Health Insurance Literacy and Financial Toxicity in Adolescent and Young Adult Cancer Survivors

Abstract

Purpose:

Empirical evidence examining the impact of health insurance literacy (HIL) on cancer-related financial toxicity (FT) among adolescent and young adults (AYAs) is limited. AYA cancer survivors experience greater levels of financial hardship due to sociodemographic and developmentally related factors. The purpose of this study was to examine the relationship between HIL and FT in this vulnerable population.

Methods:

We used a cross-sectional design to survey 246 AYA cancer survivors (diagnosed between ages 15–39) through the Kentucky Cancer Registry (KCR). Survey data were collected on FT and HIL using the Health Insurance Literacy Scale (HILS) and Health Insurance Literacy Measure (HILM) subscales on behaviors related to choosing and using health insurance plans. Record-level KCR data included county of residence and race/ethnicity among other sociodemographic variables.

Results:

Two-thirds (67%) of participants indicated experiencing problems with understanding health insurance or medical bills. When adjusting for sociodemographic variables, those with inadequate HILS scores reporting higher (p = 0.002) FT scores than those with adequate HILS (b = 0.05, SE = 0.02). An inverse relationship (p = 0.042) was found between behaviors related to choosing health insurance plans and FT (b = −0.003, SE = 0.002). A significantly (p = 0.028) lower proportion of rural participants had adequate HILS scores (55%), compared to their urban counterparts (71%).

Conclusion:

Our findings highlight the need for integrating HIL education and resources in FT interventions tailored to address the unique needs of geographically diverse AYA cancer survivors across the cancer continuum.

Keywords

financial toxicity health insurance literacy adolescent and young adult survivors rural

Introduction

The incidence and economic impact of cancer are projected to rise to $246 billion by 2030 in the United States.^1,2 In turn, rising out-of-pocket expenses for cancer care (e.g., deductibles, copayments, coinsurance) have increased, with the potential to reach upwards of $35,000 annually per patient.³ These rising costs have contributed to cancer-related financial toxicity (FT) experienced by cancer survivors.⁴ FT—the material burden and psychological distress arising from the various costs of cancer treatment⁵—is associated with poorer health-related quality of life (QOL),⁶ treatment noncompliance,⁷ decreased survival,⁸ and increased symptom burden⁹ among survivors. Adolescent and young adult (AYA) cancer survivors (diagnosed between ages 15 and 39) are at increased risk of experiencing FT due to being under-insured, lacking stable sources of income and assets, and experiencing major life transitions, such as pursuing higher education, launching into careers, finding life partners, and starting families.^10–13 More so, FT experienced by underserved racial/ethnic minorities and rural-residing AYA survivors can be amplified by factors such as lower socioeconomic status, food insecurity, inadequate health insurance coverage, barriers to accessing health care, and low health insurance literacy (HIL).^14,15

Studies have shown that even among individuals who have adequate health insurance coverage, the lack of HIL impacts effective understanding of coverage and subsequent navigation of cancer care.^16,17 HIL is defined as the degree to which individuals have the knowledge and confidence to engage with and evaluate health insurance plans based on their financial circumstances; and subsequently use their insurance to seek timely and appropriate care.^18,19 Consequently, individuals with limited HIL may select insurance coverage that fails to meet their health and financial needs, leading to FT and poorer health outcomes. Despite growing research on FT in AYA cancer survivors, few have established the association between HIL and FT in this vulnerable population, particularly in light of integrating HIL education and resources in FT interventions.^19,20

In this study, we explored the relationship between health literacy, HIL, and FT in a sample of AYA cancer survivors using data from the Kentucky Cancer Registry (KCR). We hypothesize that AYA cancer survivors with lower HIL will experience greater FT than survivors with higher HIL. The KCR is the official population-based central cancer registry for the state of Kentucky, providing access to comprehensive data along with electronic health record reporting of cancer AYA cancer survivor cases. Findings will contribute to better understanding the impact of HIL on mitigating the impact of FT on AYA cancer survivors and to inform future interventions.

Methods

Study design, setting, and sample

The Social-Ecological Model of AYA Readiness for Transition²¹ was utilized to investigate the link between health literacy, HIL, and FT. This cross-sectional study recruited participants through the population-based KCR from February 2022 to February 2023. Details of KCRs established recruitment protocol can be found in our prior publication.¹³ A total of 800 AYA cancer survivors met eligibility criteria: (1) received an oncology diagnosis in the past 10 years, (2) diagnosed between ages 15 and 39, (3) identify as Hispanic/non-Hispanic Black or non-Hispanic White race, (4) are 18 and older at the time of recruitment, (5) reside in Kentucky, and have the ability to read and write in English. 376 survivors consented to being contacted, and 260 completed online or mailed-in consents and surveys. Consents included permission to release record-level data of individuals from the KCR, which were merged with survey data. This study was approved by the University of Kentucky Institutional Review Board (#74682).

Measures

Record-level KCR data included in this analysis were date of birth, sex, county of residence, race/ethnicity, and date of diagnosis. The 2013 rural-continuum codes were applied to categorize county of residence as urban (scored 1–3) or rural (scored between 4 and 9).²² A demographic survey collected information on participant’s income, out-of-pocket health care costs, insurance coverage, occupation, and marital status. The federal poverty level (FPL) of participants was calculated using demographic survey data to assess household income following the 2024 U.S Department of Health and Human Services FPL guidelines.²³

FT was measured within 3 domains: psychological response, material conditions, and coping behaviors.²⁴ As we have done in prior studies,^25–27 psychological response was primarily measured using the validated and reliable 11-item Comprehensive Score for Financial Toxicity (COST; Cronbach α = 0.92).²⁸ Material conditions were measured by four items from the Agency for Health care Research and Quality’s Medical Expenditure Panel Survey Experiences with Cancer Survey²⁹ (MEPS-ECS) to assess if participants had ever borrowed money or gone into debt, filed for bankruptcy, been unable to cover their share of medical costs, or made financial sacrifices due to their cancer. To determine coping behaviors, one item from MEPS-ECS was utilized to evaluate if participants had delayed, foregone, or made changes to cancer care (such as medicine, specialist visits, treatments, follow-up care, or mental health services) due to costs. A total FT score was created with a potential range of 0–3; higher scores reflect higher FT. The total FT score was constructed to capture multiple dimensions of financial burden (psychosocial, material, and behavioral),³⁰ consistent with conceptual frameworks²⁴ and prior published work using similar composite measures.^25,26,31

Health literacy was measured using the Single-item Health Literacy Scale (SILS),³² “How often do you need to have someone help you when you read instructions, pamphlets, or other handwritten material from your health care provider or pharmacy?” Response options followed a 5-point Likert scale ranging from 1) “Never” to 5) “Always.” HIL was assessed using the Health Insurance Literacy Scale (HILS)³³ and the Health Insurance Literacy Measure (HILM).¹⁸ The single-item HILS asks, “Did you ever have a problem understanding health insurance or medical bills related to your cancer, its treatment, or the lasting effects of that treatment?” Those who answered “Yes” were coded as inadequate, and those who responded “No” were coded as adequate for HIL. Two HILM subscales¹⁸ measured behaviors in choosing (6 items) and using (4 items) health insurance plans. For behaviors related to choosing plans, participants were asked how likely they were to engage in the following behaviors when comparing insurance plans: understand how plans differ, find out if deductibles have to be met for services, see which doctors and hospitals are covered, understand out-of-pocket costs for prescription drugs and emergency department visits, and find out if plans cover unexpected costs. Responses followed a 4-point Likert scale ranging from 1) “Not at all likely” to 4) “Very likely”. A summative score was calculated with a potential range of 6–24 with higher scores indicating greater HIL. For behaviors related to using plans, participants were asked how likely they were to engage in the following behaviors when seeking health care services: look to member services to see what medical services are covered under the health plan, find out of provider is in-network before visit, review statements from the health plan. Responses followed a 4-point Likert scale ranging from 1) “Not at all likely” to 4) “Very likely”. A summative score was calculated again, yielding a potential range or 4–16 with higher scores indicating greater HIL.

Data analysis

Descriptive statistics, including means and standard deviations or frequency distributions, as appropriate, were used to summarize study variables. Bivariate associations among survivor sociodemographic characteristics and total FT score were conducted using correlation coefficients (Pearson’s and Spearman’s, as appropriate) and the two-sample t-test. Bivariate relationships of race and geographic location and each of the literacy items were evaluated using the Mann–Whitney U test (health literacy), and chi-square test of association (HIL) and two-sample t-test (choosing and using health insurance plans). Multiple linear regression model was used to determine associations among health literacy, HIL and FT, adjusting for sociodemographic characteristics. Variance inflation factors were used to test for multicollinearity. All data analysis was conducted using SAS, version 9.3 (Cary, NC), with an alpha level of 0.05 throughout.

Results

A total of 260 AYA cancer survivors participated in the overall study (full demographic and cancer-related characteristics located in our previous publication).¹³ For this secondary analysis, 246 provided complete data on the FT measures, thus comprising the analytic sample. The average age at diagnosis was 31.7 years (SD = 6.0; range 15–39; see Table 1). Nearly three-quarters of participants were female (74%) and White (74%). The majority had incomes above the FPL (89%), and slightly more than half were married or partnered (54%). Approximately one-quarter resided in a county designated as rural (24%).

Table 1.

Descriptive Summary Participant Characteristics and Bivariate Associations with Financial Toxicity Total Score (N = 246)

	Total sample	Association with FT
	Mean (SD); range or n (%)	Correlation coefficient or mean (SD)	p
Age at diagnosis in years	31.7 (6.0); 15–39	r = 0.08	0.20
Sex			0.42
Female	182 (74.0%)	0.26 (0.11)
Male	64 (26.0%)	0.25 (0.10)
Race			0.21
Black of African American	63 (25.6%)	0.27 (0.12)
White	183 (74.4%)	0.25 (0.24)
Income			<0.001
Above federal poverty limit	216 (88.5%)	0.25 (0.10)
At or below federal poverty limit	28 (11.5%)	0.34 (0.12)
Relationship status			0.044
Married or partnered	133 (54.3%)	0.24 (0.10)
Not married or partnered	112 (45.7%)	0.27 (0.11)
Geographic location			0.22
Rural	60 (24.4%)	0.27 (0.11)
Urban	186 (75.6%)	0.25 (0.11)
Health literacy			0.16
Frequency of help reading materials from your HCP		rho = 0.09
Never	178 (76.4%)
Rarely	34 (14.6%)
Sometimes	14 (6.0%)
Often	5 (2.1%)
Always	2 (0.9%)
Health insurance literacy			<0.001
Adequate	157 (67.4%)	0.24 (0.10)
Inadequate	76 (32.6%)	0.30 (0.11)
Choosing health insurance plans	17.3 (5.1); 6–24	r = −0.26	<0.001
Using health insurance plans	11.1 (3.6); 4–16	r = −0.08	0.23
Financial toxicity
Psychological response (COST-FACIT 0–44)	25.2 (7.6); 0–44
Material conditions (0–6)	1.7 (1.3); 0–5
Coping behaviors (0–9)	1.0 (1.7); 0–9
Total score (0–3)	0.3 (0.1); 0–0.6

FT, financial toxicity; HCP, health care provider.

For SILS, over three-quarters of AYA cancer survivors (74%) responded “never” to needing help reading instructions, pamphlets, or other written materials from their health care providers or pharmacists (see Table 1). For HILS, two-thirds (67%) of participants indicated they did experience problems with understanding health insurance or medical bills related to their cancer, its treatment, or the lasting effects of that treatment. Average scores on HILM subscale related to choosing health insurance plans were moderate, falling near the midpoint of the scales (M = 17.3, SD = 5.1, potential range 6–24), as were the scores for using health insurance plans (M = 11.1, SD = 3.6, potential range 4–16).

Participants reported low to moderate FT levels in general across all three domains. The average score of the COST (psychological response) was 25.2 (SD = 7.6). As reported in our previous study based on this data,¹³ relative to each of their potential scale ranges, mean scores for material conditions (M = 1.7, SD = 1.3; potential range 0–5) and coping behaviors (M = 1.0, SD = 1.7; potential range 0–9) were also relatively low. The overall FT score, comprised of the standardized version of each of these domains, was also relatively low on average (M = 0.3, SD = 0.1), based on the potential maximum score of 3.

In the bivariate analysis, income classified as above the FPL designation (p < .001), marital status (p = 0.044), and HILS (p < 0.001) were significantly associated with the total FT score (see Table 1). Those above the FPL (M = 0.25, SD = 0.10) had significantly lower FT total scores compared to those at or below the FPL (M = 0.34, SD = 0.12), as did those who were married or partnered (M = 0.24, SD = 0.10), compared to those who were not married or partnered (M = 0.27, SD = 0.11). Those with inadequate HILS scores had significantly higher FT (M = 0.30, SD = 0.11) compared to those with adequate HILS (M = 0.24, SD = 0.10), yet there was no association between SILS scores and FT (rho = 0.09, p = 0.16). There was a small, indirect relationship between (HILM subscale) behaviors related to using health insurance plans and FT scores (r = −0.25, p < 0.001), but using health insurance plans was not associated in the bivariate analysis. In the analysis of the relationship between race and geographic location with each of the literacy items, the only significant relationship was among geographic location and HILS scores (p = 0.028; see Table 2), with a significantly lower proportion of rural participants having adequate HILS compared to urban (55% vs. 71%, respectively).

Table 2.

Bivariate Associations among Race Geographic Classification and Health Literacy and Health Insurance Literacy (N = 246)

	Race		p	Geographic location		p
	Black	White		Rural	Urban
	n (%)	n (%)		n (%)	n (%)
Health literacy			0.94			0.99
Frequency of help reading materials from your HCP
Never	46 (76.7%)	132 (76.3%)		43 (76.7%)	135 (76.3%)
Rarely	9 (15.0%)	25 (14.4%)		7 (12.5%)	27 (15.3%)
Sometimes	3 (5.0%)	11 (6.4%)		4 (7.1%)	10 (5.6%)
Often	2 (3.3%)	3 (1.7%)		2 (3.6%)	3 (1.7%)
Always	0 (0.0%)	2 (1.2%)		0 (0.0%)	2 (1.1%)
Health insurance literacy			0.14			0.028
Adequate	45 (75.0%)	112 (64.7%)		31 (55.4%)	126 (71.2%)
Inadequate	15 (25.0%)	61 (35.3%)		25 (44.6%)	51 (28.8%)
Choosing health insurance plans	17.3 (5.0)	17.3 (5.5)	0.99	17.9 (4.4)	17.2 (5.4)	0.40
Using health insurance plans	11.1 (3.5)	11.1 (3.9)	0.90	11.5 (3.3)	11.0 (3.7)	0.34

HCP, health care provider.

The multiple linear regression model was significant overall (F = 5.9, p < 0.001), and 21% of the variability in total FT scores was explained by the variables included in the model (see Table 3). HIL remained significant in the adjusted model (p = 0.002), where those with inadequate HILS scores reporting higher FT scores than those with adequate HILS (b = 0.05, SE = 0.02), adjusting for sociodemographic characteristics. The small, inverse relationship with behaviors related to choosing health insurance plans also remained significant in the adjusted model (p = 0.042). Health literacy remained non-significant in the adjusted analysis. The only significant sociodemographic variable in the model was income, with those above the FPL having significantly lower FT scores (b = −0.09, SD = 0.02; p < 0.001). Age, sex, race, marital status, and geographic location were not associated with FT. All variance inflation factors were less than 1.7, suggesting multicollinearity was not distorting parameter estimates. Review of diagnostic plots indicated the linear assumption was satisfied, the errors appeared independent, and the model was not unduly influenced by outliers or leverage points; therefore, the use of linear regression was a valid analytic approach for modeling the relationships presented here.

Table 3.

Multiple Linear Regression Modeling Associations among Health Literacy, Health Insurance Literacy and Financial Toxicity (n* = 228)

Regressor	b (SE)	p
Age in years	0.002 (0.001)	0.079
Male sex	−0.002 (0.015)	0.91
White race	−0.005 (0.017)	0.78
Above federal poverty limit	−0.092 (0.022)	<0.001
Married or partnered	0.016 (0.016)	0.12
Rural geographic location	−0.023 (0.015)	0.32
Health literacy	0.003 (0.009)	0.76
Inadequate health insurance literacy	0.047 (0.015)	0.002
Choosing health insurance plans	−0.003 (0.002)	0.042
Using health insurance plans	0.002 (0.002)	0.28

Only those with complete data on all variables were retained in the regression model.

Discussion

The purpose of this study was to examine the relationship between FT, health literacy, and HIL among AYA cancer survivors. Consistent with our hypothesis, we observed that AYA cancer survivors with lower HIL (as measured by lower understanding and engaging in poorer behaviors related to effectively choosing health insurance plans) experienced greater FT compared to those with higher HIL even when adjusting for sociodemographic variables. A greater number of participants had lower levels of HIL compared to health literacy levels, and interestingly, no correlations were found between the two variables. HIL was significantly lower among rural versus urban residing residents. These results indicate that HIL could play an important role in mitigating the impact of FT on AYA cancer survivors.

Our study demonstrates that HIL could be a significant predictor of FT among the AYA cancer population. Similar to our sample, HIL is consistently reported to be low nationwide,³⁴ with studies demonstrating strong associations between low HIL and decreased health care utilization³⁵ and poorer self-reported health.³⁶ While HIL is generally lower among young adults,³⁷ AYA cancer survivors are particularly vulnerable to the negative impact of low HIL levels due to limited experiences with navigating health care systems³⁸ coinciding with major life transitions associated with increased financial independence.¹⁰ Future research is needed to help determine whether HIL functions as a moderator or mediator of cancer-related FT to tailor targeted FT interventions.

While the majority of empirically tested FT interventions have focused on providing financial navigation services to reduce FT among AYA cancer survivors,^25,39,40 few have focused specifically on providing tools and resources to improve HIL in order to mitigate the impact of FT on survivor wellbeing.^26,41 Our results suggest that strengthening patients’ capacity to understand, compare and choose, and effectively use health insurance may be a complementary intervention target. Therefore, tailored interventions aimed at improving HIL, particularly among AYA cancer survivors who often face employment instability, transitions in health insurance coverage, and limited prior experience navigating health insurance markets, are needed.^42,43 This includes embedding HIL screenings, standardized insurance education, or digital decision-support tools within care planning. These interventions that combine financial navigation with HIL support may be especially impactful in mitigating the long-term impact of FT while improving health care utilization and overall QOL.⁴²

While both HIL and health literacy play important roles in supporting survivors’ health outcomes, our findings suggest that the concepts have notable differences. Studies^35,42,43 have demonstrated that high health literacy does not equate to or guarantee high HIL. The latter remains significantly unrepresented in cancer literature when compared to health literacy. Housten’s systematic review⁴⁴ identified 87 intervention studies focused on health literacy among cancer populations. In contrast, no systematic reviews to date have examined HIL specifically among³⁵ AYA cancer survivors. Our current study was designed to address these gaps by comprehensively assessing both HIL and health literacy. Future studies could benefit from implementing nuanced assessments of HIL to capture its multidimensional aspects of confidence and knowledge, which are essential to designing tailored FT interventions in the AYA survivor population.

Our results extend prior work recognizing the need to understand HIL,²⁶ health literacy,⁴⁵ and sociodemographic variables¹⁶ among AYA cancer survivors within the context of cancer-related FT in survivors. In our sample of AYA cancer survivors, 44.6% of rural-residing participants and 25% of those identifying as Black/African American reported low levels of HIL. Our findings corroborate with previous studies,^44,46 demonstrating decreased HIL levels for rural residents when compared to their urban counterparts. Rural residents experience higher rates of poverty and lower rates of education and insurance coverage, thereby creating barriers that impede health care utilization.⁴⁶ This, coupled with a lack of standardized health insurance education programs and impending changes to Medicaid,⁴⁴ could further exacerbate the impact of low HIL and FT on rural populations. Although we did not find a significant relationship between HIL and race in our study, national trends demonstrate that racial and ethnic minorities have notably lower levels of HIL.^{34,44,47–49} In our prior publication based on this same data¹³ we found that Black/African American and rural AYA survivors experienced higher FT compared to their White and urban counterparts. When tailoring FT interventions for AYA cancer survivors, it is critical to consider sociodemographic factors to ensure those with lower HIL receive adequate support. Future research is needed to examine whether HIL is a mediator or moderator for FT across racial and rural populations to inform intervention design and implementation.

Sampling limitations in racial and rural groups may have impacted the multivariate analysis. Due to limited case availability via the KCR, racial/ethnic comparisons were limited to Black/African Americans and White individuals, and only English-speaking participants were included. These factors reduce the generalizability of the study and should be interpreted cautiously. While these limitations are important to acknowledge, the KCR had the most robust representation of Black/African American and rural-residing AYA cancer survivors in Kentucky, yielding high recruitment and enrollment rates. The cross-sectional approach limits nuanced understanding of the variables across the continuum of cancer care for AYA survivors, thus restricting our ability to explore how HIL, FT, and the relationship between the two variables may evolve over time. The three domains of FT were weighted equally despite the absence of formal statistical validation for this approach, which also serves as a limitation of this study.

Conclusion

Our study emphasizes the importance of examining the intersection of HIL and FT in the AYA cancer population. Results indicate the need to address HIL specifically among underserved populations to help mitigate the impact of cancer-related FT. Findings from this study informed the design and implementation of an oncology financial and legal navigation intervention to help reduce FT and improve QOL of pediatric and AYA cancer survivors and their caregivers with a focus on rural populations. While the intervention focuses on providing direct navigation services, it also provides resources to aimed at improving HIL to support decision-making around accessing timely care and engaging in cost of care conversations with providers. It is imperative that future studies continue to address the impact of HIL across the continuum of cancer care to better support the health and financial well-being of survivors.

Authors’ Contributions

All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. J.E.: Conception and design; acquisition, analysis and interpretation of data; writing—original draft; writing—review and editing; final approval. A.W.: Conception and design, analysis and interpretation of data, writing—original draft; writing—review and editing; final approval). M.C.: Acquisition, analysis and interpretation of data, writing—original draft; writing—review and editing; final approval. L.B.: Acquisition, analysis and interpretation of data, writing—original draft; writing—review and editing drafting original draft; final approval. K.D.N.: Conception and design; acquisition, analysis and interpretation of data; writing—review and editing; final approval. J.D’O.: Conception and design; acquisition, analysis and interpretation of data; writing—review and editing; final approval.

Data Sharing Agreement

The data underlying this article cannot be shared due to the privacy of individuals that participated in the study. As indicated, some variables of the dataset were derived from sources in the public domain: SEER.

Footnotes

Acknowledgment

This study was supported by the Kentucky Cancer Registry and the Patient Oriented and Population Science Shared Resource Facility, University of Kentucky Markey Cancer Center (P30CA177558).

Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by the UNITE Research Priority Area and Markey Cancer Center grant mechanism at the University of Kentucky. The funder did not play a role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the article; and the decision to submit the article for publication.

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