Risk of Adverse Financial Events in Patients With Cancer: Evidence From a Novel Linkage Between Cancer Registry and Credit Records

PURPOSE Although financial toxicity is a growing cancer survivorship issue, no studies have used credit data to estimate the relative risk of financial hardship in patients with cancer versus individuals without cancer. We conducted a population-based retrospective matched cohort study using credit reports to investigate the impact of a cancer diagnosis on the risk of adverse financial events (AFEs). METHODS Western Washington SEER cancer registry (cases) and voter registry (controls) records from 2013 to 2018 were linked to quarterly credit records from TransUnion. Controls were age-, sex-, and zip code–matched to cancer cases and assigned an index date corresponding to the case's diagnosis date. Cases and controls experiencing past-due credit card payments and any of the following AFEs at 24 months from diagnosis or index were compared, using two-sample z tests: third-party collections, charge-offs, tax liens, delinquent mortgage payments, foreclosures, and repossessions. Multivariate logistic regression models were used to evaluate the association of cancer diagnosis with AFEs and past-due credit payments. RESULTS A total of 190,722 individuals (63,574 cases and 127,148 controls, mean age 66 years) were included. AFEs (4.3% v 2.4%, P < .0001) and past-due credit payments (2.6% v 1.9%, P < .0001) were more common in cases than in controls. After adjusting for age, sex, average baseline credit line, area deprivation index, and index/diagnosis year, patients with cancer had a higher risk of AFEs (odds ratio 1.71; 95% CI, 1.61 to 1.81; P < .0001) and past-due credit payments (odds ratio 1.28; 95% CI, 1.19 to 1.37; P < .0001) than controls. CONCLUSION Patients with cancer were at significantly increased risk of experiencing AFEs and past-due credit card payments relative to controls. Studies are needed to investigate the impact of these events on treatment decisions, quality of life, and clinical outcomes.

population level study of SARS-CoV-2 prevalence amongst people experiencing homelessness in Wales, UK

IntroductionPrior research into the prevalence of SARS-CoV-2 infection amongst people experiencing homelessness (PEH) largely relates to people in communal forms of temporary accommodation in contexts where this type of accommodation remained a major part of the response to homelessness during the COVID-19 pandemic. Little is known about the prevalence of SARS-CoV-2 amongst PEH more broadly, and in a policy and practice context that favoured self-contained accommodation, such as Wales, UK. ObjectiveDescribe the prevalence of SARS-CoV-2 amongst PEH in Wales, UK, using routinely collected administrative data from the Secure Anonymised Information Linkage Databank. MethodsRoutinely collected data were used to identify PEH in Wales between 1st March 2020 and 1st March 2021. Using SARS-CoV-2 pathology testing data, prevalence rates were generated for PEH and three comparator groups: (1) the not-homeless population; (2) a cohort `exact matched' for age, sex, local authority and area deprivation; and (3) a matched comparison group created using these same variables and Propensity Score Matching (PSM). Three logistic regressions were run on samples containing each of the comparator groups to explore the effect of experiencing homelessness on testing positive for SARS-CoV-2. ResultsThe prevalence of SARS-CoV-2 infection amongst PEH was 5.0%, compared to the not-homeless population at 5.6%. For the exact matched and PSM match comparator groups, prevalence was 6.9% and 6.7%, respectively. Logistic regression found that SARS-CoV-2 infection was 0.9 times less likely amongst PEH compared to people not experiencing homelessness from the general population. The odds of SARS-CoV-2 infection for PEH was 0.75 and 0.73 where the `not-homeless' comparators were from the exact match and PSM samples, respectively. ConclusionOur analysis revealed that a year into the COVID-19 pandemic, the prevalence of SARS-CoV-2 amongst PEH in Wales was lower than the general population. A policy response to homelessness that moved away from communal accommodation may be partly responsible for the reduced SAR-CoV-2 infection amongst PEH.

Neighborhood Deprivation and Incident Alzheimer's Disease: A Regional Cohort Study of Electronic Medical Records

The prevalence of Alzheimer’s disease (AD) is anticipated to increase drastically. Neighborhood socioeconomic position (SEP) has been related to multiple processes of health. Understanding whether SEP is related to AD can inform who is at greatest risk of developing this disease. We analyzed electronic medical records of 394892 patients from the two largest health systems in Northeast Ohio to evaluate the relationship between Ohio Area Deprivation Index quintiles (defined at the census tract level) and hazard for a composite outcome of AD diagnosis or primary AD death. We included residents of Cuyahoga and neighboring counties, and used the first outpatient visit beyond age 60 occurring between 2005 and 2015 as study baseline. Outcome data were censored at the earlier of a) the beginning of any 3-year time period without visits or b) non-AD death. We estimated a Cox proportional hazards regression model, adjusting ADI quintile effects for the interaction between age at baseline, sex and race as well as birth year. We used quadratic terms for continuous predictors. After adjusting for these factors, ADI quintile was significantly related (χ2 = 83.0 on 4 d.f.; p &lt; 0.0001) to the composite time-to-event outcome. Compared to the lowest-deprivation quintile, ADI quintiles 4 (adjusted hazard ratio [95% confidence interval]: 1.18 [1.10, 1.26]) and 5 (1.37 [1.28, 1.47]) had significantly higher hazard for the composite outcome. In conclusion, neighborhood deprivation may be a risk factor for AD independent of demographic factors. Preventive efforts should target individuals living in neighborhoods with high levels of deprivation.

Inequalities in excess premature mortality in England during the COVID-19 pandemic: a cross-sectional analysis of cumulative excess mortality by area deprivation and ethnicity

ObjectivesTo examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity.DesignA statistical model to estimate increased mortality in population subgroups during the COVID-19 pandemic by comparing observed with expected mortality in each group based on trends over the previous 5 years.SettingInformation on deaths registered in England since 2015 was used, including age, sex, area of residence and cause of death. Ethnicity was obtained from Hospital Episode Statistics records linked to death data.ParticipantsPopulation study of England, including all 569 824 deaths from all causes registered between 21 March 2020 and 26 February 2021.Main outcome measuresExcess mortality in each subgroup over and above the number expected based on trends in mortality in that group over the previous 5 years.ResultsThe gradient in excess mortality by area deprivation was greater in the under 75s (the most deprived areas had 1.25 times as many deaths as expected, least deprived 1.14) than in all ages (most deprived had 1.24 times as many deaths as expected, least deprived 1.20). Among the black and Asian groups, all area deprivation quintiles had significantly larger excesses than white groups in the most deprived quintiles and there were no clear gradients across quintiles. Among the white group, only those in the most deprived quintile had more excess deaths than deaths directly involving COVID-19.ConclusionThe COVID-19 pandemic has widened inequalities in premature mortality by area deprivation. Among those under 75, the direct and indirect effects of the pandemic on deaths have disproportionately impacted ethnic minority groups irrespective of area deprivation, and the white group the most deprived areas. Statistics limited to deaths directly involving COVID-19 understate the pandemic’s impact on inequalities by area deprivation and ethnic group at younger ages.

Impact of Neighborhood Socioeconomic Disadvantage on Staffing Hours in US Nursing Homes

Severe socioeconomic disadvantage in neighborhoods where nursing homes (NH) are located may be an important contributor to disparities in resident quality of care. Disadvantaged neighborhoods may have undesirable attributes (e.g., poor public transit) that make it challenging to recruit and retain qualified staff. Lower NH staffing could subsequently leave residents vulnerable to adverse events. Thus, the purpose of this study was to evaluate whether NHs located in socioeconomically disadvantaged neighborhoods had lower healthcare provider staffing levels. We linked publicly available NH data geocoded at the Census block-group level with the Area Deprivation Index, a measure of neighborhood socioeconomic factors including poverty, employment, and housing quality (percentiles: 1-100). Consistent with prior literature on threshold effects of neighborhood poverty on outcomes, we characterized NHs as being located in a disadvantaged neighborhood if the census-block group ADI score was ≥85/100. We used generalized estimating equations clustered at the county level with fixed effects for state and rural location to evaluate relationships between ADI score and staffing. NHs located in socioeconomically disadvantaged neighborhoods had 12.1% lower levels of staffing for registered nurses (mean: 5.8 fewer hours/100 resident-days, 95% CI: 4.4-7.1 hours), 1.2% lower for certified nursing assistants (2.9 fewer hours/100 resident days; 95% CI 0.6-5.1 hours), 20% lower for physical therapists (1.4 fewer hours/100 resident-days; 95% CI 1.1-1.8 hours), and 19% lower for occupational therapists (1.3 fewer hours/100 resident-days; 95% CI 1.0-1.6 hours). These findings highlight disparities that could be targeted with policy interventions focused on recruiting and retaining staff in socioeconomically disadvantaged neighborhoods.

Area Deprivation Share: A New Measure of Social Need Faced by Hospitals Serving Older Adults

Medicare’s Hospital Readmissions Reduction Program (HRRP) places disproportionate penalties on hospitals serving populations with complex medical and social needs. Without measures to identify the social need intensity of populations cared for by these hospitals, the HRRP cannot account for these risk factors, leading to burdensome penalties that may inadvertently hinder the ability of such hospitals to care for vulnerable populations. The objective of this study is to characterize the social need intensity of US hospital acute care populations. Using the Area Deprivation Index (ADI), a validated measure that ranks neighborhood socioeconomic disadvantage based on income, employment, housing, and education factors, we determined an “Area Deprivation Share” (ADS) for hospitals with 25 or more discharges using 100% of national Medicare claims data from 2013-2014. Hospital ADS is the proportion of qualifying discharges residing in the most disadvantaged neighborhoods (ADI ≥ 80th percentile) out of all qualifying discharges during the study period. Of 4,603 hospitals, median ADS was 17% (Interquartile Range: 6% - 34%). Hospitals in the highest quintile of ADS (39% to 100%), were more frequently located in small towns or isolated rural areas (52.6%, comparted to 24.2% in lower quintiles) and served a higher percentage of Black patients (19.0%, comparted to 9.7% in lower quintiles). ADS is a potential tool to inform future Medicare policy decisions. Additional research will inform how hospitals target care processes to meet the needs of older adults with complex social needs. Further study can also explore overlapping disadvantage domains of socioeconomic status, race, and rurality.

Neurodegenerative brain changes are associated with area deprivation in the United Kingdom: findings from the Brains for Dementia Research study

Socioeconomic disadvantage is associated with greater risk of dementia. This has been theorised to reflect inequalities in cognitive reserve, healthcare access, lifestyle, and other health factors which may contribute to the clinical manifestation of dementia. We aimed to assess whether area deprivation in the United Kingdom was associated with greater risk or severity of the specific neurodegenerative diseases which lead to dementia in a multi-centre cohort with autopsy assessment. Participants underwent clinical assessment prior to brain tissue donation post-mortem. Each then underwent detailed, standardised neuropathological assessment. National area deprivation statistics were derived for each participant’s neighbourhood, for use as a predictor in binary and ordinal logistic models assessing the respective presence and severity of staging of key neuropathological changes, adjusting for theorised confounders. Individuals from among the 20% most deprived neighbourhoods in the United Kingdom had significantly higher neurofibrillary tangle and neuritic plaque staging, and increased risk of cerebral amyloid angiopathy. These findings were not explained by a greater risk of diabetes or hypertension, APOE genotype, alcohol misuse or tobacco smoking, sex, or age differences. A sensitivity analysis conditioning on baseline cognitive impairment did not meaningfully change the observed association. Socioeconomic disadvantage may contribute to dementia incidence through a greater severity of specific neuropathological changes (neurofibrillary tangles, neuritic plaques, and cerebral amyloid angiopathy), independent of other indirect influences. Mechanisms through which deprivation is associated with these require further exploration.

Factors Driving High-Need High-Risk Vulnerable Veterans Use of Outpatient Healthcare

Using predictive analytic modeling, the Veterans Affairs (VA) Geriatrics and Extended Care Data Analysis Center (GECDAC) identified vulnerable “High-Need High-Risk” (HNHR) Veterans, as requiring more support and services. We sought to identify variables linked with utilization of our outpatient HNHR C4 clinic offering Comprehensive Geriatric Assessment, Care Planning, Care Coordination, and Co-management". Of 724 HNHR Veterans contacted, 531 were reached and invited to participate; 193 were not reached, 326 were reached but declined the C4 clinic, 205 attended the clinic. We compared these groups. Independent variables were organized using Anderson’s behavioral model into predisposing (age, gender, race, ethnicity), enabling (drive time, service eligibility, Area Deprivation Index, marital status), and need factors (mental health cognitive condition, ambulatory care sensitive conditions, NOSOS, JFI, CAN, etc.). C4 enrollment acceptance was the outcome. Results showed that compared to patients who declined, HNHR veterans who attended C4 clinic had more chronic health conditions(p&lt;0.01), more service eligibility(p=0.01), more driving time to the closest VA clinic(p=0.01), and more were married (p=0.01). Patients who declined C4 clinic might have greater barriers to care access. Accessing needed healthcare among HNHR older adults maybe impacted more by enabling factors that allow the individual to seek care if needed and are the resources that may facilitate access to services, rather than need factors, which include individuals' perceptions of their health and functional state, and healthcare needs assessed by professionals. More social and intermediary determinants of health should be incorporated as enabling factors into models striving to understand drivers of healthcare use.