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.

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.

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.

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.

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.

Determinants of telemedicine adoption among financially distressed patients with cancer during the COVID-19 pandemic: insights from a nationwide study.

PURPOSE: Telemedicine use during the COVID-19 pandemic among financially distressed patients with cancer, with respect to the determinants of adoption and patterns of utilization, has yet to be delineated. We sought to systematically characterize telemedicine utilization in financially distressed patients with cancer during the COVID-19 pandemic. METHODS: We conducted a cross-sectional analysis of nationwide survey data assessing telemedicine use in patients with cancer during the COVID-19 pandemic collected by Patient Advocate Foundation (PAF) in December 2020. Patients were characterized as financially distressed by self-reporting limited financial resources to manage out-of-pocket costs, psychological distress, and/or adaptive coping behaviors. Primary study outcome was telemedicine utilization during the pandemic. Secondary outcomes were telemedicine utilization volume and modality preferences. Multivariable and Poisson regression analyses were used to identify factors associated with telemedicine use. RESULTS: A convenience sample of 627 patients with cancer responded to the PAF survey. Telemedicine adoption during the pandemic was reported by 67% of patients, with most (63%) preferring video visits. Younger age (19-35 age compared to ≥ 75 age) (OR, 6.07; 95% CI, 1.47-25.1) and more comorbidities (≥ 3 comorbidities compared to cancer only) (OR, 1.79; 95% CI, 1.13-2.65) were factors associated with telemedicine adoption. Younger age (19-35 years) (incidence rate ratios [IRR], 1.78; 95% CI, 24-115%) and higher comorbidities (≥ 3) (IRR; 1.36; 95% CI, 20-55%) were factors associated with higher utilization volume. As area deprivation index increased by 10 units, the number of visits decreased by 3% (IRR 1.03, 95% CI, 1.03-1.05). CONCLUSIONS: The rapid adoption of telemedicine may exacerbate existing inequities, particularly among vulnerable financially distressed patients with cancer. Policy-level interventions are needed for the equitable and efficient provision of this service.

Impact of lay navigation on utilization and Medicare spending for cancer survivors in the "Deep South".

PURPOSE: Though lay navigation programs have proven beneficial for individuals during cancer treatment, little is known about the effects of lay navigation on health care utilization and Medicare spending among older adults during cancer survivorship. METHODS: This retrospective cohort study used administrative claims data to evaluate a lay navigation program implemented from 2012 to 2015 at 12 academic and community cancer centers in the Southeast. Medicare beneficiaries age ≥65 years navigated during survivorship were compared to propensity score-matched, non-navigated cancer survivors. Quarterly trends in Medicare spending were estimated using repeated measures mixed models. Rate ratios (RRs) and 95% confidence intervals (CIs) were estimated using repeated measures generalized linear models for quarterly emergency room (ER) visits and hospitalizations. RESULTS: Medicare spending for navigated (n = 3255) versus non-navigated older cancer survivors (n = 3255) was initially higher but declined faster by $513 per patient per quarter (95% CI -$616, -$410). Per patient per quarter risk of ER visits decreased by 11% (RR 0.89, 95% CI 0.86, 0.92) and hospitalizations decreased by 16% (RR 0.84, 95% CI 0.81, 0.88) over time comparing navigated versus non-navigated patients. Similar results were seen for patients enrolled in navigation post-treatment (N = 1893). CONCLUSIONS: In older cancer survivors receiving care in the Deep South, patients receiving lay navigation compared to those non-navigated had significant reductions in Medicare spending, hospitalizations, and ER visits. IMPLICATIONS FOR CANCER SURVIVORS: Though much emphasis has been placed on lay navigation during initial cancer treatment, navigation is needed throughout survivorship due to the high costs and health care utilization that persist post-treatment.

Demographic and Health Behavior Factors Associated With Clinical Trial Invitation and Participation in the United States.

Importance: Representative enrollment in clinical trials is critical to ensure equitable and effective translation of research to practice, yet disparities in clinical trial enrollment persist. Objective: To examine person-level factors associated with invitation to and participation in clinical trials. Design, Setting, and Participants: This cross-sectional study analyzed responses from 3689 US adults who participated in the nationally representative Health Information National Trends Survey, collected February through June 2020 via mailed questionnaires. Exposures: Demographic, clinical, and health behavior-related characteristics. Main Outcomes and Measures: History of invitation to and participation in a clinical trial, primary information sources, trust in information sources, and motives for participation in clinical trials were described. Respondent characteristics are presented as absolute numbers and weighted percentages. Associations between respondent demographic, clinical, and health behavior-related characteristics and clinical trial invitation and participation were estimated using survey-weighted logistic regression models. Results: The median (IQR) age of the 3689 respondents was 48 (33-61) years, and most were non-Hispanic White individuals (2063 [59%]; non-Hispanic Black, 452 [10%]; Hispanic, 521 [14%]), had more than a high school degree (2656 [68%]), were employed (1809 [58%]), and had at least 1 medical condition (2535 [61%]). Overall, 439 respondents (9%) had been invited to participate in any clinical trial. Respondents with increased odds of invitation were non-Hispanic Black compared with non-Hispanic White (adjusted odds ratio [aOR], 1.85; 95% CI, 1.13-3.02), had greater than a high school education compared with less than high school education (eg, ≥college degree: aOR, 4.84; 95% CI, 1.89-12.39), were single compared with married or living as married (aOR, 1.68; 95% CI, 1.04-2.73), and had at least 1 medical condition compared to none (eg, 1 medical condition: aOR, 2.25; 95% CI, 1.32-3.82). Respondents residing in rural vs urban areas had 77% decreased odds of invitation to a clinical trial (aOR 0.33; 95% CI 0.17-0.65). Of invited respondents, 199 (47%) participated. Compared with non-Hispanic White respondents, non-Hispanic Black respondents had 72% decreased odds of clinical trial participation (aOR, 0.28; 95% CI, 0.09-0.87). Respondents most frequently reported "health care providers" as the first and most trusted source of clinical trial information (first source: 2297 [59%]; most trusted source: 2597 [70%]). The most frequently reported motives for clinical trials participation were "wanting to get better" (2294 [66%]) and the standard of care not being covered by insurance (1448 [41%]). Conclusions and Relevance: The findings of this study suggest that invitation to and participation in clinical trials may differ by person-level demographic and clinical characteristics. Strategies toward increasing trial invitation and participation rates across diverse patient populations warrant further research to ensure equitable translation of clinical benefits from research to practice.

The Impact of Depression on Health Care Utilization in Patients with Cancer.

Background: Depression is common in the oncology patient population. Little data exist on the impact of depression on health care utilization. Objectives: We evaluated the prevalence of depression and the relationship between depression and health care utilization in patients with cancer. Design: This cross-sectional study utilized patient-reported outcome data from predominately Medicare beneficiaries with cancer. We examined the emergency department visits and inpatient admissions within 3 months from survey. The relationship between depression and hospital visits was assessed using generalized linear models. Results: Of 1038 patients included in the study, 13% had moderate to severe depression. In adjusted models, patients with moderate or severe depression trended toward increased risk of hospitalizations compared with patients without depression (risk ratio: 1.25, 95% confidence interval: 0.97-1.62). Conclusions: Clinically significant depression is not uncommon in cancer patients. Further research is needed evaluating the relationship between depression, health care utilization, and early psychiatric intervention in oncology.

Treatment Decision Making and Financial Toxicity in Women With Metastatic Breast Cancer.

INTRODUCTION: Oncologists have increasingly been proponents of shared decision making (SDM) to enhance patient outcomes and reduce unnecessary health care spending. However, its effect on patient out-of-pocket costs is unknown. This study investigated the relationship between patient preferences for SDM and financial toxicity (FT) in patients with metastatic breast cancer (MBC). PATIENTS AND METHODS: This cross-sectional study utilized surveys of women aged ≥ 18 with MBC who received care at two academic hospitals in Alabama from 2017 to 2019. Patients self-reported their SDM preference (Control Preferences Scale) and FT (Comprehensive Score for Financial Toxicity [COST] tool; 11-item scale, with lower scores indicating worse FT). Effect sizes were calculated using the proportion of variance explained (R2) or Cramer's V. Differences in FT by SDM preference were estimated using mixed models clustered by site and treating medical oncologist. RESULTS: In 95 women with MBC, 44% preferred SDM, 29% preferred provider-driven decision making, and 27% preferred patient-driven decision making. Patients preferring SDM were more often college educated (53% vs. 39%; V = 0.12) with an income greater than $40,000/y (55% vs. 43%; V = 0.18). Overall median COST was 22 (interquartile range, 16-29). After adjusting for patient demographic and clinical characteristics, patients preferring patient-driven decision making trended toward worse FT (COST 17: 95% confidence interval, 12-22) compared to those preferring SDM (COST 19: 95% confidence interval, 15-23) and those preferring provider-driven decision making (COST 22: 95% confidence interval, 17-27). CONCLUSION: Patients preferring more patient-driven decision making reported worse FT, although differences did not reach statistical significance. Further research is needed to understand this relationship.

Quantifying treatment preferences and their association with financial toxicity in women with breast cancer.

BACKGROUND: The objective of the current study was to understand treatment preferences and their association with financial toxicity in Patient Advocate Foundation clients with breast cancer. METHODS: This choice-based conjoint analysis used data from a nationwide sample of women with breast cancer who received assistance from the Patient Advocate Foundation. Choice sets created from 13 attributes of 3 levels each elicited patient preferences and trade-offs. Latent class analysis segmented respondents into distinct preference archetypes. The Comprehensive Score for Financial Toxicity (COST) tool captured financial toxicity. Adjusted generalized linear models estimated COST score differences by preference archetype. RESULTS: Of 220 respondents (for a response rate of 10%), the median age was 58 years (interquartile range, 49-66 years); 28% of respondents were Black, indigenous, or people of color; and approximately 60% had household incomes <$40,000. The majority of respondents were diagnosed with early-stage cancer (91%), 38% had recurrent disease, and 61% were receiving treatment. Treatment choice was most affected by preferences related to affordability and impact on activities of daily living. Two distinct treatment preference archetypes emerged. The "cost-prioritizing group" (75% of respondents) was most concerned about affordability, impact on activities of daily living, and burdening care partners. The "functional independence-prioritizing group" (25% of respondents) was most concerned about their ability to work, physical side effects, and interference with life events. COST scores were found to be similar between the archetypes in adjusted models (cost-prioritizing group COST score, 12 [95% confidence interval, 9-14]; and functional independence-prioritizing COST score, 11 [95% confidence interval, 9-13]). CONCLUSIONS: Patients with breast cancer prioritized affordability or maintaining functional independence when making treatment decisions. Because of this variability, preference evaluation during treatment decision making could optimize patients' treatment experiences.

Health care-related time costs in patients with metastatic breast cancer.

BACKGROUND: Burdens related to time spent receiving cancer care may be substantial for patients with incurable, life-limiting cancers such as metastatic breast cancer (MBC). Estimates of time spent on health care are needed to inform treatment-related decision-making. METHODS: Estimates of time spent receiving cancer-related health care in the initial 3 months of treatment for patients with MBC were calculated using the following data sources: (a) direct observations from a time-in-motion quality improvement evaluation (process mapping); (b) cross-sectional patient surveys; and (c) administrative claims. Average ambulatory, inpatient, and total health care time were calculated for specific treatments which differed by antineoplastic type and administration method, including fulvestrant (injection, hormonal), letrozole (oral, hormonal), capecitabine (oral, chemotherapy), and paclitaxel (infusion, chemotherapy). RESULTS: Average total time spent on health care ranged from 7% to 10% of all days included within the initial 3 months of treatment, depending on treatment. The greatest time contributions were time spent traveling for care and on inpatient services. Time with providers contributed modestly to total care time. Patients receiving infusion/injection treatments, compared with those receiving oral therapy, spent more time in ambulatory care. Health care time was higher for patients receiving chemotherapeutic agents compared to those receiving hormonal agents. CONCLUSION: Time spent traveling and receiving inpatient care represented a substantial burden to patients with MBC, with variation in time by treatment type and administration method.

Oncologic Services Through Project Access and Other Safety Net Care Coordination Programs.

PURPOSE: Little is known about the provision of oncologic services by Project Access safety net care coordination programs. MATERIALS AND METHODS: Information on safety net care coordination program locations, health services, and patient eligibility was obtained via program Web sites and calls. For programs not offering oncologic care, program directors were interviewed to identify oncologic care barriers. RESULTS: Web sites of 29 safety net care coordination programs in 22 states were identified; 62% (n = 18) offered oncologic services. Programs were in 65% (n = 11) of states that did not expand Medicaid. Of those offering oncologic services, 83% (n = 15) offered free chemotherapy, and 93% (n = 27) of all programs offered oncologic imaging. Program director interviews revealed costs, longitudinal care, and multiple-physician buy-in as barriers limiting oncologic care. CONCLUSION: Third-party care coordination centers provide a novel and potentially unrecognized approach to increasing oncology service access. Further research should identify strategies to overcome the relative lack of oncologic care offerings.