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. 2021 Sep 7;57(1):159–171. doi: 10.1111/1475-6773.13868

Insurance coverage change and survivorship care among young adult survivors of childhood cancer

Erin M Mobley 1,✉, Sue E Kim 2, Michael Cousineau 2, Jennifer Tsui 2, Kimberly A Miller 2,3, Jessica Tobin 4, David R Freyer 2,5,6, Joel E Milam 7
PMCID: PMC8763279  PMID: 34378205

Abstract

Objective

To (1) characterize change in type of insurance coverage among childhood cancer survivors from diagnosis to survivorship and (2) examine whether insurance change is associated with cancer‐related follow‐up care utilization.

Data Sources

Participants in this study were derived from the Project Forward study, a population‐based, observational study of childhood cancer survivors in Los Angeles County that used California Cancer Registry data to identify participants.

Study Design

Multivariable logistic regression models incorporating survey nonresponse weights estimated the change in the marginal predicted probabilities of insurance change and survivorship care, adjusting for demographic, socioeconomic, and clinical covariates and clustering by treating hospital.

Data Collection/Extraction Methods

Study participants were diagnosed with cancer who were younger than age 20 years while living in Los Angeles County from 1996 to 2010 and were older than the age 18 years at the time of survey participation, from 2015 to 2017 (N = 1106).

Principal Findings

Most participants were 18–26 years of age, male, diagnosed before 2004, Hispanic/Latino race/ethnicity, single, without children, highly educated, not employed full time, and lived with their parents at survey. Almost half (N = 529) of participants experienced insurance change from diagnosis to survivorship. Insurance change was associated with insurance coverage at diagnosis, as those who were uninsured were most likely to experience change and gain coverage during survivorship (by 51 percentage points [ppt], standard error [SE] of 0.05). Survivors who experienced any change had decreased probability of reporting a recent cancer‐related follow‐up care visit, a disparity that was magnified for those who lost insurance coverage (−5 ppt, SE 0.02 for those who gained coverage; −15 ppt, SE 0.04 for those who lost coverage).

Conclusions

Insurance coverage change was associated with lower cancer‐related follow‐up care utilization. Indeed, survivors who experienced any insurance coverage change had decreased probability of having a cancer‐related follow‐up care visit, and this was magnified for those who lost their insurance coverage.

Keywords: cancer survivors, health equity, insurance coverage, medically uninsured, patient‐reported outcome measures, survivorship

What is known on this topic

  • Lack of health insurance coverage is one of the strongest predictors of poor outcomes among cancer survivors in the United States.

  • Compared to their cancer nonaffected peers, childhood cancer survivors experience disparities in economic, health‐related quality of life, and social outcomes, and these disparities are magnified for those who are uninsured or underinsured.

  • Survivorship care is a clinical approach to address the health and well‐being of cancer survivors, ideally using risk‐based methods of surveillance, screening, management, and prevention of late effects, along with coordination of care; however, most survivors do not receive recommended care, particularly after transitioning to adulthood.

What this study adds

  • Changes in insurance coverage during survivorship were found to be associated with survivors' insurance coverage at diagnosis, as those who were uninsured at diagnosis were most likely to gain coverage during survivorship.

  • Survivors who experienced any change had decreased probability of reporting a recent cancer‐related follow‐up care visit, a disparity that was magnified for those who lost insurance coverage.

1. INTRODUCTION

It is estimated there are more than 500,000 childhood cancer survivors (CCS) in the United States who were diagnosed younger than age 21 years. 1 Despite gains in overall survival, CCS are at risk for adverse physical, psychosocial, and behavioral outcomes that range in severity and complexity. 1 , 2 Survivorship care is a clinical approach to address the health and well‐being of cancer survivors, ideally using risk‐based methods of surveillance, screening, management, and prevention of late effects, along with coordination of care. 1 , 3 However, most young survivors do not receive recommended care, particularly after transitioning into adulthood. 4 , 5 , 6

Lack of health insurance coverage is one of the strongest predictors of poor outcomes in the United States for cancer survivors. 7 , 8 CCS face many challenges regarding their long‐term outcomes, many of which are poorly understood. In fact, compared to their cancer nonaffected peers, CCS experience disparities in economic, health‐related quality of life, and social outcomes, and these disparities are magnified for CCS who are uninsured. 9 , 10 Improved insurance coverage decreases racial, ethnic, and socioeconomic health disparities in the general population. 11 However, a significant number of cancer survivors (about 8%) remain uninsured or underinsured despite the policy changes enacted in the Patient Protection and Affordable Care Act aimed at decreasing insurance disparities. 11 Access to survivorship care is influenced by insurance coverage, out‐of‐pocket costs, and lack of perceived need for survivorship care. 12 , 13 , 14 Furthermore, CCS are more likely to report forgoing or delaying care due to cost and lost annual productivity (e.g., loss of income). 13 , 15 Some survivors of lower socioeconomic status or those who recently transitioned from parental health insurance may face financial barriers to needed care. 16 , 17

Access barriers to survivorship care resulting in disparities for CCS have been documented by race, ethnicity, sex, socioeconomic status, insurance coverage, employment, education, and underserved or rural status. 4 , 14 , 17 , 18 , 19 , 20 , 21 Barriers to survivorship occur at different levels such as patient, provider, caregiver/family members, health system, and payer. 21 Despite publication and adoption of survivorship care or long‐term follow‐up guidelines by organizations such as the Children's Oncology Group (COG), National Comprehensive Cancer Network, American Society of Clinical Oncology, American Society of Pediatric Hematology and Oncology, American Academy of Pediatrics (AAP), and others, many CCS still do not receive adequate survivorship care. 6 , 22 , 23 , 24 , 25 , 26 Because of the growing number of CCS, pediatric oncologists do not have the ability to care for the survivorship needs of all CCS. Therefore, health care delivery systems that provide an early transition to adult internists or family medicine providers who have the ability to specialize in late effects may provide an ideal model. 27

Although research has examined the impact of insurance coverage on cancer diagnosis, treatment, and overall survival, very little is known about how changes in insurance coverage affect cancer survivors, particularly young survivors who are most at‐risk as many transition out of their parents' coverage as they approach 27 years of age. 28 The primary objective of this study was to characterize change in insurance coverage among CCS from diagnosis to survivorship and describe patient factors associated with these changes. To fully understand the impact of insurance changes, the secondary objective was to understand whether these changes in coverage and other patient factors impacted patient‐reported utilization of cancer‐related follow‐up care.

2. METHODS

This study used data collected as part of the Project Forward Cohort, a population‐based, observational study of CCS in Los Angeles (LA) County. 29 Participants in Project Forward were identified and recruited through the Los Angeles Cancer Surveillance Program, the population‐based cancer registry for LA County and part of the National Cancer Institute–funded Surveillance, Epidemiology, and End‐Results (SEER) program. 30 Eligible participants were diagnosed with cancer within the age of 20 years while living in LA County from 1996 to 2010 and were older than 18 years at the time of study recruitment (from 2015 to 2017). Study participants were asked to complete a survey regarding their survivorship care, administered either electronically or on paper. 29 Responder analyses of demographic and clinical variables from registry data indicated no differences between cohort responders and nonresponders in age at diagnosis, years since diagnosis, age at study, cancer diagnosis, or stage of disease at diagnosis. 29 However, survey respondents were more likely to be female (vs. male), Non‐Hispanic/Latino white, and higher (vs. lower) socioeconomic status (SES). 29 These differences were accounted for using survey weights, described in the analysis section below. This study was approved by the institutional review board at the University of Southern California (HS‐14‐00817), the California State Committee for the Protection of Human Subjects, and the California Cancer Registry.

2.1. Theoretical framework

This study used an approach adapted from Andersen's Behavioral Model (see Figure 1). 31 , 32 The underlying assumption of this model is that the utilization outcome of having a follow‐up care visit is based on three factors as follows: characteristics that determine the propensity to use health services (predisposing factors), ability to secure the use of services via self/family or community characteristics (enabling factors), and the illness level of the individual (need factors). 32

FIGURE 1.

FIGURE 1

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Conceptual model adapted from Andersen's Behavioral Model.

*Change in insurance coverage was only included in model 2 predicting engagement in cancer‐related follow‐up care

2.2. Measures

Predisposing factors included demographic (sex, age, year of diagnosis, race and ethnicity, and marital status) and social structure characteristics (having children, educational attainment, receipt of federal or state supplemental income, full‐time employment, and living with parents). 32 Data reported by the cancer registry include age and date of diagnosis, sex, and race and ethnicity (Hispanic/Latino, non‐Hispanic/Latino white, non‐Hispanic/Latino Asian, non‐Hispanic/Latino black, and non‐Hispanic/Latino other). Age was coded as a binary variable indicating those aged 27–39 years at survey to account for the anticipated transition from parental insurance coverage at age 26 years. Data from the self‐reported survey include marital status, number of children, educational attainment, supplemental income, employment status, and living arrangement (e.g., whether the respondent lives with their parents).

The enabling factor provided by the cancer registry was insurance coverage at diagnosis, which was derived from the “payer” variable and collapsed into categories of (1) “private,” (2) “TRICARE/VA” (also included Indian Health Service), (3) “other,” which captured insured, not otherwise specified, (4) “Medicaid,” (5) “Medicare,” and (6) “uninsured or unknown.” Enabling factors that were collected in the survey included current insurance coverage, insurance understanding (including appropriate use of an existing health insurance plan and corresponding benefits), access constraints (including difficulties with getting a referral and the ability to see the doctor when needed), family and friend influences upon health decisions, knowledge about and intention to pursue survivorship care, and receipt of a written treatment summary. Responses to the question about type of insurance coverage at the time of survey were considered (1) “private” if answered health insurance through work or school, health insurance through a spouse or parent, Covered California (insurance obtained through the health insurance exchange in California), or an individual plan; (2) “TRICARE/VA” included TRICARE, Veteran's Administration, military, or Indian Health Service plans; (3) “other” captured insured, not otherwise specified; (4) “Medicaid” that included Medicaid, MediCal, or Myhealth LA; (5) “Medicare,” that included dual‐eligible coverage; and (6) “uninsured or unknown.” 33

Cancer diagnosis (adapted from the International Classification of Childhood Cancers) was reported by the cancer registry and considered a need factor. 34 Survey items capturing need factors included self‐rated health and discussion of survivorship care needs with a provider. Treatment data from the cancer registry were combined with treatment data collected in the survey to calculate the Intensity of Treatment Rating Scale (ITR‐3) and was used as a need factor. 35 , 36 These data produced a four‐level ITR scale from least (score of 1) to most intensive (score of 4) treatment.

2.3. Outcomes

The outcome of the first model was insurance change, which was derived based on any change in the type of insurance coverage from diagnosis to survivorship, similar to Cassedy et al. 37 The six categories of insurance at survey were compared to the corresponding six categories of insurance at diagnosis to produce a composite variable reflecting changes in insurance coverage. We considered those with no change in coverage from diagnosis to survivorship (whether private, public, or uninsured) to have stable coverage. CCS who experienced insurance change could have had any change in the type of coverage. Among those who experienced a change, we categorized any change that resulted in coverage during survivorship as “gaining coverage” (e.g., uninsured to private, private to public, TRICARE/VA to Medicaid). CCS who experienced any change that resulted in no coverage during survivorship were categorized as “losing coverage” (e.g., private to uninsured). The second outcome we examined was utilization of cancer‐related follow‐up care during the prior 2 years. This was derived from a survey question asking, “When did you last see a doctor for cancer‐related follow‐up care?” with a note stating that cancer‐related follow‐up care is “where a doctor examined you and did tests to see if you had any health problems from cancer or the cancer treatment you received.” The response options included within the past year, 1–2 years ago, more than 2 years ago, and never. For the purposes of this study, if the respondent indicated within the past year or 1–2 years ago, they were considered to have had cancer‐related follow‐up care (from any type of provider).

2.4. Analyses

Descriptive statistics were calculated to examine the association between insurance coverage change and each of the independent variables described as predisposing, enabling, and need factors according to Andersen's Behavioral Model. Multivariate analyses were conducted using two regression models described below. Data were weighted to be representative of the survey population, and multivariable models were adjusted for predisposing, enabling, and need characteristics, clustered by treating hospital using the “svy” command in STATA. Standard errors were robust (specified as unconditional for the multinomial logit regression model), and we used α = 0.05 level of significance for all models. Analyses were conducted using STATA version 15.1.

First, we used a multinomial logit regression model to determine which independent variables were associated with insurance change. This allows us to understand how each independent variable shifts the distribution of insurance change in our sample while holding the other independent variables constant. For instance, a significant, positive coefficient from the multinomial logit model for a particular independent variable indicates that an increase in the value of that variable would shift the distribution of insurance coverage toward change. We used the “margins” command in STATA to transform the coefficients obtained from multinomial logit model to display the average marginal effects, which allows the estimate to incorporate the magnitude of change in probability of being in each category of insurance change when the value of the independent variable was increased. The multinomial logit results presented refer to the change in probability of a CCS being in one of the three insurance change categories based on their classification of an independent variable, holding all else constant and in reference to the reference group. Second, a logit regression model was used to describe the average change in the marginal predicted probability of the binary outcome of utilization of cancer‐related follow‐up care based on each independent variable (relative to the applicable reference group), holding all else constant.

3. RESULTS

A total of 1106 survivors participated in the Project Forward survey and were included in this study. 29 Most respondents were 18–26 years of age at survey, male, diagnosed before the Children's Oncology Group (COG) Guidelines were published in 2004, of Hispanic/Latino race/ethnicity, single, without children, highly educated, employed part‐time or unemployed, and lived with their parents at the time of survey (see Table 1). At diagnosis, 666 (58%) of CCS were privately covered, 386 (37%) were publicly covered, and 54 (5%) were uninsured (see Figure 2). During survivorship, there was an increase in the proportion of CCS who were uninsured resulting in 609 (54%) CCS who were privately covered, 360 (34%) covered by public insurance, and 137 (13%) who were uninsured. Just over half (52%) of survivors maintained insurance coverage with no change, while 48% experienced some form of insurance change (36% of which gained coverage and 12% who lost coverage). Most survivors had continuous, private coverage or gained private coverage; however, among those who lost coverage, most were publicly insured at diagnosis. Additionally, the median time from diagnosis to survivorship was similar across insurance change groups (14 years for those who maintained or lost coverage; 15 years for those who gained coverage).

TABLE 1.

Characteristics of sample by predisposing, enabling, and need factors a

Variable Category Overall No change Change Change Sig.
Continuous coverage Gained coverage Lost coverage
N = 1106 577 (52%) 399 (36%) 130 (12%)
Predisposing factors b
Age at survey 18–26 years 635 (58%) 363 (63%) 196 (49%) 76 (59%) ***
27–39 years 471 (42%) 214 (37%) 203 (51%) 54 (41%)
Sex Male 544 (54%) 273 (52%) 197 (54%) 74 (62%) *
Female 562 (46%) 304 (48%) 202 (46%) 56 (38%)
Year of diagnosis 1996–2003 (pre‐COG guidelines) 677 (61%) 333 (58%) 269 (67%) 75 (59%) *
2004–2010 (post‐COG guidelines) 429 (39%) 244 (42%) 130 (33%) 55 (41%)
Race and ethnicity Hispanic/Latino 570 (54%) 266 (49%) 217 (57%) 87 (69%) *
Non‐Hispanic/Latino White 324 (27%) 195 (32%) 108 (25%) 21 (15%)
Non‐Hispanic/Latino Asian 107 (9%) 61 (10%) 33 (8%) 13 (9%)
Non‐Hispanic/Latino Black 54 (5%) 20 (4%) 27 (6%) 7 (5%)
Non‐Hispanic/Latino Other 52 (5%) 35 (6%) 15 (4%) 2 (1%)
Marital status Non‐single 355 (32%) 168 (29%) 136 (34%) 51 (39%) *
Single 751 (68%) 409 (72%) 263 (66%) 79 (61%)
Children No 889 (80%) 476 (83%) 306 (77%) 107 (83%)
Yes 217 (20%) 101 (17%) 93 (23%) 23 (17%)
Educational attainment High school graduate or less 278 (26%) 136 (25%) 86 (22%) 56 (43%) ***
Some college or college graduate 828 (74%) 441 (76%) 313 (78%) 74 (57%)
Received supplemental income No or unknown 924 (83%) 495 (85%) 312 (79%) 117 (90%) *
Yes 182 (17%) 82 (15%) 87 (21%) 13 (10%)
Employment status Part‐time or unemployed 632 (57%) 332 (58%) 216 (53%) 84 (64%)
Full‐time 474 (43%) 245 (42%) 183 (47%) 46 (36%)
Living arrangement Do not live with parents 538 (48%) 280 (48%) 188 (47%) 70 (53%)
Live with parents 568 (52%) 297 (52%) 211 (53%) 60 (47%)
Enabling factors b
Insurance at diagnosis Private, TRICARE/VA, and insured, NOS 666 (58%) 394 (66%) 209 (51%) 63 (49%) **
Medicaid and/or Medicare 386 (37%) 176 (33%) 143 (38%) 67 (51%)
Uninsured and unknown 54 (5%) 7 (1%) 47 (12%) –
Insurance at survey Private, TRICARE/VA, and insured, NOS 609 (54%) 394 (66%) 215 (55%) – ***
Medicaid and/or Medicare 360 (34%) 176 (33%) 184 (45%) –
Uninsured and unknown 137 (13%) 7 (1%) – 130 (100%)
Insurance understanding Not at all 325 (30%) 127 (23%) 78 (19%) 120 (92%) ***
Very well or somewhat 781 (70%) 450 (77%) 321 (81%) 10 (8%)
Difficulty with referral to specialist Easy or unknown 844 (76%) 467 (80%) 293 (73%) 84 (65%) **
Difficult 262 (24%) 110 (20%) 106 (27%) 46 (35%)
Unable to see doctor when needed No or unknown 837 (76%) 459 (79%) 298 (75%) 80 (62%) ***
Yes 269 (24%) 118 (21%) 101 (25%) 50 (42%)
Friend influence of health decisions No 702 (63%) 370 (64%) 248 (61%) 84 (66%)
Yes 404 (37%) 207 (36%) 151 (39%) 46 (34%)
Family influence of health decisions No 171 (16%) 78 (14%) 67 (17%) 26 (20%)
Yes 935 (84%) 499 (86%) 332 (84%) 104 (80%)
Census track‐level socioeconomic status Lowest quintile 344 (35%) 155 (30%) 137 (38%) 52 (44%) ***
Lower‐middle quintile 283 (21%) 108 (19%) 96 (23%) 34 (24%)
Middle quintile 167 (15%) 80 (13%) 68 (16%) 19 (14%)
Upper‐middle quintile 180 (15%) 116 (18%) 50 (11%) 14 (9%)
Upper quintile 177 (15%) 118 (19%) 48 (11%) 11 (8%)
Knowledge of follow‐up care No 408 (37%) 205 (35%) 143 (37%) 60 (46%)
Yes 698 (63%) 372 (65%) 256 (63%) 70 (54%)
Intention to pursue follow‐up care No 398 (36%) 183 (32%) 143 (36%) 72 (56%) ***
Yes 708 (64%) 394 (69%) 256 (64%) 58 (44%)
Written treatment summary Not received 625 (57%) 302 (52%) 235 (59%) 88 (69%) **
Received 481 (43%) 275 (48%) 164 (41%) 42 (31%)
Need factors b
Diagnosis Leukemia 395 (36%) 209 (37%) 139 (35%) 47 (36%)
Lymphoma 241 (22%) 114 (19%) 101 (26%) 26 (20%)
Brain or central nervous system 153 (14%) 86 (15%) 49 (12%) 18 (13%)
Neuro., retino., renal, hep., germ cell 119 (11%) 57 (10%) 46 (11%) 16 (13%)
Bone or sarcoma 96 (9%) 48 (8%) 35 (9%) 13 (11%)
Other carcinoma 102 (9%) 63 (11%) 29 (7%) 10 (7%)
Intensity of treatment rating (ITR) ITR: 1 69 (6%) 39 (7%) 22 (5%) 8 (6%)
ITR: 2 344 (31%) 184 (31%) 125 (32%) 35 (27%)
ITR: 3 544 (50%) 274 (48%) 202 (51%) 68 (53%)
ITR: 4 149 (13%) 80 (14%) 50 (12%) 19 (14%)
Self‐rated health Good, very good, or excellent 888 (80%) 484 (83%) 306 (77%) 98 (75%) ***
Poor or fair 218 (20%) 93 (17%) 93 (23%) 32 (25%)
Ever discussed follow‐up care No 545 (50%) 261 (46%) 208 (53%) 76 (59%) ***
Yes 561 (50%) 316 (54%) 191 (47%) 54 (41%)
Engagement in follow‐up care No follow‐up care during prior 2 years 474 (43%) 201 (35%) 185 (47%) 88 (67%) ***
Follow‐up care during prior 2 years 376 (65%) 214 (53%) 42 (33%)
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Note: Diagnosis was categorized based on the International Classification of Childhood Cancers 34 ; Neuro., retino., renal, hep., germ cell includes neuroblastoma, retinoblastoma, renal tumors, hepatic tumors, and germ cell tumors.

Abbreviations: COG, Children's Oncology Group; ITR, intensity of treatment rating; NOS, not otherwise specified.

a

Sample sizes are unweighted; column percentages are weighted.

b

Source: Adapted from Andersen's Behavioral Model. 31

*

p < 0.05; **p < 0.01; ***p < 0.001.

FIGURE 2.

FIGURE 2

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Insurance coverage change from diagnosis to survivorship.

“No change” in insurance coverage represents survivors who did not have a change in the type of coverage from diagnosis to survivorship; these were categorized as those who experienced continuous coverage that was (1) private (also includes insured, not otherwise specified), (2) public, or (3) uninsured and unknown. “Change” in insurance coverage indicates survivors who did have a change in the type of coverage from diagnosis to survivorship; those who gained coverage experienced any type of change in insurance coverage and were insured during survivorship (e.g., private coverage to public coverage); those who lost coverage changed from being insured at diagnosis to being uninsured at survivorship

Table 2 displays the average marginal effect from the multinomial logit regression model predicting insurance change, which indicates how each independent variable is associated with the probability of insurance coverage change. Regarding the predisposing factors, compared to those ages 18–26 at survey, CCS ages 27–39 were 8 percentage points (ppt) less likely to remain continuously covered and 8 ppt more likely to gain coverage, after controlling for all other independent variables. Females (compared to males) were 4 ppt more likely to remain continuously covered. In comparison to their non‐Hispanic/Latino white counterparts, Hispanic/Latino and Asian CCS were 5 and 7 ppt more likely to experience a change and lose coverage. CCS who were single at the time of survey (compared to their nonsingle peers) were less likely to lose coverage by 3 ppt. In comparison to those who were a high school graduate or less, those with some college of a college graduate were more likely to gain coverage by 9 ppt and less likely to lose coverage by 6 ppt. Receipt of supplemental income was associated with experiencing any change, gaining coverage by 12 ppt, and losing coverage by 7 ppt.

TABLE 2.

Effects of predisposing, enabling, and need factors on the probability of change in insurance coverage among childhood cancer survivors

Variable Category No change Change Change
Continuous coverage (N = 577) Gained coverage (N = 399) Lost coverage (N = 130)
Change in probability (standard error)
Predisposing factors a
Age at survey 18–26 years Ref. Ref. Ref.
27–39 years −0.08 * (0.03) 0.08** (0.02) 0.00 (0.02)
Sex Male Ref. Ref. Ref.
Female 0.04** (0.02) −0.03 (0.02) −0.02 (0.01)
Race and ethnicity Non‐Hispanic/Latino White Ref. Ref. Ref.
Hispanic/Latino −0.01 (0.06) −0.04 (0.06) 0.05** (0.02)
Non‐Hispanic/Latino Asian −0.01 (0.09) −0.06 (0.09) 0.07*** (0.02)
Non‐Hispanic/Latino other −0.02 (0.05) −0.01 (0.06) 0.02 (0.03)
Marital status Non‐single Ref. Ref. Ref.
Single 0.05 (0.04) −0.00 (0.04) −0.03* (0.02)
Educational attainment High school graduate or less Ref. Ref. Ref.
Some college or college graduate −0.03 (0.03) 0.09*** (0.02) −0.06*** (0.02)
Received supplemental income No or unknown Ref. Ref. Ref.
Yes −0.04 (0.05) 0.12** (0.04) −0.07** (0.02)
Enabling factors a
Insurance at diagnosis Private, TRICARE/VA, and insured, NOS Ref. Ref. Ref.
Medicaid and/or Medicare −0.04 (0.03) 0.04 (0.03) 0.01 (0.01)
Uninsured and unknown −0.38*** (0.05) 0.51*** (0.05) −0.13*** (0.01)
Insurance understanding Not at all Ref. Ref. Ref.
Very well or somewhat 0.11*** (0.02) 0.16*** (0.03) −0.27*** (0.01)
Census track‐level socioeconomic status Lowest quintile Ref. Ref. Ref.
Lower‐middle quintile −0.03 (0.04) 0.02 (0.04) 0.01 (0.01)
Middle quintile −0.06 (0.05) 0.02 (0.05) 0.04* (0.02)
Upper‐middle quintile 0.11* (0.05) −0.09* (0.04) −0.02 (0.02)
Upper quintile 0.14* (0.06) −0.10* (0.05) −0.04 (0.03)
Need factors a
Intensity of treatment rating (ITR) ITR: 1 −0.03 (0.07) 0.01 (0.06) 0.02 (0.04)
ITR: 2 −0.04 (0.03) 0.07* (0.03) −0.03** (0.01)
ITR: 3 −0.02 (0.03) 0.03 (0.03) −0.00 (0.01)
ITR: 4 Ref. Ref. Ref.
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Note: Coefficients represent the individual marginal effects, which were estimated as the marginal effect averaged across survivors to explain the size of the change in the probability of no change: continuous coverage, change: gained coverage, or change: lost coverage from diagnosis to survivorship. Model was adjusted for the following, which were not significant: children, employment status, educational attainment, difficultly with referral to specialist, ability to see the doctor when needed, friend and family influence of health decisions, diagnosis, and self‐rated health.

Abbreviation: NOS, not otherwise specified.

a

Source: Adapted from Andersen's Behavioral Model. 31

*

p < 0.05; **p < 0.01; ***p < 0.001.

Enabling factors indicated that compared to those with private coverage, CCS who were uninsured or had unknown insurance coverage during survivorship were less likely to experience continuous coverage by 38 ppt, more likely to gain coverage by 51 ppt, and less likely to lose coverage by 13 ppt, holding all else constant. CCS who understood their insurance very well or somewhat (in comparison to those who did not) were more likely to remain continuously covered by 11 ppt, more likely to gain coverage by 16 ppt, and less likely to lose coverage by 27 ppt. When compared to those from the lowest Census track‐level socioeconomic status quintile, participants from areas fitting the description of the middle quintile were more likely to experience a change and lose coverage by 4 ppt, and those from the upper‐middle and upper quintiles were more likely to have stable continuous coverage by 11 and 14 ppt, respectively. However, CCS from the upper‐middle and upper quintiles were less likely to experience a change and gain coverage by 9 and 10 ppt, respectively (holding all else constant). Finally, regarding need factors, in comparison to CCS who received the most intense treatment (measured by ITR: 4), those who received treatment corresponding to ITR: 2 were more likely to experience a change and gain coverage by 7 ppt and lose coverage by 3 ppt. See Figure 3 for a visual depiction of the significant predisposing, enabling, and need factors impacting change in insurance coverage.

FIGURE 3.

FIGURE 3

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Significant predisposing, enabling, and need factors impacting the probability of change in insurance coverage among childhood cancer survivors.

“No change” in insurance coverage represents survivors who did not have a change in the type of coverage from diagnosis to survivorship; these were categorized as those who experienced continuous coverage that was (1) private (also includes insured, not otherwise specified), (2) public, or (3) uninsured and unknown. “Change” in insurance coverage indicates survivors who did have a change in the type of coverage from diagnosis to survivorship; those who gained coverage experienced any type of change in insurance coverage and were insured during survivorship (e.g., private coverage to public coverage); those who lost coverage changed from being insured at diagnosis to being uninsured at survivorship

The multivariable logit regression results (Table 3) display the association between utilization of cancer‐related follow‐up care in the prior 2 years, taking into consideration insurance change and holding each independent variable constant. CCS who experienced any insurance change were less likely to report receipt of cancer‐related follow‐up care in comparison to those with stable coverage (a 5 ppt decline for those who gained coverage and 15 ppt decline for those who lost coverage). CCS who were publicly covered (in comparison to those who were privately insured) were more likely to have a cancer‐related follow‐up care visit by 5 ppt.

TABLE 3.

Effects of change in insurance coverage and insurance at diagnosis on the probability of having a cancer‐related follow‐up care visit during the prior 2 years among childhood cancer survivors

Variable Category Cancer‐related follow‐up care (N = 1106)
Change in probability (standard error)
Insurance change No change: Continuous coverage Ref.
Change: gained coverage −0.05 * (0.02)
Change: lost coverage −0.15*** (0.04)
Insurance at diagnosis Private, TRICARE/VA, and Insured, NOS Ref.
Medicaid and/or Medicare 0.05** (0.02)
Uninsured and unknown 0.01 (0.04)
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Note: Coefficients represent the individual marginal effects, which were estimated as the marginal effect averaged across survivors to explain the size of the change in the probability of engagement in cancer‐related follow‐up care during the prior 2 years. Model was adjusted for covariates based on findings from the Project Forward Cohort population‐based study, 29 which were also significant in this model: year of diagnosis, race and ethnicity, employment status, knowledge of follow‐up care, intention to pursue follow‐up care, written treatment summary, intensity of treatment rating, and ever discussed follow‐up care. Model was also adjusted for the following covariates that were not significant: marital status, children, educational attainment, receipt of federal or state supplemental income, living arrangement, insurance understanding, difficultly with referral to specialist, ability to see the doctor when needed, friend and family influence of health decisions, socioeconomic status, diagnosis, and self‐rated health.

Abbreviation: NOS, not otherwise specified.

*

p < 0.05; **p < 0.01; ***p < 0.001.

4. DISCUSSION

In this population‐based study of a diverse cohort of CCS in Los Angeles County, insurance change was significantly associated with survivors' predisposing and enabling factors and less so with need factors. 31 , 32 This study builds upon the findings from the Project Forward Study and provides a unique approach to examining insurance coverage at diagnosis and change in insurance coverage during survivorship, and how these factors impact cancer‐related follow‐up care. 29 Notably, this study found that CCS who experienced any insurance change (losing or gaining coverage) had decreased probability of having a cancer‐related follow‐up care visit, and this disparity was largest for those who lost coverage during survivorship.

In this sample, most participants had stable, private coverage or gained private coverage during survivorship; however, among those who lost coverage, most were publicly insured at diagnosis. These findings highlight potential groups to target for intervention studies. CCS who experienced no change in insurance coverage were more likely to understand their insurance, to be female, and from areas of higher socioeconomic status. CCS who were ages 27–39 at survey, highly educated, received supplemental income, understood their insurance very well or somewhat, or received less intense treatment had increased probability of experiencing a positive gain due to insurance coverage change during survivorship. Among those who lost coverage, a higher proportion of Hispanic/Latino or Asian CCS and those from the middle SES quintile experienced a change. CCS who lost coverage were less likely to be single, highly educated, receive supplemental income, and report not understanding their health insurance or benefits. For example, these socioeconomic, racial, or ethnic subgroups may reflect employment instability (leading to change in insurance coverage) or the dilemma of the “working poor” (those who are “gig” workers without benefits and/or working but caught in a coverage gap where they exceed the income eligibility thresholds for public programs or social services and still struggle to afford health care expenses). Prior work has shown that late effects of cancer treatment can negatively impact employment, leading to instability or change in employer‐based insurance coverage. 38

Change in insurance coverage had a significant impact on cancer‐related follow‐up care utilization, as we observed a significant decline in the probability of having a visit for CCS who experienced any insurance change. Differences in cancer‐related follow‐up care utilization among CCS who are Hispanic/Latino, Asian, or those who received less intense treatment are aligned with prior studies. 18 , 29 These results underscore the importance of increasing health insurance accessibility for this population of young adult CCS who often find themselves in the midst of social, professional, residential, and financial transition. For example, social workers or financial counselors at cancer treatment facilities could counsel patients and their families about the importance of maintaining insurance coverage during survivorship. In fact, at 72% of NCI Community Oncology Research Program (NCORP) practices and 76% of National Comprehensive Cancer Network (NCCN) facilities, patients are routinely screened for financial distress. 39 , 40 Perhaps, if screening for insurance accessibility becomes standard of care prior to the transition to survivorship, it could lead to improved utilization of survivorship care. Furthermore, this presents an opportunity for enhanced collaboration across various providers to help facilitate the transition from pediatric oncology care to adult internists or family medicine providers who have the ability to specialize in late effects. 27

Few, if any, studies have examined insurance coverage changes from childhood diagnosis to young adult survivorship, and associate those changes with cancer‐related follow‐up care. However, our findings are consistent with prior studies among, for example, adult breast cancer survivors among whom insurance coverage disruptions were associated with less use of preventive services and more issues with affordability of care. 41 , 42 Using data from the Behavioral Risk Factor Surveillance System from 2011 to 2017 (before and after Medicaid expansion in 2014), a study of adults under age 65 diagnosed with cancer found temporal decreases in the proportion of uninsured survivors and survivors indicating they struggled with affordability of care. 41 In that study, the largest improvement was seen among those living in Medicaid expansion states. 41 Our study shows that CCS covered by Medicaid at diagnosis had an increased probability of having a cancer‐related follow‐up visit in comparison to those who were privately covered at diagnosis. However, we also observed that there was an increase in the number of uninsured CCS from diagnosis (1996–2010) to survivorship (2015–2017, following Medicaid expansion). In our study, 13% of our sample was uninsured in survivorship, which is slightly higher than prior studies using samples derived from the Childhood Cancer Survivor Study, whose estimates range from about 7% to 10%. 43 , 44 Notably, survivors who experienced any coverage change had decreased probability of having a cancer‐related follow‐up care visit. This finding suggests that any period of uninsurance or under‐insurance can have a lasting impact and that continuity of insurance coverage is important when considering strategies to decrease barriers to care. These findings are aligned with other prior literature documenting persistent disparities or differences among groups who have gained coverage. 45 , 46

Strengths of this study include the diverse, population‐based sample of CCS representing the most common malignancies for children who were diagnosed from 1996 to 2010, both before and after the publication of the first edition of the COG Long‐Term Follow‐Up Guidelines in 2003. 47 Nevertheless, this sample may not be reflective of CCS residing in other areas of the United States and caution is needed when generalizing to other populations. However, our sample is highly diverse with regard to race, ethnicity, sex, socioeconomic status, year of diagnosis, and current age, and we conducted weighted analyses to adjust for survey nonresponse bias. Although this longitudinal study assessed change in insurance coverage from diagnosis to survivorship, we were unable to examine frequent changes in insurance coverage during the interim time period due to limitations in available data. Additionally, there are some limitations inherent in the treatment data collected by SEER, as it only includes initial therapy that may result in some missing data when calculating the ITR. However, treatment data available in SEER has been shown to be robust when used as an estimator for ITR. 36 Future work concerning insurance coverage would benefit, for example, by integrating insurance claims to examine more detailed nuances and terms of coverage regarding of insurance status.

Insurance change was associated with lower cancer‐related follow‐up care utilization. Survivors who experienced any insurance coverage change had decreased probability of having a cancer‐related follow‐up care visit, and this was magnified for those who lost their insurance coverage. The results of this study underscore the importance of continued efforts to examine changes or instability in insurance coverage and ensure continuity of insurance coverage to prevent disparities in and barriers to survivorship care, with the ultimate goal of improving outcomes for young adult CCS.

CONFLICT OF INTEREST

No potential conflicts of interest for any of the authors of this manuscript exist.

DISCLAIMER

The contents do not represent the views of the US Department of Veterans Affairs or the US Government.

ACKNOWLEDGMENTS

We would like to thank the National Cancer Institute for funding this important work and our collaborators in the USC Center for Young Adult Cancer Survivorship Research for their support of our research endeavors. Most importantly, we would like to thank all of the cancer survivors who participated in the Project Forward study, without whom we would not have been able to produce this manuscript.

Mobley EM, Kim SE, Cousineau M, et al. Insurance coverage change and survivorship care among young adult survivors of childhood cancer. Health Serv Res. 2022;57(1):159‐171. doi: 10.1111/1475-6773.13868

Funding information Erin M. Mobley was supported by the National Institutes of Health Division of Loan Repayment through a National Cancer Institute Pediatric Extramural Loan Repayment Award to conduct this study (1L40CA253827‐01). Erin M. Mobley and Jessica Tobin were supported by 5T32CA009492‐34 from the National Cancer Institute. Jessica Tobin was also supported by the VA Office of Academic Affiliations through the Advanced Fellowship Program in Health Services Research and Development. The data collection for this project was funded by R01MD007801 from the National Institute on Minority Health and Health Disparities (Michael Cousineau, Kimberly A. Miller, Jessica Tobin, David R. Freyer, and Joel E. Milam). Additional support was provided by P30CA014089 from the National Cancer Institute.

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