Comparing the use of aggressive end-of life care among frail and non-frail patients with cancer using a claims-based frailty index.

INTRODUCTION: Despite mounting consensus that end-of-life (EOL) care for patients with cancer should focus on improving quality of life, many patients continue to receive aggressive, disease-oriented treatment until death. Within this group, patients with increased frailty may be at higher risk of adverse treatment-related outcomes. We therefore examined the relationship between degree of frailty and receipt of aggressive EOL care among Medicare-insured patients with cancer in Ohio. MATERIALS AND METHODS: From the Ohio Cancer Incidence Surveillance System (OCISS) linked with Medicare claims, we identified patients diagnosed with breast, colorectal, lung, or prostate cancer who died between 2012 and 2016. Frailty was operationalized using a validated claims-based frailty index. Six quality indicators reflecting receipt of aggressive EOL care were identified from claims: (1) any cancer-directed treatment, (2) >1 emergency department (ED) visit, (3) >1 hospital admission, (4) any intensive care unit (ICU) admission in the last 30 days of life, (5) entry to hospice in the last three days of life, and (6) in-hospital mortality. Multivariable logistic regression analysis was performed to control for demographic factors, Medicare and Medicaid dual enrollment, and cancer type and stage in the relationship between frailty and aggressive EOL care. RESULTS: Overall, 31,465 patients met selection criteria. Patients with moderate/severe frailty were less likely than non-/pre-frail patients to receive any aggressive EOL care (adjusted odds ratio [aOR] 0.92 [95% confidence interval 0.86-0.99]). This group was also less likely to undergo cancer-directed treatment in their last 30 days or to enter hospice in their last three days. Increasing frailty was associated with lower odds of admission to the ICU in the last 30 days of life (mild frailty: aOR 0.88 [0.83-0.94]; moderate/severe frailty: aOR 0.85 [0.78-0.92]) or of dying in-hospital (mild frailty: 0.85 [0.79-0.91]; moderate/severe frailty: aOR 0.74 [0.67-0.82]), but higher odds of having >1 ED visit in the last 30 days of life (mild frailty: aOR 1.43 [1.32-1.53]; moderate/severe frailty: aOR 1.61 [1.47-1.77]). DISCUSSION: These findings suggest the need for more explicit discussion of emergency care seeking for patients with cancer at the end of life.

Nationwide disparities in transportation related delays to care experienced by children with frequent ear infections.

BACKGROUND: Acute otitis media (AOM), or ear infection, is the most common reason for pediatric medical visits in the United States [1]. Additionally, transportation barriers are a significant driver of missed and delayed care across medical specialties [2,3]. Yet, the role of transportation barriers in impeding access for children with frequent ear infections (FEI) has not been investigated. Assessing the prevalence of transportation barriers across sociodemographic groups may help clinicians improve outcomes for children with FEI. METHODS: A retrospective analysis of the U.S. National Health Interview Survey was completed to examine associations between sociodemographic characteristics among children with FEI and transportations barriers to seeking care between 2011 and 2018. RESULTS: Multivariable logistic regression found that income level, insurance status, and health status were linked to disparities in transportation barriers among children with FEI. Those in the middle (aOR 3.00, 95% CI 1.77-5.08, p < 0.001) and lowest income brackets (aOR 6.33, 95% CI 3.80, p < 0.001), who were publicly insured (aOR 3.24, 95% CI 2.00-5.23, p < 0.001) or uninsured (aOR 3.46, 95% CI 1.84-6.51, p < 0.001), and with Poor to Fair health status were more likely to face transportation delays than patients who were in the highest income bracket, privately insured, or had Good to Excellent health status. CONCLUSION: Children with FEI from families that were lower-income, less insured, and less healthy faced more transportation barriers when accessing care than their counterparts. Future interventions to improve health-related transportation should be targeted toward these patient subgroups to reduce gaps in outcomes.

Sociodemographic disparities in the use of health information technology by a national sample of head and neck cancer patients.

BACKGROUND: Quantifying disparities in health information technology (HIT) use among head and neck cancer (HNC) patients may help clinicians reduce care gaps and improve outcomes. METHODS: Relationships between HIT usage and sociodemographic characteristics were studied for adults with HNC between 2011 and 2018 through a retrospective analysis of the US National Health Interview Survey. RESULTS: Multivariate logistic regression indicated HIT usage disparities based on race, age, educational attainment, and insurance status. Black (aOR 0.07, 95% CI 0.01-0.52, P = 0.010), uninsured (aOR 0.21, 95% CI 0.06-0.79, P = 0.022), and senior patients (aOR 2.72, 95% CI 1.55-4.80, P < 0.001) emailed providers less than non-Hispanic White, privately insured, and middle-aged (45-64) patients, respectively. Similar disparities were found among patients searching for health information, scheduling appointments, and filling prescriptions online. CONCLUSION: Black, older, less educated, and un/underinsured HNC patients use HIT less than their counterparts. Reducing these inequities may help improve their outcomes.

Prevalence, trends, and demographic characteristics associated with self-reported financial stress among head and neck cancer patients in the United States of America.

BACKGROUND: Understanding the economic burden imposed by head and neck cancer diagnoses essential to contextualize healthcare decision-making for these patients. METHODS: A retrospective, cross-sectional analysis of the US National Health Interview Survey was performed between 2013 and 2018. Demographic and socioeconomic characteristics of adult head and neck cancer patients were analyzed in relation to survey responses related to financial stress factors. RESULTS: Among 710 head and neck cancer patients, 21.39% (95% Cl, 17.69%-25.09%) reported difficulty paying medical bills within the previous 12 months. Multivariable logistic regression revealed insurance status [aOR 2.17 (95% CI, 1.15-4.07), p < 0.001] and poverty status [aOR 2.55 (95% CI, 1.48-4.37), p = 0.017] to be significantly associated with difficulty paying medical bills. CONCLUSION: A large proportion of HNC patients may experience financial stress related not only to out-of-pocket health care costs, but also exogenous financial challenges. These findings suggest that a significant proportion of HNC patients may experience financial stress related not only to out-of-pocket health care costs, but also exogenous financial challenges. Such barriers may impede patients' ability to access and adhere to treatment or force detrimental tradeoffs between health care and other essential needs.