Readmission disparity was measured using a multilevel model that gauged the association between social factors and readmission risk at a given hospital. Three social factors (Race, Medicaid coverage, and Area Deprivation Index) were combined into an index reflecting exposure to social adversity.

RESULTS

Of the State's 45 acute-care hospitals, 26 exhibited improved disparity performance in 2019.

LIMITATIONS

The program is limited to inpatients within a single state; the analysis does not provide evidence on the causal relationship between the intervention and readmission disparities.

CONCLUSION

This represents the first large-scale effort in the US to link disparities to hospital payment. Because the methodology relies on claims data, it could easily be adopted elsewhere. The incentives are directed to within-hospital disparities, thus mitigating concerns about penalizing hospitals with patients with greater social exposure. This methodology could be used to measure disparity in other outcomes.

Racial and Ethnic Disparities in the Incidence of High-Impact Chronic Pain Among Primary Care Patients with Acute Low Back Pain: A Cohort Study

OBJECTIVE

We assessed whether race or ethnicity was associated with the incidence of high-impact chronic low back pain (cLBP) among adults consulting a primary care provider for acute low back pain (aLBP).

METHODS

In this secondary analysis of a prospective cohort study, patients with aLBP were identified through screening at seventy-seven primary care practices from four geographic regions. Incidence of high-impact cLBP was defined as the subset of patients with cLBP and at least moderate disability on Oswestry Disability Index [ODI >30]) at 6 months. General linear mixed models provided adjusted estimates of association between race/ethnicity and high-impact cLBP.

RESULTS

We identified 9,088 patients with aLBP (81.3% White; 14.3% Black; 4.4% Hispanic). Black/Hispanic patients compared to White patients, were younger and more likely to be female, obese, have Medicaid insurance, worse disability on ODI, and were at higher risk of persistent disability on STarT Back Tool (all P < .0001). At 6 months, more Black and Hispanic patients reported high-impact cLBP (30% and 25%, respectively) compared to White patients (15%, P < .0001, n = 5,035). After adjusting for measured differences in socioeconomic and back-related risk factors, compared to White patients, the increased odds of high-impact cLBP remained statistically significant for Black but not Hispanic patients (adjusted odds ration [aOR] = 1.40, 95% confidence interval [CI]: 1.05-1.87 and aOR = 1.25, 95%CI: 0.83-1.90, respectively).

CONCLUSIONS

We observed an increased incidence of high-impact cLBP among Black and Hispanic patients compared to White patients. This disparity was partly explained by racial/ethnic differences in socioeconomic and back-related risk factors. Interventions that target these factors to reduce pain-related disparities should be evaluated.

CLINICALTRIALS.GOV IDENTIFIER

NCT02647658.

Neighborhood Socioeconomic Status Independently Predicts Outcomes After Mitral Valve Surgery

BACKGROUND

Socioeconomic status has increasingly recognized influence on outcomes after cardiac surgery. However, singular metrics fail to fully capture the socioeconomic context within which patients live, which vary greatly between neighborhoods. We sought to explore the impact of neighborhood-level socioeconomic status on patients undergoing mitral valve surgery in the United States.

METHODS

Adults undergoing first-time, isolated mitral valve surgery were queried from The Society of Thoracic Surgeons Adult Cardiac Surgery Database between 2012 and 2018. Socioeconomic status was quantified using the Area Deprivation Index, a weighted composite including average housing prices, household incomes, education, and employment levels. The associations between regional deprivation, access to mitral surgery, valve repair rates, and outcomes were evaluated using logistic regression.

RESULTS

Among 137,100 patients included, patients with socioeconomic deprivation had fewer elective presentations, more comorbidity burden, and more urgent/emergent surgery. Patients from less disadvantaged areas received operations from higher volume surgeons and had higher repair rates (highest vs lowest quintile: 72% vs 51%, P < .001, more minimally-invasive approach (33% vs 20%, P < .001), lower composite complication rate (42% vs 50%, P < .001), and lower 30-day mortality (1.8% vs 3.9%, P < .001). After hierarchical multivariable adjustment, the Area Deprivation Index significantly predicted 30-day mortality and repair rate (P < .001).

CONCLUSIONS

In a risk-adjusted national analysis of mitral surgery, patients from more deprived areas were less likely to undergo mitral repair and more likely to have complications. Further work at targeting neighborhood-level disparity is important to improving mitral surgical outcomes in the United States.

Physical Therapist Telehealth Delivery at 1 Year Into COVID-19

OBJECTIVE

The purpose of this study was to examine telehealth physical therapy utilization 1 year into the COVID-19 pandemic and identify factors that influence physical therapists' delivery of telehealth in an urban academic medical center.

METHODS

Electronic medical record data were extracted within the dates of interest (March 22, 2021 to May 15, 2021), the proportion of physical therapy sessions delivered via telehealth were identified, and patient characteristics were compared by telehealth volume (0 vs ≥1 session, 1 vs >1 session). Qualitative data also were collected from physical therapists via semi-structured interviews, and a directed content analysis was conducted, informed by the Capability, Opportunity, Motivation, and Behavior model, to identify factors influencing telehealth delivery.

RESULTS

Telehealth was used for 3793 of 8038 (47.2%) physical therapist sessions, and 1028 unique patients had at least 2 physical therapist sessions (without telehealth: 6.6% [n = 68], telehealth once: 39.1% [n = 402], telehealth more than once: 54.3% [n = 558]). Patients without telehealth were older, non-English speaking, had non-commercial insurance, and had at least 1 chronic health condition. Patients with telehealth more than once had a neurologic diagnosis and lived farther from the treating clinic. Capabilities that influenced telehealth delivery were physical therapist clinical skills and knowledge, technical proficiency, telehealth-specific interpersonal skills, and cognitive flexibility. Factors external to physical therapists-including the environment, patient equipment and technology proficiency, physical therapist equipment, clinic factors, and patient and referring provider perspectives-also influenced telehealth delivery. Finally, patient needs and telehealth as a beneficial tool guided physical therapist intention to use telehealth.

CONCLUSION

Sustained telehealth utilization outcomes 1 year into the COVID-19 pandemic and an interaction among physical therapist, patient, and environmental factors support the long-term potential of telehealth physical therapy in an urban academic medical center.

IMPACT

These findings support the long-term potential of telehealth approaches and can be used to inform telehealth physical therapist training programs and clinical implementation, future research, and health policy.

Development, implementation, and evaluation of Teach Back curriculum for community health workers

Teach Back is a commonly used communication method to improve patient understanding and retention of health information. The method has been shown to be effective in improving patient and healthcare system outcomes, including patient health literacy and hospital readmissions. Community health workers (CHWs) are frontline healthcare workers who can help address patient health and social needs associated with hospital readmissions. However, a gap exists in Teach Back curricula and training methods reflecting the scope of work for CHWs. The objective of this training was to provide CHWs with didactic information and skill building practice curriculum focused on the integration of Teach Back into clinical patient interactions, care coordination, and follow-up support. A multidisciplinary team of academic and clinical partners at a large academic health university developed, implemented, and evaluated a 3-week pilot Teach Back training with CHWs through a quality improvement approach. The CHWs reported overall satisfaction with the training and instructors. The academic clinical partnership allowed the training to be tailored to the daily clinical workflow as reflected in the CHWs agreement that the training was relevant and practical. With the repeated exposure to Teach Back each week, the CHWs also reported an increase in confidence and conviction in using Teach Back. Additional implementation and evaluation of the training curriculum for CHWs is needed to gain further insights into Teach Back and training best practices and translation into practice.

The Relationship Between Neighborhood Disadvantage and Kidney Disease Progression in the Chronic Kidney Disease in Children (CKiD) Cohort

RATIONALE & OBJECTIVE

To examine the relationship between neighborhood poverty and deprivation, chronic kidney disease (CKD) comorbidities, and disease progression in children with CKD.

STUDY DESIGN

Observational cohort study.

SETTING & PARTICIPANTS

Children with mild to moderate CKD enrolled in the CKiD (Chronic Kidney Disease in Children) study with available US Census data.

EXPOSURE

Neighborhood poverty and neighborhood disadvantage.

OUTCOME

Binary outcomes of short stature, obesity, hypertension, and health care utilization for cross-sectional analysis; a CKD progression end point (incident kidney replacement therapy [KRT] or 50% loss in estimated glomerular filtration rate), and mode of first KRT for time-to-event analysis.

ANALYTICAL APPROACH

Cross-sectional analysis of health characteristics at time of first Census data collection using logistic regression to estimate odds ratios. Risk for CKD progression was analyzed using a Cox proportional hazard model. Multivariable models were adjusted for race, ethnicity, sex, and family income.

RESULTS

There was strong agreement between family and neighborhood socioeconomic characteristics. Risk for short stature, hospitalization, and emergency department (ED) use were significantly associated with lower neighborhood income. After controlling for race, ethnicity, sex, and family income, the odds of hospitalization (OR, 1.71 [95% CI, 1.08-2.71]) and ED use (OR, 1.56 [95% CI, 1.02-2.40]) remained higher for those with lower neighborhood income. The hazard ratio of reaching the CKD progression outcome for participants living in lower income neighborhoods was significantly increased in the unadjusted model only (1.38 [95% CI, 1.02-1.87]). Likelihood of undergoing a preemptive transplant was decreased with lower neighborhood income (OR, 0.47 [95% CI, 0.24-0.96]) and higher neighborhood deprivation (OR, 0.31 [95% CI, 0.10-0.97]), but these associations did not persist after controlling for participant characteristics.

LIMITATIONS

Limited generalizability, as only those with consistent longitudinal nephrology care were studied.

CONCLUSIONS

Neighborhood-level socioeconomic status (SES) was associated with poorer health characteristics and CKD progression in univariable analysis. However, the relationships were attenuated after accounting for participant-level factors including race. A persistent association of neighborhood poverty with hospitalizations and ED suggests an independent effect of SES on health care utilization, the causes for which deserve additional study.

Clinical characteristics and social determinants of health associated with 30-day hospital readmissions of patients with COVID-19

COVID-19 readmissions are associated with increased patient mortality and healthcare system strain. This retrospective cohort study of PCR-confirmed COVID-19 positive adults (>18 years) hospitalized and readmitted within 30 days of discharge from index admission was performed at eight Atlanta hospitals from March to December 2020. The objective was to describe COVID-19 patient-level demographics and clinical characteristics, and community-level social determinants of health (SDoH) that contribute to 30-day readmissions. Demographics, comorbidities, COVID-19 treatment, and discharge disposition data were extracted from the index admission. ZIP codes were linked to a demographic/lifestyle database interpolating to community-level SDoH. Of 7155 patients with COVID-19, 463 (6.5%) had 30-day, unplanned, all-cause hospital readmissions. Statistically significant differences were not found in readmissions stratified by age, sex, race, or ethnicity. Patients with a high-risk Charlson Comorbidity Index had higher odds of readmission (OR 4.8 (95% CI: 2.1 to 11.0)). Remdesivir treatment and intensive care unit (ICU) care were associated with lower odds of readmission (OR 0.5 (95% CI: 0.4 to 0.8) and OR 0.5 (95% CI: 0.4 to 0.7), respectively). Patients residing in communities with larger average household size were less likely to be readmitted (OR 0.7 (95% CI: 0.5 to 0.9). In this cohort, patients who received remdesivir, were cared for in an ICU, and resided in ZIP codes with higher proportions of residents with increased social support had lower odds of readmission. These patient-level factors and community-level SDoH may be used to identify patients with COVID-19 who are at increased risk of readmission.

Neighborhood Socioeconomic Disadvantage and Disability After Critical Illness

OBJECTIVES

Factors common to socioeconomically disadvantaged neighborhoods, such as low availability of transportation, may limit access to restorative care services for critical illness survivors. Our primary objective was to evaluate whether neighborhood socioeconomic disadvantage was associated with an increased disability burden after critical illness. Our secondary objective was to determine if the effect differed for those discharged to the community compared with those discharged to a facility.

DESIGN

Longitudinal cohort study with linked Medicare claims data.

SETTING

United States.

PATIENTS

One hundred ninety-nine older adults, contributing to 239 ICU admissions, who underwent monthly assessments of disability for 12 months following hospital discharge in 13 different functional tasks from 1998 to 2017.

MEASUREMENTS AND MAIN RESULTS

Neighborhood disadvantage was assessed using the area deprivation index, a 1-100 ranking evaluating poverty, housing, and employment metrics. Those living in disadvantaged neighborhoods (top quartile of scores) were less likely to self-identify as non-Hispanic White compared with those in more advantaged neighborhoods. In adjusted models, older adults living in disadvantaged neighborhoods had a 9% higher disability burden over the 12 months following ICU discharge compared with those in more advantaged areas (rate ratio, 1.09; 95% Bayesian credible interval, 1.02-1.16). In the secondary analysis adjusting for discharge destination, neighborhood disadvantage was associated with a 14% increase in disability burden over 12 months of follow-up (rate ratio, 1.14; 95% credible interval, 1.07-1.21). Disability burden was 10% higher for those living in disadvantaged neighborhoods and discharged home as compared with those discharged to a facility, but this difference was not statistically significant (interaction rate ratio, 1.10; 95% credible interval, 0.98-1.25).

CONCLUSIONS

Neighborhood socioeconomic disadvantage is associated with a higher disability burden in the 12 months after a critical illness. Future studies should evaluate barriers to functional recovery for ICU survivors living in disadvantaged neighborhoods.

Area Deprivation and Medicare Spending for Coronary Artery Bypass Grafting: Insights from Michigan

BACKGROUND

Prior work has established that high socioeconomic deprivation is associated with worse short- and long-term outcomes for coronary artery bypass graft (CABG) patients. The relationship between socioeconomic status and 90-day episode spending is poorly understood. In this observational cohort analysis, we evaluated whether socioeconomically disadvantaged patients were associated with higher expenditures during 90-day episodes of care following isolated CABG.

METHODS

We linked clinical registry data from 8,728 isolated CABG procedures from January 1st, 2012 to December 31st, 2018 to Medicare fee-for-service claims data. Our primary exposure variable was patients in the top decile of the Area Deprivation Index. Linear regression was used to compare risk-adjusted, price-standardized 90-day episode spending for deprived against non-deprived patients, as well as component spending categories: index hospitalization, professional services, post-acute care, and readmissions.

RESULTS

A total of 872 patients were categorized as being in the top decile. Mean 90-day episode spending for the 8,728 patients in the sample was $55,258 (standard deviation = $26,252). Socioeconomically deprived patients had higher overall 90-day spending compared to non-deprived patients ($61,579 vs. $54,557, difference = $3,003, p = 0.001). Spending was higher in socioeconomically deprived patients for index hospitalizations (difference = $1,284, p = 0.005), professional services (difference = $379, p = 0.002) and readmissions (difference = $1,188, p = 0.008). Inpatient rehabilitation was the only significant difference in post-acute care spending (difference = $469, p = 0.011).

CONCLUSIONS

Medicare spending was higher for socioeconomically deprived CABG in Michigan, indicating systemic disparities over and above patient demographic factors.

Hospital Characteristics by Proportion of Patients from Disadvantaged Neighborhoods

Neighborhood disadvantage reflects historic and ongoing systemic injustices. Without addressing these upstream social determinants of health, hospitals may face different risk profiles for important quality metrics. Our objective was to assess differences in hospital characteristics where the proportion of patients residing in severely disadvantaged neighborhoods was high vs low. Using Medicare fee-for-service claims between January 1, 2014 and November 30, 2014 (5,807,499 hospital stays), we calculated Area Disadvantage Share (ADS), the proportion of each hospital's discharges to severely disadvantaged neighborhoods, for 4,528 hospitals. We examined hospital characteristics by distribution of ADS and by risk-adjusted 30-day readmission. Hospitals in the highest decile cared for a higher proportion of Black patients, were more often located in rural areas, and had higher patient risk of 30-day readmission compared to all other deciles. Hospitals face unequal burdens of neighborhood disadvantage, a factor distinct from other social determinants such as rurality.

Coronavirus Disease 2019 and Hospital Readmissions: Patient Characteristics and Socioeconomic Factors Associated With Readmissions in an Urban Safety-Net Hospital System

BACKGROUND

It is not yet known whether socioeconomic factors (ie, social determinants of health) are associated with readmission following hospitalization for coronavirus disease 2019 (COVID-19).

METHODS

We conducted a retrospective cohort study of 6191 adult patients hospitalized with COVID-19 in a large New York City safety-net hospital system between March 1 and June 1, 2020. Associations between 30-day readmission and selected demographic characteristics, socioeconomic factors, prior health care utilization, and relevant features of the index hospitalization were analyzed using a multivariable generalized estimating equation model.

RESULTS

The readmission rate was 7.3%, with a median of 7 days between discharge and readmission. The following were risk factors for readmission: age 65 and older [adjusted odds ratio (aOR): 1.32; 95% confidence interval (CI): 1.13-1.55], history of homelessness, (aOR: 2.03 95% CI: 1.49-2.77), baseline coronary artery disease (aOR: 1.68; 95% CI: 1.34-2.10), congestive heart failure (aOR: 1.34; 95% CI: 1.20-1.49), cancer (aOR: 1.68; 95% CI: 1.26-2.24), chronic kidney disease (aOR: 1.74; 95% CI: 1.46-2.07). Patients' sex, race/ethnicity, insurance, and presence of obesity were not associated with increased odds of readmission. A longer length of stay (aOR: 0.98; 95% CI: 0.97-1.00) and use of noninvasive supplemental oxygen (aOR: 0.68; 95% CI: 0.56-0.83) was associated with lower odds of readmission. Upon readmission, 18.4% of patients required intensive care, and 13.7% expired.

CONCLUSION

We have found some factors associated with increased odds of readmission among patients hospitalized with COVID-19. Awareness of these risk factors, including patients' social determinants of health, may ultimately help to reduce readmission rates.

Association Between Neighborhood Disadvantage and Pediatric Readmissions

OBJECTIVE

Although individual-level social determinants of health (SDH) are known to influence 30-day readmission risk, contextual-level associations with readmission are poorly understood among children. This study explores associations between neighborhood disadvantage measured by Area Deprivation Index (ADI) and pediatric 30-day readmissions.

METHODS

This retrospective cohort study included discharges of patients aged < 20 years from Maryland's 2013-2016 all-payer dataset. The ADI, which quantifies 17 indicators of neighborhood socioeconomic disadvantage within census block groups, is used as a proxy for contextual-level SDH. Readmissions were identified with the 30-day Pediatric All-Condition Readmissions measure. Associations between ADI and readmission were identified with generalized estimating equations adjusted for patient demographics and clinical severity (Chronic Condition Indicator [CCI], Pediatric Medical Complexity Algorithm [PMCA], Index Hospital All Patients Refined Diagnosis Related Groups [APR-DRG]), and hospital discharge volume.

RESULTS

Discharges (n = 138,998) were mostly female (52.7%), publicly insured (55.1%), urban-dwelling (93.0%), with low clinical severity levels (0-1 CCIs [82.3%], minor APR-DRG severity [48.4%]). Overall readmission rate was 4.0%. Compared to the least disadvantaged ADI quartile, readmissions for the most disadvantaged quartile were significantly more likely (aOR 1.19, 95% CI 1.09-1.30). After adjustment, readmissions were associated with public insurance and indicators of medical complexity (higher number of CCIs, complex-chronic disease PMCA, and APR-DRG severity).

CONCLUSION

In this all-payer, statewide sample, living in the most socioeconomically disadvantaged neighborhoods independently predicted pediatric readmission. While the relative magnitude of neighborhood disadvantage was modest compared to medical complexity, disadvantage is modifiable and thus represents an important consideration for prevention and risk stratification efforts.

The Impact of Payment Reform on Pediatric Craniofacial Fracture Care in Maryland

STUDY DESIGN

Retrospective, quasi-experimental difference-in-differences investigation.

OBJECTIVE

Pediatric craniofacial fractures are often associated with substantial morbidity and consumption of healthcare resources. Maryland's All Payer Model (APM) represents a unique case study of the health economics surrounding pediatric craniofacial fractures. The APM implemented global hospital budgets to disincentivize low-value care and encourage preventive, community-based efforts. The objective of this study was to investigate how this reform has impacted pediatric craniofacial fracture care in Maryland.

METHODS

Children (≤18 years) receiving inpatient craniofacial fracture-related care in Maryland between January, 2009 through December, 2016 were investigated. New Jersey was used for comparison. Data were abstracted from the Kid's Inpatient Database (Healthcare Cost and Utilization Project).

RESULTS

Between 2009-2016, 3,655 pediatric patients received inpatient care for craniofacial fractures in Maryland and New Jersey. Prior to APM implementation, around 20% of Maryland patients received care outside of urban teaching hospitals. After APM implementation, less than 6% of patients received care outside of urban teaching hospitals (p = 0.003). Implementation of the APM in Maryland also resulted in fewer pediatric craniofacial fracture admissions than New Jersey, though this only reached borderline significance (adjusted difference-in-differences estimate: -1.1 fewer admissions, 95% confidence interval: -2.1 to 0.0, p = 0.05). Inpatient costs for pediatric craniofacial care and mean did not change post-APM.

CONCLUSIONS

Maryland's APM consolidated pediatric craniofacial fracture inpatient care at urban, teaching hospitals. Inpatient costs and lengths of stay did not change after policy implementation, but overall admission rates decreased. Such considerations are important when considering national expansion of global hospital budgeting.

Assessing and Augmenting Predictive Models for Hospital Readmissions With Novel Variables in an Urban Safety-net Population

BACKGROUND

The performance of existing predictive models of readmissions, such as the LACE, LACE+, and Epic models, is not established in urban safety-net populations. We assessed previously validated predictive models of readmission performance in a socially complex, urban safety-net population, and if augmentation with additional variables such as the Area Deprivation Index, mental health diagnoses, and housing access improves prediction. Through the addition of new variables, we introduce the LACE-social determinants of health (SDH) model.

METHODS

This retrospective cohort study included adult admissions from July 1, 2016, to June 30, 2018, at a single urban safety-net health system, assessing the performance of the LACE, LACE+, and Epic models in predicting 30-day, unplanned rehospitalization. The LACE-SDH development is presented through logistic regression. Predictive model performance was compared using C-statistics.

RESULTS

A total of 16,540 patients met the inclusion criteria. Within the validation cohort (n=8314), the Epic model performed the best (C-statistic=0.71, P<0.05), compared with LACE-SDH (0.67), LACE (0.65), and LACE+ (0.61). The variables most associated with readmissions were (odds ratio, 95% confidence interval) against medical advice discharge (3.19, 2.28-4.45), mental health diagnosis (2.06, 1.72-2.47), and health care utilization (1.94, 1.47-2.55).

CONCLUSIONS

The Epic model performed the best in our sample but requires the use of the Epic Electronic Health Record. The LACE-SDH performed significantly better than the LACE and LACE+ models when applied to a safety-net population, demonstrating the importance of accounting for socioeconomic stressors, mental health, and health care utilization in assessing readmission risk in urban safety-net patients.

Association between neighbourhood deprivation and hypertension in a US-wide Cohort

Background

Socioeconomic status (SES) at the individual level is associated with hypertension risk. Less is known about neighbourhood level SES or how neighbourhood and individual level SES may jointly affect hypertension risk.

Methods

The Area Deprivation Index (ADI) includes 17 census-based measures reflecting neighbourhood SES. The ADI was linked to enrolment addresses of 47 329 women in the Sister Study cohort and categorised as ≤10% (low deprivation), 11%–20%, 21%–35%, 36%–55% and >55% (high deprivation). Hypertension was defined as either high systolic (≥140 mm Hg) or diastolic (≥90 mm Hg) blood pressure or taking antihypertensive medication. We used log binomial regression to investigate the cross-sectional association between ADI and hypertension and evaluated interactions between ADI and race/ethnicity and between ADI and individual SES.

Results

The highest ADI level of >55% was associated with increased prevalence of hypertension, compared with the lowest level of ADI≤10%, in a model adjusted for age, race/ethnicity, educational attainment and annual household income (prevalence ratio=1.26, 95% CI 1.21 to 1.32). We observed interaction between race/ethnicity and ADI (interaction contrast ratio (ICR)=1.9; 95% CI 0.94 to 2.8 comparing non-Hispanic Black women with ADI >55% to non-Hispanic White women with ADI≤10%) and between household income and ADI (ICR 0.38; 95% CI 0.12 to 0.65 comparing participants with household income ≤US$49 999 and ADI>55% to those with household income >US$100 000 and ADI≤10%).

Conclusions

These findings suggest that neighbourhood deprivation measured by ADI may be a risk factor for hypertension and that ADI may act synergistically with race/ethnicity and individual household income to contribute to hypertension.

Relationship between socioeconomic status, exposure to airborne pollutants, and chronic rhinosinusitis disease severity

BACKGROUND

Air pollution directly interacts with airway mucosa, yet little is known about how pollutants affect upper airway inflammation. Studies have shown increased incidence of chronic rhinosinusitis (CRS), rhinitis, and asthma in areas with higher traffic pollution, and these neighborhoods are often associated with lower socioeconomic status (SES). The Area Deprivation Index (ADI) assesses neighborhood-level SES by zip code. The purpose of this study was to assess the relationship between SES and exposure to inhaled pollutants and CRS disease severity.

METHODS

CRS patients with and without nasal polyps (CRSwNP and CRSsNP, respectively) were identified (total patients = 234; CRSwNP patients = 138; CRSsNP patients = 96). Pollutant concentrations, including particulate matter 2.5 (PM_2.5 ), black carbon (BC), and nitrogen dioxide (NO₂ ), were measured at 70 sites within the defined countywide sites and used to estimate patient exposures. SES was measured by ADI state deciles. Disease severity metrics included the modified Lund-Mackay score (LMS), the need for systemic steroids, and functional endoscopic sinus surgery (FESS). Associations were analyzed and identified using linear, logistic, and Poisson multivariable regression.

RESULTS

The distribution of CRSsNP and CRSwNP patients across ADI state deciles was similar. ADI, however, was a predictor of exposure to airborne pollutants (PM_2.5 , BC, and NO₂ ) with a 1.39%, 2.39%, and 2.49% increase in PM_2.5 , BC, and NO₂ per increasing decile increment (p < 0.0001), respectively, which demonstrated a direct correlation between deprived neighborhoods and higher levels of exposure to PM_2.5 , BC, and NO₂ with an increase in pollutant levels per increase in ADI decile. Furthermore, ADI was a predictor for increased steroid treatment.

CONCLUSION

Lower SES predicted higher exposure to air pollution and increased disease severity in patients with CRS as demonstrated by the increased need for steroid treatment.

Man vs. Machine: Comparing Physician vs. Electronic Health Record-Based Model Predictions for 30-Day Hospital Readmissions

BACKGROUND

Electronic health record (EHR)-based readmission risk prediction models can be automated in real-time but have modest discrimination and may be missing important readmission risk factors. Clinician predictions of readmissions may incorporate information unavailable in the EHR, but the comparative usefulness is unknown. We sought to compare clinicians versus a validated EHR-based prediction model in predicting 30-day hospital readmissions.

METHODS

We conducted a prospective survey of internal medicine clinicians in an urban safety-net hospital. Clinicians prospectively predicted patients' 30-day readmission risk on 5-point Likert scales, subsequently dichotomized into low- vs. high-risk. We compared human with machine predictions using discrimination, net reclassification, and diagnostic test characteristics. Observed readmissions were ascertained from a regional hospitalization database. We also developed and assessed a "human-plus-machine" logistic regression model incorporating both human and machine predictions.

RESULTS

We included 1183 hospitalizations from 106 clinicians, with a readmission rate of 20.8%. Both clinicians and the EHR model had similar discrimination (C-statistic 0.66 vs. 0.66, p = 0.91). Clinicians had higher specificity (79.0% vs. 48.9%, p < 0.001) but lower sensitivity (43.9 vs. 75.2%, p < 0.001) than EHR model predictions. Compared with machine, human was better at reclassifying non-readmissions (non-event NRI + 30.1%) but worse at reclassifying readmissions (event NRI - 31.3%). A human-plus-machine approach best optimized discrimination (C-statistic 0.70, 95% CI 0.67-0.74), sensitivity (65.5%), and specificity (66.7%).

CONCLUSION

Clinicians had similar discrimination but higher specificity and lower sensitivity than EHR model predictions. Human-plus-machine was better than either alone. Readmission risk prediction strategies should incorporate clinician assessments to optimize the accuracy of readmission predictions.

Association of Socioeconomic Disadvantage With Long-term Mortality After Myocardial Infarction: The Mass General Brigham YOUNG-MI Registry

Importance

Socioeconomic disadvantage is associated with poor health outcomes. However, whether socioeconomic factors are associated with post-myocardial infarction (MI) outcomes in younger patient populations is unknown.

Objective

To evaluate the association of neighborhood-level socioeconomic disadvantage with long-term outcomes among patients who experienced an MI at a young age.

Design, Setting, and Participants

This cohort study analyzed patients in the Mass General Brigham YOUNG-MI Registry (at Brigham and Women's Hospital and Massachusetts General Hospital in Boston, Massachusetts) who experienced an MI at or before 50 years of age between January 1, 2000, and April 30, 2016. Each patient's home address was mapped to the Area Deprivation Index (ADI) to capture higher rates of socioeconomic disadvantage. The median follow-up duration was 11.3 years. The dates of analysis were May 1, 2020, to June 30, 2020.

Exposures

Patients were assigned an ADI ranking according to their home address and then stratified into 3 groups (least disadvantaged group, middle group, and most disadvantaged group).

Main Outcomes and Measures

The outcomes of interest were all-cause and cardiovascular mortality. Cause of death was adjudicated from national registries and electronic medical records. Cox proportional hazards regression modeling was used to evaluate the association of ADI with all-cause and cardiovascular mortality.

Results

The cohort consisted of 2097 patients, of whom 2002 (95.5%) with an ADI ranking were included (median [interquartile range] age, 45 [42-48] years; 1607 male individuals [80.3%]). Patients in the most disadvantaged neighborhoods were more likely to be Black or Hispanic, have public insurance or no insurance, and have higher rates of traditional cardiovascular risk factors such as hypertension and diabetes. Among the 1964 patients who survived to hospital discharge, 74 (13.6%) in the most disadvantaged group compared with 88 (12.6%) in the middle group and 41 (5.7%) in the least disadvantaged group died. Even after adjusting for a comprehensive set of clinical covariates, higher neighborhood disadvantage was associated with a 32% higher all-cause mortality (hazard ratio, 1.32; 95% CI, 1.10-1.60; P = .004) and a 57% higher cardiovascular mortality (hazard ratio, 1.57; 95% CI, 1.17-2.10; P = .003).

Conclusions and Relevance

This study found that, among patients who experienced an MI at or before age 50 years, socioeconomic disadvantage was associated with higher all-cause and cardiovascular mortality even after adjusting for clinical comorbidities. These findings suggest that neighborhood and socioeconomic factors have an important role in long-term post-MI survival.

The role of neighborhood disadvantage in predicting mortality in patients after transcatheter aortic valve replacement

BACKGROUND

Neighborhoods have a powerful impact on health. Prior investigations into disparities associated with transcatheter aortic valve replacement (TAVR) have focused on race and access to the procedure. We sought to investigate the role of neighborhood disadvantage on mortality post-TAVR.

METHODS

Patients who underwent TAVR at Kaiser Permanente Los Angeles Medical Center between June, 2011 and March, 2019 were evaluated. Neighborhood disadvantage was defined using the area deprivation index, an established and validated index that considers multiple socioeconomic metrics. Cutoffs used for disadvantage were national percentile ≥25% and state decile ≥6. Cox proportional hazards regression analysis was used to assess outcomes.

RESULTS

A total of 668 patients (age 82.1 ± 7.5 years, 49% female) were included, of which 215 (32.2%) were from disadvantaged neighborhoods by state decile, and 167 (25%) by national percentile. At a median follow-up of 18.8 months (interquartile range 8.7-36.5 months), neighborhood disadvantage was independently associated with increased all-cause mortality (National percentile: hazard ratio [HR] 1.91, 95% confidence interval [CI] 1.35-2.69; state decile: HR 1.68, 95% CI 1.21-2.34). On propensity scored analysis, neighborhood disadvantaged remained independently associated with increased all-cause mortality (National percentile: IPTW HR 1.86, 95% CI 1.52-2.28, PSM HR 1.67, 95% CI 1.11-2.51; state decile: IPTW HR 1.55, 95% CI 1.26-1.91, PSM HR 2.0, 95% CI 1.33-2.99).

CONCLUSION

Living in a disadvantaged neighborhood was independently associated with increased mortality post-TAVR on multivariate and propensity score matched analysis. Further investigations into the role of neighborhood disadvantage are needed to address disparities and improve outcomes post-TAVR.

Neighborhood Deprivation and Racial/Ethnic Disparities in Human Immunodeficiency Virus Viral Suppression: A Single-center, Cross-sectional Study in the United States Midwest

Combating disparities is a crucial goal of ongoing efforts to end the human immunodeficiency virus (HIV) epidemic. In a multivariable analysis of a cohort in the Midwestern United States, racial/ethnic disparities in HIV viral suppression were no longer robust after accounting for other sociodemographic factors. Neighborhood deprivation and low income were independently inversely associated with viral suppression.

Evaluating the impact of social deprivation on Press Ganey® Outpatient Medical Practice Survey Scores

Background

Social deprivation has been shown to affect access to health care services, and influences outcomes for a variety of physical and psychological conditions. However, the impact on patient satisfaction remains less clear. The objective of this study was to determine if social deprivation is an independent predictor of patient satisfaction, as measured by the Press Ganey® Outpatient Medical Practice Survey (PGOMPS).

Methods

We retrospectively reviewed unique new adult patient (≥ 18 years of age) seen at a tertiary academic hospital and rural/urban outreach hospitals/clinics between January 2014 and December 2017. Satisfaction was defined a priori as achieving a score above the 33rd percentile. The 2015 Area Deprivation Index (ADI) was used to determine social deprivation (lower score signifies less social deprivation). Univariate and multivariable binary logistic regression were used to determine the impact of ADI on PGOMPS total and provider sub-scores while controlling for variables previously shown to impact scores (wait time, patient age, sex, race, specialty type, provider type, and insurance status).

Results

Univariate analysis of PGOMPS total scores revealed a 4% decrease in odds of patient satisfaction per decile increase in ADI (p < 0.001). Patients within the most deprived quartile were significantly less likely to report satisfaction compared to the least deprived quartile (OR 0.79, p < 0.001). Multivariable analysis revealed that the odds of achieving satisfaction decreased 2% for each decile increase in ADI on the Total Score (p < 0.001), independent of other variables previously shown to impact scores. For PGOMPS Provider Sub-Score, univariate analysis showed that patients in the lowest ADI quartile were significantly less likely be satisfied, as compared to the least deprived quartile (OR 0.77; 95% CI 0.70–0.86; p < 0.001). A 5% decrease in a patient being satisfied was observed for each decile increase in ADI (OR 0.95; 95% CI 0.94–0.96; p < 0.001).

Conclusions

Social deprivation was an independent predictor of outpatient visit dissatisfaction, as measured by the Press Ganey® Outpatient Medical Practice Survey. These results necessitate consideration when developing health care delivery policies that serve to minimize inequalities between patients of differing socioeconomic groups.

Temporary Financial Assistance Decreased Health Care Costs For Veterans Experiencing Housing Instability

Compared with housed people, those experiencing homelessness have longer and more expensive inpatient stays as well as more frequent emergency department visits. Efforts to provide stable housing situations for people experiencing homelessness could reduce health care costs. Through the Supportive Services for Veteran Families program, the Department of Veterans Affairs partners with community organizations to provide temporary financial assistance to veterans who are currently homeless or at imminent risk of becoming homeless. We examined the impact of temporary financial assistance on health care costs for veterans in the Supportive Services for Veteran Families program and found that, on average, people receiving the assistance incurred $352 lower health care costs per quarter than those who did not receive the assistance. These results can inform national policy debates regarding the proper solution to housing instability.

Initial Management of Acute and Chronic Low Back Pain: Responses from Brief Interviews of Primary Care Providers

Background: In April 2017, the American College of Physicians (ACP) published a clinical practice guideline for low back pain (LBP) recommending nonpharmacologic treatments as first-line therapy for acute, subacute, and chronic LBP. Objective: To assess primary care provider (PCP)-reported initial treatment recommendations for LBP following guideline release. Design: Cross-sectional structured interviews. Participants: Convenience sample of 72 PCPs from 3 community-based outpatient clinics in high- or low-income neighborhoods. Approach: PCPs were interviewed about their familiarity with the ACP guideline, and how they initially manage patients with acute/subacute and chronic LBP. Treatment responses were coded as patient education, nonpharmacologic, pharmacologic, or medical specialty referral. PCPs were also asked about their comfort referring patients to nonpharmacologic treatment providers, and about barriers to referring. Responses were assessed using content analysis. Differences in responses were assessed using descriptive statistics. Key results: Interviews were completed between December 2017 and March 2018. Of 72 participating PCPs (50% male; mean years of practice = 13.8), over three-fourths indicated being familiar with the ACP guideline (76%-87% at 3 clinics). For acute LBP, PCPs typically provided advice to stay active (81%) and pharmacologic management (97%; primarily nonsteroidal anti-inflammatory drugs). For chronic LBP, PCPs were more likely to recommend nonpharmacologic treatments than for acute LBP (85% vs. 0%, p < 0.001). The most common nonpharmacologic treatments recommended for chronic LBP were physical therapy (78%), chiropractic care (21%), massage therapy (18%), and acupuncture (17%) (each compared with 0% for acute LBP, all p < 0.001). The cost of nonpharmacologic treatments was perceived as a barrier. However, PCPs working in low-income neighborhood clinics were as likely to recommend nonpharmacologic approaches as those from a high-income neighborhood clinic. Conclusions: While most PCPs indicated they were familiar with the ACP guideline for LBP, nonpharmacologic treatments were not recommended for patients with acute symptoms. Further dissemination and implementation of the ACP guideline are needed.

A comparison of two neighborhood-level socioeconomic indexes in the United States

socioeconomic indexes that capture information about wealth, education, employment, and housing are in wide use in public health. Here we compare the widely used Area Deprivation Index (ADI) to the Yost index. Though they are derived largely from the same data, there are substantial differences between the two. Examination of the geographic areas where the two indexes are most dissimilar suggest that the Yost index has greater face validity and that the ADI is highly sensitive to locations with incomplete census data and with census data containing outliers.

Association of Temporary Financial Assistance With Housing Stability Among US Veterans in the Supportive Services for Veteran Families Program

Importance

Temporary financial assistance (TFA) for housing-related expenses is a key component of interventions to prevent homelessness or to quickly house those who have become homeless. Through the US Department of Veterans Affairs (VA) Supportive Services for Veteran Families (SSVF) program, the department provides TFA to veterans in need of housing assistance.

Objective

To assess the association between TFA and housing stability among US veterans enrolled in the SSVF program.

Design, Setting, and Participants

This retrospective cohort study analyzed data on veterans who were enrolled in the SSVF program at 1 of 203 partner organizations in 49 US states and territories. Some veterans had repeat SSVF episodes, but only the first episodes were included in this analysis. An episode was defined as the period between entry into and exit from the program occurring between October 1, 2015, and September 30, 2018.

Exposures

Receipt of TFA.

Main Outcomes and Measures

The main outcome was stable housing, defined as permanent, independent residence with payment by the program client or housing subsidy after exit from the SSVF program. Covariates included demographic characteristics, monthly income and source, public benefits, health insurance, use of other VA programs for homelessness, comorbidities, and geographic location. Multivariable mixed-effects logistic regression, inverse probability of treatment weighting, and instrumental variable approaches were used.

Results

The overall cohort consisted of 41 969 veterans enrolled in the SSVF program, of whom 29 184 (mean [SD] age, 50.4 [12.9] years; 25 396 men [87.0%]) received TFA and 12 785 (mean [SD] age, 50.0 [13.3] years; 11 229 men [87.8%]) did not receive TFA. The mean (SD) duration of SSVF episodes was 90.5 (57.7) days. A total of 69.5% of SSVF episodes involved receipt of TFA, and the mean (SD) amount of TFA was $6070 ($7272). Stable housing was obtained in 81.4% of the episodes. Compared with those who did not receive TFA, veterans who received TFA were significantly more likely to have stable housing outcomes (risk difference, 0.253; 95% CI, 0.240-0.265). An association between the amount of TFA received and stable housing was also found, with risk differences ranging from 0.168 (95% CI, 0.149-0.188) for those who received $0 to $2000 in TFA to 0.226 (95% CI, 0.203-0.249) for those who received more than $2000 to $4000 in TFA.

Conclusions and Relevance

This study found that receipt of TFA through the SSVF program was associated with increased rates of stable housing. These results may inform national policy debates regarding the optimal solutions to prevent and reduce housing instability.

Impact of Individual versus Geographic-Area Measures of Socioeconomic Status on Health Associations Observed in the Behavioral Risk Factor Surveillance System

Efforts to enhance Electronic Health Record (EHR) data for the study of conditions in which social and economic variables play a prominent role include linking clinical data to sources of external information via patient-specific geocodes. This approach is convenient, but whether geographic-area-level information from secondary sources is adequate as a surrogate of individual-level information is not fully understood. We used Behavioral Risk Factor Surveillance System (BRFSS) epidemiologic data to compare associations of individual income, median aggregate income, and Area Deprivation Index (ADI)-a validated score of U.S. socioeconomic deprivation-with various health outcomes. Median income and ADI assigned according to respondent area of residence were significantly associated with various health outcomes, but with substantially lower effect sizes than those of individual income. Our results show the limited ability of median income and ADI at the level of metropolitan/micropolitan statistical areas versus individual income for use as measures of socioeconomic status.

Evaluation of Changes in Veterans Affairs Medical Centers' Mortality Rates After Risk Adjustment for Socioeconomic Status

IMPORTANCE

Socioeconomic factors are associated with worse outcomes after hospitalization, but neither the Centers for Medicare & Medicaid Services (CMS) nor the Veterans Affairs (VA) health care system adjust for socioeconomic factors in profiling hospital mortality.

OBJECTIVE

To evaluate changes in Veterans Affairs medical centers' (VAMCs') risk-standardized mortality rates among veterans hospitalized for heart failure and pneumonia after adjusting for socioeconomic factors.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, retrospective data were used to assess 131 VAMCs' risk-standardized 30-day mortality rates with or without adjustment for socioeconomic covariates. The study population included 42 892 veterans hospitalized with heart failure and 39 062 veterans hospitalized with pneumonia from January 1, 2012, to December 31, 2014. Data were analyzed from March 1, 2019, to April 1, 2020.

MAIN OUTCOMES AND MEASURES

The primary outcome was 30-day mortality after admission. Socioeconomic covariates included neighborhood disadvantage, race/ethnicity, homelessness, rurality, nursing home residence, reason for Medicare eligibility, Medicaid and Medicare dual eligibility, and VA priority.

RESULTS

The study population included 42 892 veterans hospitalized with heart failure (98.2% male; mean [SD] age, 71.9 [11.4] years) and 39 062 veterans hospitalized with pneumonia (96.8% male; mean [SD] age, 71.0 [12.4] years). The addition of socioeconomic factors to the CMS models modestly increased the C statistic from 0.77 (95% CI, 0.77-0.78) to 0.78 (95% CI, 0.78-0.78) for 30-day mortality after heart failure and from 0.73 (95% CI, 0.72-0.73) to 0.74 (95% CI, 0.73-0.74) for 30-day mortality after pneumonia. Mortality rates were highly correlated (Spearman correlations of ≥0.98) in models that included or did not include socioeconomic factors. With the use of the CMS model for heart failure, VAMCs in the lowest quintile had a mean (SD) mortality rate of 6.0% (0.4%), those in the middle 3 quintiles had a mean (SD) mortality rate of 7.2% (0.4%), and those in the highest quintile had a mean (SD) mortality rate of 8.8% (0.6%). After the inclusion of socioeconomic covariates, the adjusted mean (SD) mortality was 6.1% (0.4%) for hospitals in the lowest quintile, 7.2% (0.4%) for those in the middle 3 quintiles, and 8.6% (0.5%) for those in the highest quintile. The mean absolute change in rank after socioeconomic adjustment was 3.0 ranking positions (interquartile range, 1.0-4.0) among hospitals in the highest quintile of mortality after heart failure and 4.4 ranking positions (interquartile range, 1.0-6.0) among VAMCs in the lowest quintile. Similar findings were observed for mortality rankings in pneumonia and after inclusion of clinical covariates.

CONCLUSIONS AND RELEVANCE

This study suggests that adjustments for socioeconomic factors did not meaningfully change VAMCs' risk-adjusted 30-day mortality rates for veterans hospitalized for heart failure and pneumonia. The implications of such adjustments should be examined for other quality measures and health systems.

Neighborhood-Level Social Disadvantage and Risk of Delirium Following Major Surgery

BACKGROUND/OBJECTIVES

Delirium is a common postoperative complication associated with prolonged length of stay, hospital readmission, and premature mortality. We explored the association between neighborhood-level characteristics and delirium incidence and severity, and compared neighborhood- with individual-level indicators of socioeconomic status in predicting delirium incidence.

DESIGN

A prospective observational cohort of patients enrolled between June 18, 2010, and August 8, 2013. Baseline interviews were conducted before surgery, and delirium/delirium severity was evaluated daily during hospitalization. Research staff evaluating delirium were blinded to baseline cognitive status.

SETTING

Two academic medical centers in Boston, MA.

PARTICIPANTS

A total of 560 older adults, aged 70 years or older, undergoing major noncardiac surgery.

INTERVENTION

The Area Deprivation Index (ADI) was used to characterize each neighborhood's socioeconomic disadvantage.

MEASUREMENTS

Delirium was assessed using the Confusion Assessment Method (CAM) long form. Delirium severity was calculated using the highest value of CAM Severity score (CAM-S) occurring during daily hospital assessments (CAM-S Peak).

RESULTS

Residing in the most disadvantaged neighborhoods (ADI > 44) was associated with a higher risk of incident delirium (12/26; 46%), compared with the least disadvantaged neighborhoods (122/534; 23%) (risk ratio (RR) (95% confidence interval (CI)) = 2.0 (1.3-3.1). The CAM-S Peak score was significantly associated with ADI (Spearman rank correlation, ρ = 0.11; P = .009). Mean CAM-S Peak scores generally rose from 3.7 to 5.3 across levels of increasing neighborhood disadvantage. The RR (95% CI) values associated with individual-level markers of socioeconomic status and cultural background were: 1.2 (0.9-1.7) for education of 12 years or less; 1.3 (0.8-2.1) for non-White race; and 1.7 (1.1-2.6) for annual household income of less than $20,000. None of these individual-level markers exceeded the ADI in terms of effect size or significance for prediction of delirium risk.

CONCLUSIONS

Neighborhood-level makers of social disadvantage are associated with delirium incidence and severity, and demonstrated an exposure-response relationship. Future studies should consider contextual-level metrics, such as the ADI, as risk markers of social disadvantage that can help to guide delirium treatment and prevention.

Study of lipoprotein(a) and its impact on atherosclerotic cardiovascular disease: Design and rationale of the Mass General Brigham Lp(a) Registry

Lipoprotein(a) [Lp(a)] is independently associated with atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Elevated Lp(a) affects approximately one in five individuals and meaningfully contributes to the residual cardiovascular risk in individuals with otherwise well-controlled risk factors. With targeted therapies in the therapeutic pipeline, there is a need to further characterize the clinical phenotypes and outcomes of individuals with elevated levels of this unique biomarker. The Mass General Brigham Lp(a) Registry will be built from the longitudinal electronic health record of two large academic medical centers in Boston, Massachusetts, to develop a detailed cohort of patients who have had their Lp(a) measured. In combination with structured data sources, clinical documentation will be analyzed using natural language processing techniques to accurately characterize baseline characteristics. Important outcome measures including all-cause mortality, cardiovascular mortality, and cardiovascular events will be available for analysis. Approximately 30 000 patients who have had their Lp(a) tested within the Mass General Brigham system from January 2000 to July 2019 will be included in the registry. This large Lp(a) cohort will provide meaningful observational data regarding the differential risk associated with Lp(a) values and cardiovascular disease. With a new frontier of targeted Lp(a) therapies on the horizon, the Mass General Brigham Lp(a) Registry will help provide a deeper understanding of Lp(a)'s role in long term cardiovascular outcomes.

Racial and Ethnic Disparities in COVID-19: Evidence from Six Large Cities

As of June 2020, the coronavirus pandemic has led to more than 2.3 million confirmed infections and 121 thousand fatalities in the USA, with starkly different incidence by race and ethnicity. Our study examines racial and ethnic disparities in confirmed COVID-19 cases across six diverse cities-Atlanta, Baltimore, Chicago, New York City, San Diego, and St. Louis-at the ZIP code level (covering 436 "neighborhoods" with a population of 17.7 million). Our analysis links these outcomes to six separate data sources to control for demographics; housing; socioeconomic status; occupation; transportation modes; health care access; long-run opportunity, as measured by income mobility and incarceration rates; human mobility; and underlying population health. We find that the proportions of Black and Hispanic residents in a ZIP code are both positively and statistically significantly associated with COVID-19 cases per capita. The magnitudes are sizeable for both Black and Hispanic, but even larger for Hispanic. Although some of these disparities can be explained by differences in long-run opportunity, human mobility, and demographics, most of the disparities remain unexplained even after including an extensive list of covariates related to possible mechanisms. For two cities-Chicago and New York-we also examine COVID-19 fatalities, finding that differences in confirmed COVID-19 cases explain the majority of the observed disparities in fatalities. In other words, the higher death toll of COVID-19 in predominantly Black and Hispanic communities mostly reflects higher case rates, rather than higher fatality rates for confirmed cases.