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Address correspondence to: Anne R. Markus, PhD, Department of Health Policy and Management, Milken Institute School of Public Health, The George Washington University, 950 New Hampshire Avenue Northwest, Washington DC 20052.
Department of Health Policy and Management, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia
Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia
Department of Health Policy and Management, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia
Little attention has been paid to the influence of individually measured social determinants of health on cancer screening tests in the Medicaid population.
Methods
Analysis was conducted on 2015–2020 claims data from a subgroup of Medicaid enrollees from the District of Columbia Medicaid Cohort Study (N=8,943) who were eligible for colorectal (n=2,131), breast (n=1,156), and cervical cancer (n= 5,068) screening. Participants were grouped into 4 distinct social determinants of health groups on the basis of their responses to social determinants of health questionnaire. This study estimated the influence of the 4 social determinants of health groups on the receipt of each screening test using log-binomial regression adjusted for demographics, illness severity, and neighborhood-level deprivation.
Results
The receipt of cancer screening tests was 42%, 58%, and 66% for colorectal, cervical, and breast cancer, respectively. Those in the most disadvantaged social determinants of health group were less likely to receive a colonoscopy/sigmoidoscopy than those in the least disadvantaged one (adjusted RR=0.70, 95% CI=0.54, 0.92). The pattern for mammograms and Pap smears was similar (adjusted RR=0.94, 95% CI=0.80, 1.11 and adjusted RR=0.90, 95% CI=0.81, 1.00, respectively). In contrast, participants in the most disadvantaged social determinants of health group were more likely to receive fecal occult blood test than those in the least disadvantaged one (adjusted RR=1.52, 95% CI=1.09, 2.12).
Conclusions
Severe social determinants of health measured at the individual level are associated with lower cancer preventive screening. A targeted approach that addresses the social and economic adversities that affect cancer screening could result in higher preventive screening rates in this Medicaid population.
INTRODUCTION
Cancer is the second leading cause of death in the U.S.
Breast cancer is the most commonly diagnosed cancer and the second most common cause of cancer deaths, whereas colorectal cancer is the fourth most commonly diagnosed and the third cause of cancer deaths for both women and men nationwide.
Cancer stat facts: female breast cancer. NIH, National Cancer Institute, Surveillance, Epidemiology, and End Results Program. https://seer.cancer.gov/statfacts/html/breast.html. Accessed August 22, 2022.
People with more education and higher incomes generally have lower cancer death rates than others, but even so, they may experience disparities owing to their race or ethnicity: Blacks have the highest cancer death rate of all racial groups regardless of socioeconomic position.
Higher rates of preventive health care with commercial insurance compared with Medicaid: findings from the Arkansas Health Care Independence “Private Option” Program.
Association of neighborhood measures of social determinants of health with breast, cervical, and colorectal cancer screening rates in the U.S. Midwest.
Since 2010, public and private insurers must cover preventive services recommended by the U.S. Preventive Services Task Force, for which there is high or moderate certainty that the net benefit is substantial (i.e., Grade A) or moderate (i.e., Grade B).
42 U.S. Code § 300gg–13 - coverage of preventive health services. Ithaca, NY: Legal Information Institute. https://www.law.cornell.edu/uscode/text/42/300gg-13. Published March 23, 2010. Accessed August 9, 2022.
However, population- and state-based analyses of claims data show lower rates of cancer screening among Medicaid enrollees than among commercially insured individuals.
Higher rates of preventive health care with commercial insurance compared with Medicaid: findings from the Arkansas Health Care Independence “Private Option” Program.
Multiple determinants contribute to individual cancer risk and survival, including biological/genetic, environmental, health care, and social determinants of health (SDH).
SDH are the nonmedical factors that influence health outcomes. SDH include the conditions in which people are born, grow, work, live, and age as well as the wider set of economic policies and systems, social norms, social policies, and political systems that shape them.
Although a number of studies have evaluated the role of health policies (i.e., expanded coverage, copayments, provider reimbursement) on cancer screening rates in the Medicaid population, few have examined the influence of SDH factors. The purpose of this paper is to estimate the influence of an aggregate set of individually measured SDH factors on the cancer screening rates of a cohort of adults insured by the District of Columbia (DC) Medicaid program, controlling for demographics, disease severity, and area-level deprivation. Cancer screening test completion was hypothesized to be lower among Medicaid enrollees with the most social and economic adversities than among those with the fewest.
METHODS
This study took advantage of data collected as part of a prospective cohort study, known as the DC Medicaid Cohort Study (N=8,943 adult Medicaid enrollees)
and examined the relationship between SDH grouped into 4 distinct social risk groups and the receipt of screening tests for 3 cancers. The study identified participants eligible for a colorectal (n=2,131), breast (n=1,156), and/or cervical (n=5,068) cancer screening test on the basis of the U.S. Preventive Services Task Force recommendations
and determined completion of a colorectal, breast, and cervical cancer screening test as defined in the Healthcare Effectiveness Data and Information Set guidelines.
Separate models were developed using Medicaid claims over a 4-year period for the receipt of at least 1 colorectal, breast, and cervical cancer screening test as a function of social risk group, age, sex, morbidity burden, having a regular medical provider, length of Medicaid coverage, and neighborhood deprivation.
Study Sample
The parent study screened adult Medicaid enrollees at the time of a healthcare visit to an emergency department, primary care office, or obstetrics and gynecology office affiliated with 1 of 2 DC hospitals over a 16-month period starting in September 2017 and ending in December 2018. Patients had to be aged between 18 and 64 years at the time of study enrollment, had to be insured by the DC Medicaid program, and had to have access to a telephone. Patients were deemed ineligible if unable to understand consent, non-English speaking, or also insured by Medicare.
Eligibility for this analysis is based on the cancer screening test using sex, participants aging 2 years before study enrollment, and having medical history during a 2-year period before study enrollment (Appendix Table 1, available online, shows the medical exclusion criteria). Participants had to be aged at least 50 years without a previous history of colorectal cancer or total colectomy procedure or be female, had to be aged ≥50 years with no previous history of bilateral mastectomy or be female, or had to be aged at least 21 years with no previous history of a hysterectomy. Relatively few participants were excluded owing to medical contraindications (Figure 1). The sample consists largely of Black Medicaid enrollees (91%).
The receipt of at least 1 colorectal, breast, or cervical cancer screening test during a 4-year study period (2 years before and 2 years after study enrollment) was the main study outcome. It was identified using the Current Procedural Terminology/Healthcare Common Procedure Coding System codes detailed in the 2018 Healthcare Effectiveness Data and Information Set resource guide (Appendix Table 1, available online).
The recommended screening for colorectal cancer in adults aged 50–75 years includes stool based (annual fecal occult blood test [FOBT] and annual fecal immunochemical test [FIT]) and direct visualization screening tests (colonoscopy every 10 years, computed tomography colonography every 5 years, or flexible sigmoidoscopy every 5 years).
The analysis excluded fecal immunochemical test or computed tomography colonography because the study sample did not include any claims for these tests. Because only 0.3% of participants had a flexible sigmoidoscopy during the 4-year period, the analysis combined it with colonoscopy. For breast cancer, the recommended screening is a biennial mammogram for women aged between 50 and 75 years. For cervical cancer, the recommended screening is a Papanicolaou smear without human papillomavirus testing every 3 years for women aged <30 years or a Pap with human papillomavirus testing every 5 years for women aged 30–65 years.
The main covariate of interest was adverse SDH measured at the time of enrollment through a face-to-face interview with a research assistant. The WHO model of SDH, which includes both structural determinants of health inequities and intermediary determinants of health, guided the SDH assessment.
The structural determinants measured were race, education, and employment status; the intermediary determinants included material circumstances (e.g., residence type, housing instability, food insecurity, financial strain), health behaviors (e.g., smoking, illicit drug, and alcohol use), and psychosocial factors (e.g., loneliness, marital status, living with children, history of being in jail/prison) (Appendix Figure 1, available online, shows the baseline SDH assessment).
Because individual SDH factors are highly correlated with one another and evaluating them separately in a regression model may lead to important associations being missed, the study employed latent class analysis (LCA) to categorize participants into 4 social risk groups on the basis of a similar response profile to the SDH assessment variables.
All SDH factors were dichotomized to make them easier to interpret the class solution. LCA models with 2–6 class solutions were run owing to the need for a relatively small number of latent classes for ease of interpretation. LCA assigns individuals to classes on the basis of their probability of being in classes according to the pattern of scores they have on the indicator variables, in this study, the SDH factors.
The LCA identified 4 distinct social risk groups within the cohort according to fit, classification, diagnostics, and ease of interpretation. The lowest social risk group had the highest employment rate and reported the fewest social disadvantages (social risk Group 1). Group 2 participants were also more employed but more likely to report trouble paying their bills. Group 3 consisted mostly of unemployed participants but not reporting financial strain, whereas Group 4, the highest social risk group, had the highest unemployment rate and reported the most social hardships in terms of housing, food insecurity, financial strain, and health behaviors.
The analysis controlled for risk factors when examining the relationship between social risk group measured at the individual level and receipt of each cancer screening test, including socioeconomic disadvantage assessed at the neighborhood level. All participants with a valid address were assigned a census block group and then linked to the 2019 Area Deprivation Index (ADI)—a weighted, composite score based on 17 census block-level indicators of poverty; educational attainment; housing; and employment.
The ADI ranges from 1 to 100. The higher the score, the worse the area deprivation. This study grouped participants into 4 categories on the basis of the ADI quartile distribution in the parent cohort.
Other factors included disease burden (measured according to the Johns Hopkins Adjusted Clinical Groups system [Version 12.0]),
regular medical providers, and Medicaid coverage duration during the 4-year study period, in addition to age and sex. The Adjusted Clinical Groups system uses ICD-10 diagnosis and pharmacy codes from administrative billing data (the Medicaid claims for a 2-year period before study enrollment in this study) to quantify disease burden on the basis of clinical factors, such as the likelihood or persistence of a condition, the severity of the condition, diagnostic certainty, etiology, and the types of healthcare services required.
An indicator variable of whether the participant had a regular doctor was included on the basis of a question in the baseline SDH assessment. The Medicaid eligibility claims file was used to determine each participant's Medicaid coverage status during the 4-year study period.
Statistical Analysis
First, the relationship between the receipt of at least 1 colonoscopy and/or sigmoidoscopy, FOBT, mammogram, or Papanicolaou smear and adverse SDH (i.e., social risk group), age, sex, duration of Medicaid coverage, disease burden, having a regular medical provider, and ADI quartile was assessed using a chi-square test of homogeneity. Second, the correlation between social risk group and the other risk factors was estimated. Third, the receipt of each cancer screening test was modeled separately as a function of social risk group, ADI quartile, disease burden, age, sex, duration of Medicaid coverage, and having a regular medical provider using log-binomial regression. Because social risk group had a meaningfully different association with the receipt of colonoscopy/sigmoidoscopy versus FOBT, each was modeled separately.
Because there was a strong relationship between social risk group and having a regular medical provider, models were rerun without the regular medical provider variable to estimate the relationship between social risk group and receipt of the cancer screening tests less conservatively. All analyses were completed using SAS 9.4 and R, Version 4.0.1.
RESULTS
During the 4-year study period, the receipt of a colonoscopy/sigmoidoscopy or FOBT was 42% among the 2,131 participants eligible for colorectal cancer screening. More participants received a colonoscopy/sigmoidoscopy (26%) than FOBT (13%), and few received both (4%). Among the 271 participants who only received an FOBT, 5 received an annual FOBT during the 4-year period.
Among the female participants, 66% of the 1,156 eligible participants received at least 1 mammogram during the study period, and 39% received at least 2 mammograms. Slightly more than half (58%) of the 5,068 women eligible for cervical cancer screening received at least 1 Papanicolaou smear.
Younger women were more likely to receive a Papanicolaou smear than older women, and men were less likely to receive a colonoscopy/sigmoidoscopy than women (Table 1). Participants who reported having a regular medical provider were more likely to receive a screening test than those who did not, except for FOBT. Those in the lowest social risk group (fewest disadvantages) were more likely to receive a colonoscopy/sigmoidoscopy or Papanicolaou smear than those in the highest social risk group. There was no significant association between the ADI quartile and receipt of the cancer screening tests.
Table 1Percentage Distribution of Receipt of Preventive Services by Different Risk Factors
Table 2 shows the relationship between social risk group and the other covariates for participants eligible for a colorectal screening test (Appendix Table 2, available online, shows the results for breast and cervical cancer subgroups). Participants in social risk Group 1 were significantly more likely to report having a medical provider (88%) than those in social risk Group 4 (74%). The higher the social risk group, the more severe the disease burden. There was significant variation within each social risk group by ADI quartile and vice versa. The patterns observed in Table 2 for participants eligible for a colorectal screening test were qualitatively the same for the other 2 cancer screening subgroups (Appendix Table 2, available online) apart from age. For those eligible for a cervical cancer screening test, participants in social risk Group 1 were younger than those in social risk Group 4.
Table 2Percentage Distribution of Social Risk Group by Different Risk Factors for Colorectal Screening Group (N=2,131)
The likelihood of receiving a colonoscopy/sigmoidoscopy was 30% lower for participants in the highest social risk group (most disadvantaged) than for the lowest group (adjusted RR [aRR]=0.70; 95% CI=0.54, 0.92) after adjusting for the other covariates (Table 3). In contrast to colonoscopy/sigmoidoscopy, participants in the highest social risk group were more likely to receive an FOBT than those in the lowest social risk group (aRR=1.52, 95% CI=1.09, 2.12). For mammograms and Pap smears, the pattern for social risk group was similar to colonoscopy/sigmoidoscopy. When the models excluded regular medical providers, participants in social risk Group 4 were less likely to receive a Pap smear (aRR=0.89, 95% CI=0.80, 0.99).
Table 3Adjusted RR (95% CI) of Receiving Cancer Screening Test During 4-Year Study Period
Log-binomial model adjusted for age, sex, morbidity burden, having a regular medical provider, the length of Medicaid coverage, Area Deprivation Index quartile, and social risk group.
Log-binomial model adjusted for age, sex, morbidity burden, the length of Medicaid coverage, Area Deprivation Index quartile, and social risk group. FOBT, fecal occult blood test.
Statistical significance is between social risk group and receipt of cancer screening test.
a Reference group is in parentheses.
b Log-binomial model adjusted for age, sex, morbidity burden, having a regular medical provider, the length of Medicaid coverage, Area Deprivation Index quartile, and social risk group.
c Log-binomial model adjusted for age, sex, morbidity burden, the length of Medicaid coverage, Area Deprivation Index quartile, and social risk group.FOBT, fecal occult blood test.
Neighborhood socioeconomic disadvantage as measured by the ADI was not associated with the receipt of cancer screening except for cervical cancer (data not shown). Female participants who lived in the second and third ADI quartiles were less likely to receive a Pap smear than women living in the least disadvantaged neighborhood quartile (aRR=0.90, 95% CI=0.84, 0.97 and aRR=0.94, 95% CI=0.88, 0.99 respectively).
DISCUSSION
This study evaluated the influence of a comprehensive set of adverse SDH measured at the individual level on the receipt of colorectal, breast, and cancer screening tests in an adult sample of Medicaid enrollees. Participants with worse SDH were less likely to receive the recommended cancer screening tests than those with the fewest social risks.
The proportion of participants who completed cancer screening tests in the sample was low but higher than in previous research using Medicaid claims for mammograms
Findings show that access to comprehensive health insurance coverage is not enough to eliminate disparities in the receipt of cancer screening tests among individuals of low income. Social risk group significantly influenced both types of colorectal cancer tests and was borderline significant for breast and cervical cancer screening.
Results suggest that a wide array of adverse SDH typically measured (i.e., poverty, lower education, and race/ethnicity) negatively affect the receipt of cancer screening tests. For example, a few studies have found that food insecurity,
are associated with a lower proportion of individuals completing a cancer screening test within the recommended period. Although this study did not evaluate the impact of each SDH factor separately, the 4 social risk groups represent individuals who vary meaningfully in terms of structural determinants of health inequities (e.g., educational level, employment status) and intermediary determinants (e.g., smoking, food insecurity, housing instability, financial strain).
This study did not find that SDH measured at the neighborhood level were associated with completion of cancer screening. Previous research reported inconsistent results of area-level SDH on cancer screening tests after controlling for individual-level SDH measures.
Association of neighborhood measures of social determinants of health with breast, cervical, and colorectal cancer screening rates in the U.S. Midwest.
reported that the odds of completing cancer screening tests were significantly lower among individuals living in the most deprived census block quintile than in the least deprived. However, they did not control for individual-level SDH factors except for age, sex, and race/ethnicity.
Association of neighborhood measures of social determinants of health with breast, cervical, and colorectal cancer screening rates in the U.S. Midwest.
found that once they controlled for individual-level household income, education, and race/ethnicity, area-level measures of poverty and race were not significantly associated with cervical cancer screening. This study's results imply that SDH factors measured at the individual level are the more important determinants of completion of cancer screening tests.
This is the first study to report that the influence of SDH on colorectal cancer screening completion varied by type of test. Participants with the most social disadvantages were more likely to do an FOBT, whereas participants with the least adversities were more likely to complete a colonoscopy. Unlike colonoscopy, FOBT is less invasive and more convenient because it does not require people to complete laxative preparations, take the day off work, undergo sedation, and have another adult drive them home. At least 1 managed care company contracting with the DC Medicaid program has implemented a targeted outreach program accompanied by mail-in FOBT kits,
However, it should be emphasized that very few participants completed the FOBT test annually. If the criteria had been annual FOBT, the relationship between FOBT and social risk group could not have been examined.
Limitations
This study has limitations. First, the 4-year study period is short, particularly for colorectal cancer screening. Second, not all participants were covered by Medicaid for the entire period, which may have resulted in underestimating adherence. This study may also have overestimated cancer screening test completion if some procedures were conducted for diagnostic rather than screening purposes. Third, claims do not include information on the extent to which low cancer screenings resulted from the absence of specialist referrals. Fourth, the study may have failed to exclude (a likely small number of) participants who had a disqualifying medical procedure before the 2-year prestudy enrollment period. Fifth, the SDH information was not collected annually, which may have resulted in some misclassification because circumstances can change over the 4-year period. Furthermore, this study evaluated the influence of an aggregated set of SDH rather than specific determinants. `Sixth, the study sample was identified at the time of a healthcare encounter, consisting primarily of Black enrollees who were very sick, so generalizability is limited. Finally, data are before coronavirus disease 2019 (COVID-19), precluding an assessment of COVID-19 on cancer screening test completion.
CONCLUSIONS
Among a sample of adults covered by the same public insurance program, social and economic disadvantages were associated with the receipt of cancer screening tests, signifying additional barriers to accessing recommended preventive care. To reduce cancer-related disparities, state Medicaid agencies need to systematically assess SDH among their members and use the results to seek solutions in collaboration with their enrollees, the healthcare system, and other service sectors. Medicaid must provide more infrastructure, resources, and support for more targeted action informed by these assessments to achieve health equity.
The authors wish to acknowledge Lydia Abma, who provided research assistance to this project while she was enrolled in the MPH in Health Policy program in the Department of Health Policy and Management at The George Washington University Milken Institute School of Public Health.
This study took advantage of data collected as part of a prospective cohort study, known as the DC Medicaid Cohort Study GW IRB#081728.
This analysis was made possible by the National Institute on Minority Health and Health Disparities (Grant Number R01MD011607).
Cancer stat facts: female breast cancer. NIH, National Cancer Institute, Surveillance, Epidemiology, and End Results Program. https://seer.cancer.gov/statfacts/html/breast.html. Accessed August 22, 2022.
Higher rates of preventive health care with commercial insurance compared with Medicaid: findings from the Arkansas Health Care Independence “Private Option” Program.
Association of neighborhood measures of social determinants of health with breast, cervical, and colorectal cancer screening rates in the U.S. Midwest.
42 U.S. Code § 300gg–13 - coverage of preventive health services. Ithaca, NY: Legal Information Institute. https://www.law.cornell.edu/uscode/text/42/300gg-13. Published March 23, 2010. Accessed August 9, 2022.
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