Why location matters: Associations between county-level characteristics and availability of NCORP and NCI sites.

BACKGROUND: The majority of patients with cancer seek care at community oncology sites; however, most clinical trials are available at National Cancer Institute (NCI)-designated sites. While the NCI National Cancer Oncology Research Program (NCORP) was designed to address this problem, little is known about the county-level characteristics of NCORP site locations. METHODS: This cross-sectional analysis determined the association between availability of NCORP or NCI sites and county-level characteristic theme percentile scores from the CDC's Social Vulnerability Index themes. Health Resources and Services Administration's Area Health Resource Files were used to determine contiguous counties. We estimated risk ratios and 95% confidence intervals (CI) using modified Poisson regression models to evaluate the association between county-level characteristics and site availability within singular and singular & contiguous counties. RESULTS: Of 3141 included counties, 14% had an NCORP, 2% had an NCI, and 1% had both sites. Among singular counties, for a standard deviation (SD) increase in the racial and ethnic theme score there was a 22% higher likelihood of NCORP site availability (95% CI 1.10-1.36); for a SD increase in the socioeconomic status theme score there was a 24% lower likelihood of NCORP site availability (95% CI 0.67-0.87). Associations were of smaller magnitude when including contiguous counties. NCI sites were located in more vulnerable counties. CONCLUSION(S): NCORP sites were more often in racially diverse counties, and less often in socioeconomically vulnerable counties. Research is needed to understand how clinical trial representation will increase if NCORP sites strategically increase their locations in more vulnerable counties.

Understanding the financial cost of cancer clinical trial participation.

BACKGROUND: Though financial hardship is a well-documented adverse effect of standard-of-care cancer treatment, little is known about out-of-pocket costs and their impact on patients participating in cancer clinical trials. This study explored the financial effects of cancer clinical trial participation. METHODS: This cross-sectional analysis used survey data collected in December 2022 and May 2023 from individuals with cancer previously served by Patient Advocate Foundation, a nonprofit organization providing social needs navigation and financial assistance to US adults with a chronic illness. Surveys included questions on cancer clinical trial participation, trial-related financial hardship, and sociodemographic data. Descriptive and bivariate analyses were conducted using Cramer's V to estimate the in-sample magnitude of association. Associations between trial-related financial hardship and sociodemographics were estimated using adjusted relative risks (aRR) and corresponding 95% confidence intervals (CI) from modified Poisson regression models with robust standard errors. RESULTS: Of 650 survey respondents, 18% (N = 118) reported ever participating in a cancer clinical trial. Of those, 47% (n = 55) reported financial hardship as a result of their trial participation. Respondents reporting trial-related financial hardship were more often unemployed or disabled (58% vs. 43%; V = 0.15), Medicare enrolled (53% vs. 40%; V = 0.15), and traveled >1 h to their cancer provider (45% vs. 17%; V = 0.33) compared to respondents reporting no hardship. Respondents who experienced trial-related financial hardship most often reported expenses from travel (reported by 71% of respondents), medical bills (58%), dining out (40%), or housing needs (40%). Modeling results indicated that respondents traveling >1 h vs. ≤30 min to their cancer provider had a 2.2× higher risk of financial hardship, even after adjusting for respondent race, income, employment, and insurance status (aRR = 2.2, 95% CI 1.3-3.8). Most respondents (53%) reported needing $200-$1000 per month to compensate for trial-related expenses. Over half (51%) of respondents reported less willingness to participate in future clinical trials due to incurred financial hardship. Notably, of patients who did not participate in a cancer clinical trial (n = 532), 13% declined participation due to cost. CONCLUSION: Cancer clinical trial-related financial hardship, most often stemming from travel expenses, affected almost half of trial-enrolled patients. Interventions are needed to reduce adverse financial participation effects and potentially improve cancer clinical trial participation.

Dedicated financial hardship screening adds value to routine distress screening among gynecologic cancer patients.

OBJECTIVES: To evaluate existing distress screening to identify patients with financial hardship (FH) compared to dedicated FH screening and assess patient attitudes toward FH screening. METHODS: We screened gynecologic cancer patients starting a new line of therapy. Existing screening included: (1) Moderate/severe distress defined as Distress Thermometer score ≥ 4, (2) practical concerns identified from Problem Checklist, and (3) a single question assessing trouble paying for medications. FH screening included: (1) Comprehensive Score for Financial Toxicity (COST) tool and (2) 10-item Financial Needs Checklist to guide referrals. FH was defined as COST score < 26. We calculated sensitivity (patients with moderate/severe distress + FH over total patients with FH) and specificity (patients with no/mild distress + no FH over total patients with no FH) to assess the extent distress screening could capture FH. Surveys and exit interviews assessed patient perspectives toward screening. RESULTS: Of 364 patients screened for distress, average age was 62 years, 25% were Black, 45% were Medicare beneficiaries, 32% had moderate/severe distress, 15% reported ≥1 practical concern, and 0 reported trouble paying for medications. Most (n = 357, 98%) patients also completed FH screening: of them, 24% screened positive for FH, 32% reported ≥1 financial need. Distress screening had 57% sensitivity and 77% specificity for FH. Based on 79 surveys and 43 exit interviews, FH screening was acceptable with feedback to improve the timing and setting of screening. CONCLUSIONS: Dedicated FH screening was feasible and acceptable, but sensitivity was low. Importantly, 40% of women with FH would not have been identified with distress screening alone.

Accuracy of Cancer Registry Primary Payer Information and Implications for Policy Research.

BACKGROUND: Cancer registry-based "primary payer at diagnosis" (PPDx) data are commonly used to evaluate the effect of insurance on cancer care outcomes, yet little is known about how well they capture Medicaid or Medicare enrollment. METHODS: We linked the National Cancer Institute's Surveillance, Epidemiology, and End Results registry data to monthly Centers for Medicare and Medicaid Services (CMS) Medicaid and Medicare enrollment records, state-year Medicaid policy, and managed care enrollment. We selected adults aged 19-64 years diagnosed between 2007 and 2011. We used bivariate analyses to compare PPDx to CMS enrollment at diagnosis month and assessed underreporting rates by patient characteristics and state-year policy. RESULTS: PPDx reported 7.8% Medicare and 10.1% Medicaid, whereas CMS enrollment indicated 5.5% Medicare, 10.4% Medicaid, and 3.4% dual Medicare-Medicaid (N = 896,031). Positive predictive values for PPDx assignment to Medicaid and Medicare were 65.3% and 75.4%, with false negative rates of 52.0% and 33.8%, respectively. Medicaid underreporting was higher in low (56.5%) versus high (50.8%) poverty areas, for males (56.1%) versus females (48.9%), for Medicaid poverty expansion or waiver enrolled (63.8%) versus cash assistance-related eligibility (47.3%), and in states with large managed care enrollment (all P < 0.001). If Medicaid and Medicare enrollment data were used to edit PPDx, 12.0% of persons would switch primary payer assignment. CONCLUSIONS: Registry-reported PPDx fails to fully capture Medicaid and Medicare enrollment, which may result in biased estimates of insurance-related policy impacts. Enhancement with objective enrollment data could reduce measurement error and bias in estimates necessary to support policy assessment.

Assessing the Impact of Family Caregivers in Clinical Encounter Participation on Patient Activation in the Metastatic Breast Cancer Setting.

Objective: Caregivers support individuals undergoing cancer treatment by assisting with activities, managing care, navigating healthcare systems, and communicating with care teams. We explored the quantity and quality of caregiver participation during recorded clinical appointments in women with metastatic breast cancer. Methods: This was a convergent parallel mixed methods study. Caregiver participation quality was operationalized using a summative thematic content analysis to identify and sum caregiver roles performed during appointments. Caregiver participation quantity was measured by calculating the proportion of speaking time. Participation quality and quantity were compared to patient activation, assessed using the Patient Activation Measure. Results: Fifty-three clinical encounters were recorded. Identified caregiver roles included: General Support; Management of Treatment or Medication; Treatment History; Decision-Making; Insurance or Money; Pharmacy; Scheduling; Travel Concerns; General Cancer Understanding; Patient Specific Cancer Understanding; Caregiver-Initiated or Emphasis on Symptom Severity; and Caregiver Back-Up of Patient Symptom Description. Caregivers averaged 5 roles (SD 3): 48% of patients had low quality (< 5 roles) and 52% had high quality (> 6 roles). Regarding quantity, caregivers spoke on average for 4% of the encounter, with 60% of patients having low quantity (< 4%) and 40% of patients having high quantity (> 4%). Greater quality and quantity of caregiver participation was associated with greater patient activation. Conclusions: Caregivers perform a variety of roles during oncological decision-making visits aiding both patient and provider. Greater participation in terms of quantity and quality by the caregiver was associated with greater patient activism, indicating a need for better integration of the caregiver in clinical decision-making environments.

Cancer-Related Financial Hardship Screening as Part of Practice Transformation.

BACKGROUND: Data on financial hardship, an "adverse event" in individuals with cancer, are needed to inform policy and supportive care interventions and reduce adverse economic outcomes. METHODS: Lay navigator-led financial hardship screening was piloted among University of Alabama at Birmingham oncology patients initiating treatment in October 2020. Financial hardship screening, including reported financial distress and difficulty, was added to a standard-of-care treatment planning survey. Screening feasibility and completion and proportions of reported financial distress and difficulty were calculated overall and by patient race and rurality. The risk of financial distress by patient sociodemographics was estimated. RESULTS: Patients who completed a treatment planning survey (N=2741) were 18% Black, Indigenous, or persons of color (BIPOC) and 16% rural dwelling. The majority of patients completed financial hardship screening (90%), surpassing the target feasibility completion rate of 75%. The screening revealed 34% of patients were experiencing financial distress, including 49% of BIPOC and 30% of White patients. Adjusted models revealed BIPOC patients had a 48% higher risk of financial distress compared with those who were White (risk ratio 1.48, 95% CI, 1.31-1.66). Large differences in reported financial difficulties were seen comparing patients who were BIPOC and White (utilities: 33% vs. 10%, upfront medical payments: 44% vs. 23%, transportation: 28% vs. 12%, respectively). CONCLUSIONS: The collection of patient-reported financial hardship data via routine clinical care was feasible and identified racial inequities at treatment initiation. Efforts to collect patient economic data should support the design, implementation, and evaluation of patient-centered interventions to improve equity and reduce the impact of financial hardship.

Impact of Affordable Care Act provisions on the racial makeup of patients enrolled at a Deep South, high-risk breast cancer clinic.

Purpose: Black women are less likely to receive screening mammograms and are at a higher lifetime risk for developing breast cancer compared to their White counterparts. Affordable Care Act (ACA) provisions decreased cost sharing for women's preventive screening, potentially mitigating screening disparities. We examined enrollment of a high-risk screening program before and after ACA implementation stratified by race. Methods: This retrospective, quasi-experimental study examined the ACA's impact on patient demographics at a high-risk breast cancer screening clinic from 02/28/2003-02/28/2019. Patient demographic data were abstracted from electronic medical records and descriptively compared in the pre- and post-ACA time periods. Interrupted time series (ITS) analysis using Poisson regression assessed yearly clinic enrollment rates by race using incidence rate ratios (IRR) and 95% confidence intervals (CI). Results: 2,767 patients enrolled in the clinic. On average, patients were 46 years old (SD, ± 12), 82% were commercially insured, and 8% lived in a highly disadvantaged neighborhood. In ITS models accounting for trends over time, Prior to ACA implementation, White patient enrollment was stable (IRR 1.01, 95% CI 1.00-1.02) while Black patient enrollment increased at 13% per year (IRR 1.13, 95% CI 1.05-1.22). Compared to the pre-ACA enrollment period, the post-ACA enrollment rate remained unchanged for White patients (IRR 0.99, 95% CI 0.97-1.01) but decreased by 17% for Black patients (IRR 0.83, 95% CI 0.74-0.92). Conclusion: Black patient enrollment decreased at a high-risk breast cancer screening clinic post-ACA compared to the pre-ACA period, indicating a need to identify factors contributing to racial disparities in clinic enrollment.

Expanding research on the impact of financial hardship on emotional well-being: guidance of diverse stakeholders to the Emotional Well-Being and Economic Burden of Disease (EMOT-ECON) Research Network.

The Emotional Well-Being and Economic Burden (EMOT-ECON) Research Network is one of six research networks funded by the National Institutes of Health (NIH) to advance research about emotional well-being (EWB), and the only one that focuses on addressing how economic burden due to disease or illness affects EWB. The network convened researchers, patients, patient advocates, health care providers and other stakeholders from across the US to discuss the significance of addressing the impact of the economic burden of disease on EWB, the complexity of this prevalent problem for patients and families, and the research gaps that still need to be studied to ultimately develop strategies to reduce the impact of economic burden of disease on EWB and health. Participants identified some important future areas of research as those investigating: (i) prevalent and relevant emotions for patients experiencing economic burden of disease and financial hardship, and how their broader outlook on life is impacted; (ii) constructs and contexts that influence whether the economic burden is stressful; (iii) strategies to deal and cope and their positive or negative effects on EWB and health; and (iv) multi-level and multi-stakeholder interventions to address economic factors (e.g., costs, ability to pay), administrative burdens, education and training, and especially patients' emotional as well as financial status.

Associations between health insurance status, neighborhood deprivation, and treatment delays in women with breast cancer living in Georgia.

BACKGROUND: Little is known regarding the association between insurance status and treatment delays in women with breast cancer and whether this association varies by neighborhood socioeconomic deprivation status. METHODS: In this cohort study, we used medical record data of women diagnosed with breast cancer between 2004 and 2022 at two Georgia-based healthcare systems. Treatment delay was defined as >90 days to surgery or >120 days to systemic treatment. Insurance coverage was categorized as private, Medicaid, Medicare, other public, or uninsured. Area deprivation index (ADI) was used as a proxy for neighborhood-level socioeconomic status. Associations between delayed treatment and insurance status were analyzed using logistic regression, with an interaction term assessing effect modification by ADI. RESULTS: Of the 14,195 women with breast cancer, 54% were non-Hispanic Black and 52% were privately insured. Compared with privately insured patients, those who were uninsured, Medicaid enrollees, and Medicare enrollees had 79%, 75%, and 27% higher odds of delayed treatment, respectively (odds ratio [OR]: 1.79, 95% confidence interval [CI]: 1.32-2.43; OR: 1.75, 95% CI: 1.43-2.13; OR: 1.27, 95% CI: 1.06-1.51). Among patients living in low-deprivation areas, those who were uninsured, Medicaid enrollees, and Medicare enrollees had 100%, 84%, and 26% higher odds of delayed treatment than privately insured patients (OR: 2.00, 95% CI: 1.44-2.78; OR: 1.84, 95% CI: 1.48-2.30; OR: 1.26, 95% CI: 1.05-1.53). No differences in the odds of delayed treatment by insurance status were observed in patients living in high-deprivation areas. DISCUSSION/CONCLUSION: Insurance status was associated with treatment delays for women living in low-deprivation neighborhoods. However, for women living in neighborhoods with high deprivation, treatment delays were observed regardless of insurance status.

A nationwide cross-sectional study on the association of patient-level factors with financial anxiety in the context of chronic medical conditions.

Patient-level characteristics associated with the prevalence and severity of financial anxiety have yet to be described. We conducted a cross-sectional analysis of survey data assessing financial anxiety in patients with chronic medical conditions in December 2020. 1771 patients (42.6% response rate) participated in the survey. Younger age (19-35 age compared to ≥ 75 age) (ß, 5.86; 95% CI 2.10-9.63), male sex (ß, - 1.9; 95% CI - 3.1 to - 0.73), Hispanic/Latino race/ethnicity (compared with White patients) (ß, 2.55; 95% CI 0.39-4.71), household size ≥ 4 (compare with single household) (ß, 4.54; 95% CI 2.44-6.64), household income of ≥ $96,000-$119,999 (compared with ≤ $23,999) (ß, - 3.2; 95% CI - 6.3 to 0.04), single marital status (compared with married) (ß, 2.18; 95% CI 0.65-3.71), unemployment (ß, 2.07; 95% CI 0.39-3.74), high-school education (compared with advanced degrees) (ß, 3.10; 95% CI 1.32-4.89), lack of insurance coverage (compared with private insurance) (ß, 6.05; 95% CI 2.66-9.45), more comorbidities (≥ 3 comorbidities compared to none) (ß, 2.95; 95% CI 1.00-4.90) were all independently associated with financial anxiety. Patients who are young, female, unmarried, and representing vulnerable sub-populations are at elevated risk for financial anxiety.

"It's just not easy to understand": A mixed methods study of health insurance literacy and insurance plan decision-making in cancer survivors.

BACKGROUND: Understanding cancer survivors' health insurance decision-making is needed to improve insurance choice, potentially resulting in reduced financial hardship. METHODS: This explanatory mixed methods study assessed health insurance decision-making in cancer survivors. Health Insurance Literacy Measure (HILM) captured HIL. Quantitative eye-tracking data collected from two simulated health insurance plan choice sets gauged dwell time (seconds), or interest, in benefits. Dwell time differences by HIL were estimated using adjusted linear models. Qualitative interviews explored survivors' insurance decision-making choices. RESULTS: Cancer survivors (N = 80; 38% breast cancer) had a median age of 43 at diagnosis (IQR 34-52). When comparing traditional and high-deductible health plans, survivors were most interested in drug costs (median dwell time 58 s, IQR 34-109). When comparing health maintenance organization and preferred provider organization plans, survivors were most interested in test/imaging costs (40s, IQR 14-67). Survivors with low versus high HIL had more interest in deductible (ß = 19 s, 95% CI 2-38) and hospitalization costs (ß = 14 s, 95% CI 1-27) in adjusted models. Survivors with low versus high HIL more often ranked out-of-pocket (OOP) maximums and coinsurance as the most important and confusing benefits, respectively. Interviews (n = 20) revealed survivors felt alone "to do their own research" about insurance choices. OOP maximums were cited as the deciding factor since it is "how much money is going to be taken out of my pocket." Coinsurance was considered "rather than a benefit, it's a hindrance." CONCLUSION: Interventions to aid in health insurance understanding and choice are needed to optimize plan choice and potentially reduce cancer-related financial hardship.

Associations Between Patient-Perceived Cancer Curability and Advance Directive Completion.

Background: Despite Advance Care Planning recommendations for patients with cancer, many lack Advance Directives (ADs). AD disparities persist among Black, Indigenous, or People of Color (BIPOC) patients. Based on a hypothesized correlation, we examined the association between patient-perceived cancer incurability and AD completion. Methods: This cross-sectional study obtained self-reported AD completion and incurability perception from routine care surveys. AD completion by incurability perception was estimated using modified Poisson regression. Subgroup analyses examined patients who were BIPOC, White, and had solid organ malignancies. Results: Our sample (N = 1209) was predominantly female (70%), White (73%) with early-stage disease (60%), and solid organ malignancies (82%). AD completion was 42%, and 40% of patients reported their cancer incurable. Patient-perceived incurability was not associated with increased AD completion (likelihood ratio 0.94, 95% confidence interval 0.78-1.13) in overall or subgroup analyses. Conclusion: Patient-perceived cancer incurability was not associated with AD completion, even accounting for race/ethnicity and cancer type.

Patient-reported discrimination among limited-resourced cancer survivors: a brief report.

PURPOSE: Healthcare discrimination has been associated with health disparities including lower cancer screenings, higher medical mistrust, and strained patient-provider relationships. Our study sought to understand patient-reported discrimination among cancer survivors with limited resources living in the United States. DESIGN AND METHODS: We used cross-sectional survey data distributed by the Patient Advocate Foundation (PAF) in 12/2020 and 07/2021. Respondents reported source and reason of healthcare discrimination. Age, sex, race and ethnicity, annual household income, Rural-Urban Commuting Area (RUCA), Area Deprivation Index (ADI), employment status, cancer type, and number of comorbidities were independent variables of interest. The association between these variables and patient-reported healthcare discrimination was estimated using risk ratios (RRs) and 95% confidence intervals (CIs) from a multivariable modified Poisson regression model with robust standard errors. FINDINGS: A total of 587 cancer survivors were included in our analysis. Most respondents were female (72%) and aged ≥56 (62%); while 33% were Black, Indigenous, or Person of Color. Overall, 23% reported receipt of discrimination, with the majority reporting doctor, nurse, or healthcare provider as the source (58%). Most common reasons for discrimination included disease status (42%), income/ability to pay (36%), and race and ethnicity (17%). In the adjusted model, retired survivors were 62% less likely to report discrimination compared to those employed (RR 0.38; 95% CI 0.23-0.64). Additionally, survivors with ≥3 comorbidities were 86% more likely to report discrimination compared to those survivors with no non-cancer comorbidities (RR 1.86; 95% CI 1.26-2.72). IMPLICATIONS: Cancer survivors with limited resources reported substantial discrimination most often from a healthcare provider and most commonly for disease status and income. Discrimination should be mitigated to provide equitable and high-quality cancer care.

Influence of Cost-Related Considerations on Clinical Trial Participation: Results from the 2020 Health Information National Trends Survey (HINTS).

BACKGROUND: People experiencing financial burden are underrepresented in clinical trials. OBJECTIVE: Describe the prevalence of cost-related considerations influential to trial participation and their associations with person-level characteristics. DESIGN: This cross-sectional study used and assessed how three cost-related considerations would influence the decision to participate in a hypothetical clinical trial. PARTICIPANTS: A total of 3682 US adult respondents to the Health Information National Trends Survey MAIN MEASURES: Survey-weighted multivariable logistic regression estimated associations between respondent characteristics and odds of reporting cost-related considerations as very influential to participation. KEY RESULTS: Among 3682 respondents, median age was 48 (IQR 33-61). Most were non-Hispanic White (60%), living comfortably or getting by on their income (74%), with ≥ 1 medical condition (61%). Over half (55%) of respondents reported at least one cost-related consideration as very influential to trial participation, including if usual care was not covered by insurance (reported by 42%), payment for participation (24%), or support for participation (24%). Respondents who were younger (18-34 vs. ≥ 75, adjusted odds ratio [aOR] 4.3, 95% CI 2.3-8.1), more educated (high school vs.

Vaccine Hesitancy versus Vaccine Behavior in Patients with Chronic Illness.

While vaccine hesitancy has been described for the general population, vaccine hesitancy among the chronically ill has not been well explored. This study assesses COVID­19 vaccine hesitancy and uptake among individuals with chronic illness using nationwide survey data. We analyzed vaccine hesitancy prior to and after approval of the vaccines using multinomial logistic regression and binomial logistic regression, respectively. In the first survey, 39% reported they were unlikely or unsure about receiving the vaccine. In adjusted analyses, female sex, Black race, anti­vaccination attitudes, media mistrust, and not following the media were associated with vaccine hesitancy. Despite this hesitance, in the follow­up survey, 89% reported vaccine receipt, with those more fearful of COVID­19, with more trust in the media, and closely following the development of the vaccine were most likely to move from hesitance to acceptance. Vaccine hesitancy is a mutable characteristic, underscoring the need for high-quality public health messaging.

Ineligible, Unaware, or Uninterested? Associations Between Underrepresented Patient Populations and Retention in the Pathway to Cancer Clinical Trial Enrollment.

PURPOSE: Cancer clinical trials can benefit current and future patients; however, Black patients, rural residents, and patients living in disadvantaged areas are often underrepresented. Using an adapted version of Unger and colleagues' model of the process of clinical trial enrollment, we evaluated the relationship between underrepresented patient populations and trial end points. METHODS: This retrospective study included 512 patients with breast or ovarian cancer who were prescribed a therapeutic drug at the University of Alabama at Birmingham from January 2017 to February 2020. Patient eligibility was assessed using open clinical trials. We estimated odds ratios and 95% CIs using logistic regression models to examine the relationship between underrepresented patient populations and trial enrollment end points: eligibility, interest, offer, enrollment, and declining enrollment. RESULTS: Of the patients in our sample, 27% were Black, 18% were rural residents, and 19% lived in higher disadvantaged neighborhoods. In adjusted models, each comparison group had similar odds of being eligible for a clinical trial. Black versus White patients had 0.40 times the odds of interest in clinical trials and 0.56 times the odds of enrollment. Patients living in areas of higher versus lower disadvantage had 0.46 times the odds of enrolling and 3.40 times the odds of declining enrollment when offered. CONCLUSION: Eligibility did not drive clinical trial enrollment disparities in our sample; however, retention in the clinical trial enrollment process appears to vary by group. Additional work is needed to understand how interventions can be tailored to each population's specific needs.

Associations between geography, decision-making style, and interest in cancer clinical trial participation.

BACKGROUND: Clinical trials offer novel treatments, which are essential to high quality cancer care. Patients living in rural areas are often underrepresented in clinical trials due to several factors. This study evaluated the association between rurality and interest in clinical trial participation, change in interest, and treatment decision-making style preference. METHODS: This cohort study included patients with cancer receiving oncology care at the University of Alabama at Birmingham from 2017 to 2019. Associations between treatment decision-making preference and the interaction between rurality and area deprivation were analyzed using multinomial logistic regression. Initial interest in clinical trial participation and change in interest were analyzed using modified Poisson regressions with robust standard errors. Initial interest model was stratified by Area Deprivation Index (ADI; higher vs. lower disadvantaged). RESULTS: In adjusted models, patients in rural versus urban areas had similar initial interest in clinical trials, both those in higher (40% vs. 50%) and lower disadvantaged settings (54% vs. 62%). Additionally, rural versus urban patients had similar change of clinical trial interest for both those who changed from uninterested-to-interested (31% vs. 26%) and interested-to-uninterested (47% vs. 42%). CONCLUSION: This study compares the interest in clinical trial participation among patients living in rural and urban settings. Lack of interest may be secondary to barriers that patients in rural areas face (e.g., transportation, financial, access). Most rural patients prefer a shared treatment decision-making style, which should be considered when identifying interventions to increase enrollment of underserved rural patients in clinical trials.

Cost-Related Medication Nonadherence and Patient Cost Responsibility for Rural and Urban Cancer Survivors.

PURPOSE: The relationship between out-of-pocket spending and cost-related medication nonadherence among older rural- and urban-dwelling cancer survivors is not well understood. METHODS: This retrospective cohort study used the Surveillance, Epidemiology, and End Results Program, Medicare claims, and the Consumer Assessment of Healthcare Providers and Systems survey linked data resource linked data (2007-2015) to investigate the relationship between cancer survivors' cost responsibility in the year before and after report of delaying or not filling a prescription medication because of cost in the past 6 months (cost-related medication nonadherence). Secondary exposures and outcomes included Medicare spending and utilization. Generalized linear models assessed bidirectional relationships between cost-related medication nonadherence, spending, and utilization. Effects of residence were assessed via interaction terms. RESULTS: Of 6,591 older cancer survivors, 13% reported cost-related medication nonadherence. Survivors were a median 8 years (interquartile range, 4.5-12.5 years) from their cancer diagnosis, 15% were dually Medicare/Medicaid-eligible, and prostate (40%) and breast (32%) cancer survivors were most prevalent. With every $500 USD increase in patient cost responsibility, risk of cost-related medication nonadherence increased by 3% (risk ratio, 1.03; 95% CI, 1.02 to 1.04). After report of cost-related medication nonadherence, patient cost responsibility was 22% higher (95% CI, 1.11 to 1.32) compared with those not reporting nonadherence, amounting to $523 USD (95% CI, $430 USD to $630 USD). Medicare spending and utilization were also higher before and after report of cost-related nonadherence versus none. For survivors residing in rural (18%) and urban (82%) areas, residence did not modify adherence or cost outcomes. CONCLUSION: A bidirectional relationship exists between patient cost responsibility and cost-related medication nonadherence. Interventions reducing urban- and rural-dwelling survivor health care costs and cost-related adherence barriers are needed.

Health insurance and financial hardship in cancer survivors during the COVID-19 pandemic.

Uninsured or underinsured individuals with cancer are likely to experience financial hardship, including forgoing healthcare or non-healthcare needs such as food, housing, or utilities. This study evaluates the association between health insurance coverage and financial hardship among cancer survivors during the COVID-19 pandemic. This cross-sectional analysis used Patient Advocate Foundation (PAF) survey data from May to July 2020. Cancer survivors who previously received case management or financial aid from PAF self-reported challenges paying for healthcare and non-healthcare needs during the COVID-19 pandemic. Associations between insurance coverage and payment challenges were estimated using Poisson regression with robust standard errors, which allowed for estimation of adjusted relative risks (aRR). Of 1,437 respondents, 74% had annual household incomes <$48,000. Most respondents were enrolled in Medicare (48%), 22% in employer-sponsored insurance, 13% in Medicaid, 6% in an Affordable Care Act (ACA) plan, and 3% were uninsured. Approximately 31% of respondents reported trouble paying for healthcare during the COVID-19 pandemic. Respondents who were uninsured (aRR 2.58, 95% confidence interval [CI] 1.83-3.64), enrolled in an ACA plan (aRR 1.86, 95% CI 1.28-2.72), employer-sponsored insurance (aRR 1.70, 95% CI 1.23-2.34), or Medicare (aRR 1.49, 95% CI 1.09-2.03) had higher risk of trouble paying for healthcare compared to Medicaid enrollees. Challenges paying for non-healthcare needs were reported by 57% of respondents, with 40% reporting trouble paying for food, 31% housing, 28% transportation, and 20% internet. In adjusted models, Medicare and employer-sponsored insurance enrollees were less likely to have difficulties paying for non-healthcare needs compared to Medicaid beneficiaries. Despite 97% of our cancer survivor sample being insured, 31% and 57% reported trouble paying for healthcare and non-healthcare needs during the COVID-19 pandemic, respectively. Greater attention to both medical and non-medical financial burden is needed given the economic pressures of the COVID-19 pandemic.

Cancer-Related Care Costs and Employment Disruption: Recommendations to Reduce Patient Economic Burden as Part of Cancer Care Delivery.

Cancer survivors are frequently unprepared to manage the out-of-pocket (OOP) costs associated with undergoing cancer treatment and the potential for employment disruption. This commentary outlines a set of research recommendations stemming from the National Cancer Institute's Future of Health Economics Research Conference to better understand and reduce patient economic burden as part of cancer care delivery. Currently, there are a lack of detailed metrics and measures of survivors' OOP costs and employment disruption, and data on these costs are rarely available at the point of care to guide patient-centered treatment and survivorship care planning. Future research should improve the collection of data about survivors' OOP costs for medical care, other cancer-related expenses, and experiences of employment disruption. Methods such as microcosting and the prospective collection of patient-reported outcomes in cancer care are needed to understand the true sum of cancer-related costs taken on by survivors and caregivers. Better metrics and measures of survivors' costs must be coupled with interventions to incorporate that information into cancer care delivery and inform meaningful communication about OOP costs and employment disruption that is tailored to different clinical situations. Informing survivors about the anticipated costs of their cancer care supports informed decision making and proactive planning to mitigate financial hardship. Additionally, system-level infrastructure should be developed and tested to facilitate screening to identify survivors at risk for financial hardship, improve communication about OOP costs and employment disruption between survivors and their health-care providers, and support the delivery of appropriate financial navigation services.