Having a Routine Source of Healthcare and Its Impact on Colorectal Cancer Screening Recommendation Compliance

Abstract

Introduction:

Colorectal cancer (CRC) screening rates remain low in the US. Previous research has indicated that primary care providers are trusted sources for healthcare recommendations, including cancer screening.

Methods:

CRC module questions within the 2022 BRFSS were reviewed and multivariable logistic regression was used to explore the relationship between healthcare engagement and likelihood of CRC screening.

Results:

Results showed that those with the highest level of healthcare seeking behavior were almost 10 times as likely to receive appropriate CRC screening compared to the lowest engagement group. In a multivariable logistic regression, this relationship remained with higher healthcare engagement having an odds ratio of 5.951 compared to low engagement.

Discussion:

This study indicates seeing a regular healthcare provider in the past year is associated with increased CRC screening. These results confirmed he role that marriage/partnership plays in cancer screening in the US which should be an intervention area considered. This study re-emphasized that there remain racial/ethnic disparities in CRC screening with almost all groups receiving less CRC screening compared to White, non-Hispanic respondents.

Conclusion:

This research re-emphasizes the critical role that primary care providers play in the landscape of patient care and specifically identifies these settings as key for intervening to increase uptake of CRC screening recommendations.

Keywords

community health health outcomes health promotion prevention primary care

Introduction

Colorectal cancer (CRC) is the third most common cancer worldwide, and the fourth most common cancer which affects both sexes in the US.^1,2 CRC rates are linked to both modifiable (e.g., weight, type 2 diabetes, smoking, diet, alcohol use) and non-modifiable (age, race/ethnicity, sex at birth, gall bladder removal, colorectal polyps, inflammatory bowel disease, family CRC history, some genetic syndromes, etc.) risk factors. Various screening methods and implementation models have shown success in reducing CRC mortality rates with a reduction in mortality up to 73% because of early screening.³ CRC screening recommendations as of 2021 in the US, are that individuals aged 45 to 74 receive appropriate CRC screening to include a stool-based tests such as high-sensitivity guaiac fecal occult blood test (gFOBT) or fecal immunochemical test (FIT) annually; a stool DNA test every 1 to 3 years; CT colonography every 5 years; flexible sigmoidoscopy every 5 years; flexible sigmoidoscopy every 10 years and a FIT every year; or colonoscopy screening every 10 years.⁴ Historical data on CRC screening has shown that screening rates have increased from less than 25% in the late 1980s to a higher end estimate of 60% by 2006.^5-8 Researchers linked this increased screening rate prior to 2006 entirely to Medicare reimbursement changes in 2001 that began to cover colonoscopy.⁹ As of 2021, 71.8% of recommended individuals receive CRC screening, which is below the Healthy People 2030 goal of 74.4% and falls short of the universal screening recommendation.¹⁰

Previous studies show that CRC screening increased when primary care providers (PCPs) were involved in recruitment and when individuals have a usual source of care.^9,11,12 The US studies exploring the relationship between usual source of care and CRC screening compliance have been based on smaller point in time surveys or national surveys like the National Health Interview Survey which do not often have the power to create state-based estimates nor track trends over time.^13,14 Additionally, many studies that established this relationship originally were published prior to the Affordable Care Act (ACA) and Medicaid expansion in many states. This study aims to address these potential limitations by examining broadly representative data in the US which can be used to create state-based estimates and is routinely collected and available post-ACA implementation from the Behavioral Risk Factors Surveillance System (BRFSS) survey.

When PCPs at 4 major healthcare systems in the US were surveyed, researchers found that for patients that were CRC screening eligible (50-74 at the time of the study), the majority of providers rated colonoscopy as very effective (82.9%) followed by FIT (59.6%) with 26.3% rating colonoscopy more effective than FIT. Also, for this age group, 77.9% of providers recommended colonoscopy every 10 years and 92.4% recommended FIT annually, which is in line with CRC cancer screening recommendations from USPSTF at the time.¹⁵ However, in randomized controlled trials the actual implementation of these screening recommendations is much lower, with only 25% of PCPs recommending screening during usual checkups.¹⁶ So while PCPs understand the value of screening and the need to make recommendations, the rate at which they make those recommendations during typical healthcare visits is quite low. Barriers to recommending screening reported by PCPs include lack of time, patient reluctance, and colonoscopy scheduling challenges.¹⁷

A meta-analysis of healthcare seeking behavior in high income countries completed in 2021 examined both the likelihood of visiting a PCP and the frequency of those visits by Socio-Economic Status (SES) and observed that SES inequality does not affect likelihood of visiting a PCP.¹⁸ Lower SES was associated with higher frequency but a lower rate of accessing specialists.¹⁸ Specific to CRC screening in primary care practices in the US, we see that lower SES is associated with a higher colorectal cancer screening rate in both rural and urban clinics.¹⁹

Health insurance has been shown to influence the likelihood of CRC screening in the US with historical studies finding that participants who reported having health insurance were more than twice as likely to report CRC screening and reporting that lack of insurance and cost of care were specific barriers.^20,21 When Medical Expenditure Panel Survey data were analyzed to determine the predictive power of health insurance coverage on CRC screening over time, no appreciable change in CRC screening rates post-ACA implementation was observed.²² So while health insurance coverage is identified by patients a facilitator for CRC screening, it is not the only determining factor.

A previous cross-sectional study of uptake of FIT colorectal cancer screening found that people who are married were 41% more likely to get screened compared to those who were not (widowed, divorced, or single).²³ This difference was even higher when their partner also participated in screening. A similar review of the BRFSS data in 2015 confirmed this relationship and found that the increased participation extended to those in a partnership as well.²⁴ Family structure and social support clearly influence CRC screening uptake, therefore marital status was included as a covariate in this study.

Previous research outlined in this section shows that uptake of CRC screening is influenced by testing access and cost, access to a provider with ability to effectively discuss screening, healthcare system engagement, and social support. This study aims to further explore the relationship between a person’s healthcare provider relationship and their engagement in the healthcare system on their likelihood to comply with CRC screening recommendations by utilizing the 2022 national BRFSS data. Our hypothesis is that participation in recommended screenings for CRC is increased by having a PCP and further, seeing that provider within the last year.

Methods

Overview of BRFSS

The BRFSS is a US-based national telephone annual survey of non-institutionalized adult populations funded by the Centers for Disease Control and Prevention (CDC). CDC defines core and optional modules for each survey year and has included a module on CRC screening in even years. Additional details on the execution of BRFSS, sampling methodologies, individual year questionnaires, and module creation have been published previously.²⁵ For this study, BRFSS data were obtained from the CDC’s public access website for 2022, the most recent year that the CRC Screening Module was included as a core module. The CRC Screening Module questions are only asked if the respondent is over 45 years of age, aligning with current CDC and US Preventive Service Task Force recommendations for screening which also begin at 45 and are standard through age 75. There is a calculated variable included in the public access data which uses multiple variables across the survey to determine if an individual respondent aged 45 to 75 has fully met the USPSTF CRC screening recommendations which is the outcome of interest for this study. The responses are categorized into: Has at least one of the recommended tests within the time interval, Did not have any of the recommended CRC tests within the time interval, Have never had any of the recommended CRC tests. The second and third calculated response options were considered non-compliant with screening recommendations and were collapsed into 1 category for this analysis.

In order to assess healthcare seeking behaviors and their impact on adequacy of CRC screening, a complex variable was created from 2 existing BRFSS questions: (1) “Do you have one person (or a group of doctors) that you think of as your personal health care provider?” and (2) “About how long has it been since you last visited a doctor for a routine checkup?” The resulting composite variable had 4 categories representing a combination of “Have a personal care provider” (yes/no) and “Visited doctor in the last year” (yes/no).

Outcome Variable

The primary outcome variable was compliance with U.S. Preventive Services Task Force (USPSTF) colorectal cancer (CRC) screening recommendations. The BRFSS dataset contains a derived measure based on responses to questions regarding stool-based tests, colonoscopy, sigmoidoscopy, and CT colonography. Respondents are classified as having (1) completed at least 1 recommended CRC screening test within the appropriate interval, (2) not completed any recommended test within the interval, or (3) never completed any recommended test. For this analysis, categories 2 and 3 were combined into a single “non-compliant” group, while category 1 was coded as “compliant.”

Independent Variables

Independent variables were selected based on prior literature linking demographic, socioeconomic, health status, and healthcare access factors to CRC screening behavior. Demographic variables included age, sex at birth (male or female), and race/ethnicity.^1,2 Socioeconomic variables included education level, annual household annual income, employment status, and marital status.^18,19,23,24 Health-related variables included self-reported general health, health insurance coverage, having a personal healthcare provider, and time since last routine checkup (<12 months vs ≥12 months).^20,21 To capture both continuity and recency of care, a composite healthcare engagement variable was created by combining the measures for having a personal healthcare provider and having a routine checkup in the past 12 months, resulting in 4 categories: YY (has a personal healthcare provider and had a checkup in the past 12 months), NY (no provider but had a checkup in the past 12 months), YN (has a provider but no checkup in the past 12 months), and NN (no provider and no checkup in the past 12 months, reference category).

Statistical Analysis

Weighted frequencies and means were calculated to describe the study population. Bivariate associations between independent variables and CRC screening compliance were assessed using weighted chi-square tests for categorical variables and t-tests for continuous variables, with significance set at P < .05. Multicollinearity was evaluated using variance inflation factors (VIF). Variables with P < .05 in bivariate analysis were entered into a multivariable logistic regression model using backward stepwise selection, retaining race/ethnicity and sex regardless of statistical significance to control for confounders. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported. All analyses accounted for the complex survey design and sampling weights provided by CDC. Statistical analyses were performed using SAS version 9.4.

Results

Table 1 presents the weighted and unweighted frequencies for all demographic, socioeconomic, health status, and healthcare access characteristics. The final weighted sample represented 122,572,627 U.S. adults aged 45 to 75 years, with a mean age of 59.6 years. The majority were White, non-Hispanic (65.13%), female (51.92%), and married or partnered (64.42%). Most had at least some college education (63.46%), annual household incomes of $35,000 or more (71.43%), and were currently employed for pay (52.38%). In terms of health indicators, 78.72% reported good or better health, and 94.58% had health insurance coverage. Most respondents (89.59%) had a personal healthcare provider, and 82.49% had a routine checkup in the past 12 months. When combining these measures, 78.16% had both a provider and a recent checkup (YY), 4.36% had no provider but a recent checkup (NY), 11.46% had a provider but no recent checkup (YN), and 6.02% had neither (NN). Overall, 66.13% of respondents were compliant with USPSTF colorectal cancer screening recommendations, 6.72% were overdue for screening, and 27.10% had never been screened.

Table 1.

Weighted and Unweighted Frequencies for Selected Population Characteristics as Collected on the 2022 BRFSS.

Population characteristic	Unweighted		Weighted
	N	%/Mean	N	%/Mean
	251 226	—	122 572 627	—
Demographics
Age (45-75)	—	61 years		59.59 years
Race and ethnicity
White only, non-Hispanic	19 7408	78.58	79 832 939	65.13
Black only, non-Hispanic	20 740	8.26	14 785 853	12.06
American Indian/Alaskan Native only, non-Hispanic	4082	1.62	1 553 231	1.27
Asian only, Non-Hispanic	5113	2.04	5 932 189	4.84
Native Hawaiian or other pacific islander only, non-Hispanic	1237	0.49	494 403	0.40
Multiracial, non-Hispanic	4438	1.77	3 003 093	2.45
Hispanic	18 208	7.25	16 970 919	13.85
Birth sex
Male	116 272	46.28	58 929 920	48.08
Female	134 954	53.72	63 642 707	51.92
Marital status
Married or partnered	153 576	61.91	77 901 450	64.42
Never married or not currently married	94 502	38.09	43 028 871	35.58
Education
Did not graduate high school	13 782	5.52	13 995 884	11.51
Graduated high school	57 751	23.14	30 446 084	25.03
Attended college or technical school	69 049	27.66	37 410 578	30.76
Graduated from college or technical school	109 041	43.68	3 977 1941	32.70
Annual Income
<$35,000	54 494	27.33	27 123 998	28.57
$35,000-$75,000	58 390	29.29	25 371 492	26.72
≥$75,000	86 498	43.38	42 457 795	44.71
Employment Status
Currently employed for pay	120 901	49.33	62 205 127	52.38
Job seeking or otherwise employed for no pay	17 072	6.97	10 283 038	8.66
Non-employed	107 110	43.70	46 263 733	38.96
Health indicators
Health status
Good or better	201 014	80.23	96 174 498	78.72
Fair or poor	49 521	19.77	25 998 549	21.28
Health insurance
Yes	233 479	96.16	111 411 372	94.58
No	9335	3.84	6 384 608	5.42
Have a personal healthcare provider
Yes	228 252	91.10	109 452 509	89.59
No	22,295	8.90	12 718 074	10.41
Routine check up in the last 12 months
Yes	209 123	83.40	100 883 636	82.49
No	41 613	16.60	21 413 894	17.51
Have seen their personal healthcare provider for a routine checkup in the last 12 months (YY)	199 617	79.78	95 343 567	78.16
Have seen someone other than a personal healthcare provider for a routine checkup in the last 12 months (NY)	9105	3.64	5 322 053	4.36
Have not had a checkup in the last 12 months but do have a personal healthcare provider (YN)	28 361	11.34	13 980 796	11.46
Do not have a personal healthcare provider and have not received a checkup in the last 12 months (NN)	13 117	5.24	7 342 983	6.02
Colorectal cancer (CRC) screening
People aged 45-75 who have fully met the UPSTF CRC recommendations
Had at least one of the recommended CRC tests within the time interval	155 370	69.96	70 104 974	66.13
Did not have any of the recommended CRC tests within the recommended time interval	15 848	7.14	7 118 812	6.72
Have never had any of the recommended CRC tests	50 873	22.91	28 708 433	27.10

Bivariate Analysis

In weighted bivariate analysis (Table 2), CRC screening compliance was significantly associated (P < .05) with age, race/ethnicity, sex, marital status, education, annual household income, employment status, self-reported health status, health insurance coverage, having a personal healthcare provider, time since last routine checkup, and the composite healthcare engagement variable. The strongest unadjusted association was observed for the composite healthcare engagement variable: respondents with both a provider and a recent checkup (YY) had nearly 10 times the odds of screening compliance compared to those with neither (NN) (OR = 9.615, 95% CI: 8.665-10.669, P < .0001).

Table 2.

Weighted Odds Ratios for Appropriate Colorectal Cancer Screening for Selected Population Characteristics, BRFSS 2022.

Population characteristic	Odds ratio	Confidence interval			P-value
Demographics
Age (45-75)	1.098	1.095	—	1.101	<.0001
Race and Ethnicity (comparison group White, non-Hispanic)
Black only, non-Hispanic	0.938	0.879	—	1.002	<.0001
AI/AN only, non-Hispanic	0.566	0.473	—	0.676	.0464
Asian only, non-Hispanic	0.526	0.457	—	0.605	.0004
Native Hawaiian or Pacific Islander, non-Hispanic	0.574	0.419	—	0.786	.2789
Multiracial, non-Hispanic	0.754	0.652	—	0.872	.0748
Hispanic	0.485	0.453	—	0.52	<.0001
Birth Sex (Male vs Female)	0.875	0.841	—	0.911	<.0001
Marital Status (Not married and never married vs married or partnered)	0.739	0.709	—	0.77	<.0001
Education (comparison group did not graduate high school)
Graduated high school	1.762	1.62	—	1.916	.8582
Attended college or technical school	2.171	1.999	—	2.358	<.0001
Graduated college or technical school	2.485	2.294	—	2.693	<.0001
Annual Income (comparison group <$35 000)
$35 000-<$75 000	1.448	1.367	—	1.534	<.0001
≥$75 000	1.528	1.45	—	1.61	<.0001
Employment status (comparison group employed for wages)
Job seeking or otherwise employed for no pay	0.739	0.685	—	0.797	<.0001
Non-employed	2.274	2.176	—	2.377	<.0001
Health indicators
Health status (good or better vs fair or poor health)	1.1	1.049	—	1.156	<.0001
Health Insurance (have some form of insurance vs no insurance)	6.266	5.594	—	7.018	<.0001
Have a personal healthcare provider (Y v N)	4.58	4.256	—	4.928	<.0001
Routine check up in the last 12 months (Y v N)	3.959	3.76	—	4.17	<.0001
Healthcare seeking combined (comparison group is neither (NN))
Have seen their personal healthcare provider for a routine checkup in the last 12 months (YY)	9.615	8.665	—	10.669	<.0001
Have seen someone other than a personal healthcare provider for a routine checkup in the last 12 months (NY)	3.301	2.942	—	3.704	.7303
Have not had a checkup in the last 12 months but do have a personal healthcare provider (YN)	3.597	3.11	—	4.161	.0251

Multivariable Logistic Regression

Variables retained in the final adjusted model included age, race/ethnicity, sex, marital status, education, annual income, and the composite healthcare engagement variable (Table 3). After adjustment, the highest level of healthcare engagement (YY) remained the strongest predictor of screening compliance (adjusted OR = 5.91, 95% CI: 5.12-6.821, P < .0001). Respondents with a provider but no recent checkup (YN) (adjusted OR = 3.489, 95% CI: 2.885-4.22, P < .0001) and those with no provider but a recent checkup (NY) (adjusted OR = 2.357, 95% CI: 2.016-2.756, P = .002) also had significantly higher odds of compliance compared to NN. Older age, higher educational attainment, higher income, being married or partnered, and female sex were each independently associated with higher odds of CRC screening compliance.

Table 3.

Adjusted Model of Weighted Odds Ratios for Appropriate Colorectal Cancer Screening for Selected Population Characteristics, BRFSS 2022.

Population characteristic	Odds ratio	Confidence interval			P-value
Demographics
Age (45-75)	1.101	1.098	—	1.105	<.0001
Race and ethnicity (comparison group White, non-Hispanic)
Black only, non-Hispanic	1.1	0.999	—	1.212	.0007
AI/AN only, non-Hispanic	1.308	1.163	—	1.471	<.0001
Asian only, non-Hispanic	0.842	0.658	—	1.078	.2396
Native Hawaiian or Pacific Islander, non-Hispanic	0.613	0.503	—	0.748	<.0001
Multiracial, non-Hispanic	0.912	0.594	—	1.401	.8051
Hispanic	1.068	0.883	—	1.293	.1723
Birth sex (male vs female)	0.947	0.9	—	0.996	.0356
Marital status (not married and never married vs married or partnered)	0.83	0.781	—	0.882	<.0001
Education (comparison group did not graduate high school)
Graduated high school	1.227	1.088	—	1.385	.0145
Attended college or technical school	1.441	1.277	—	1.626	<.0001
Graduated college or technical school	1.63	1.442	—	1.842	<.0001
Annual Income (comparison group <$35 000)
$35 000-<$75 000	1.239	1.149	—	1.336	.9805
≥$75 000	1.532	1.415	—	1.659	<.0001
Health indicators
Healthcare seeking combined (comparison group is neither (NN))
Have seen their personal healthcare provider for a routine checkup in the last 12 months (YY)	5.91	5.12	—	6.821	<.0001
Have seen someone other than a personal healthcare provider for a routine checkup in the last 12 months (NY)	2.357	2.016	—	2.756	.002
Have not had a checkup in the last 12 months but do have a personal healthcare provider (YN)	3.489	2.885	—	4.22	<.0001

Discussion

This study indicates that seeing a regular healthcare provider in the past year is associated with increased CRC screening likelihood. These confirm results seen in other countries as well as single state estimates previously published in the US. This analysis is more robust than previous analyses by virtue of the combination of having a regular provider and having seen that provider in the past 12 months. Combining these and adding nuance helped us show that higher levels of healthcare engagement can increase CRC screening participation 10-fold. These points emphasize the role that primary care and medical homes play in linking patients to appropriate cancer screening options as well as the trusted role these providers play in overall health recommendations for patients. To support further engagement of patients within their healthcare system, PCPs can consider adopting strategies highlighted in published recommendations such as developing community partnerships, building inclusive and multidisciplinary staff teams, integrating care that addresses social needs, and building strong referral networks with local partners.^26-28

The role that marriage/partnership plays in cancer screening in the US was consistent with previous studies.^23,24 As is the case with many health behaviors, being married/partnered is protective by increasing the likelihood of healthy activity engagement, including preventive healthcare.²⁹ This data reinforces the idea that social networks should be engaged by PCPs to ensure that patients follow through on screening recommendations or specialist referrals. This could include implementing couple-tailored print materials regarding CRC screening, education classes, or more informal discussions regarding partner screening habits and recommendations during individual visits.^30,31 For patients not married or partnered, engagement of further social supports such as parents or children may be a potential avenue of intervention that has not yet been well studied. There is likely an opportunity to broadly explore interventions shown to increase overall cancer screening rates through evidence-based linkage to care services.³²

Non-employed individuals were over 2 times as likely to receive CRC screening compared to those who were employed. Some possible explanations for this could be that those individuals may receive additional social services outside of Medicaid or are living within the household of someone with insurance. Additionally, this observation could be related to the time available to seek services for non-employed individuals who are retired. These hypotheses merit further investigation to better understand how employment status intersects with healthcare access and screening behavior, particularly in the context of public insurance eligibility.

This study has several limitations in that BRFSS is a self-reported telephone-based survey and may not fully represent the entire US population. Additionally, the CRC screening module is only asked to individuals that meet the current CRC screening recommended age group and therefore will not account for shifting trends in CRC incidence.³³ Additionally, this is a cross-sectional study and individuals are not followed over time. As such, it is not possible to ascribe causation to the observations in this study. Strengths of this study include the large sample size as well as the documented reliability of BRFSS questionnaires and specifically the CRC screening module.^34-36

Conclusions

This research re-emphasizes the critical role that PCPs and medical homes play in the landscape of patient care and specifically identifies these settings as key for intervening to increase uptake of CRC screening recommendations. Previous research showed that PCPs are trusted messengers of health information and recommendations.^9,11,12 There remain barriers within the primary care environment for linking a patient with recommended CRC screening which should be explored.^16,17 However, considering the predictive factors identified in this study within clinics or care environments is likely to yield greater uptake of CRC screening.

Footnotes

Acknowledgements

None.

ORCID iDs

Kate Goodin

Derrick Nyantakyi Owusu

Ethical Considerations

This research involved secondary data analysis of publicly accessible, de-identified survey data and therefore did not constitute human subjects research.

Consent to Participate

This research did not include collecting any information directly from participants; this research solely included secondary analysis of publicly accessible, de-identified surveys. Therefore, it was not possible to obtain informed consent from original survey participants. Information on privacy protections and informed consent for original data collection efforts for the Behavioral Risk Factors Surveillance System are published by the Centers for Disease Control and Prevention.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Publication fees were supported by the Public health Infrstructure Grant through the Centers for Disease Control and Prevention.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data is available publicly at

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