Abstract
Background:
Timely cervical cancer screenings are critical for middle-aged to older Latinas. However, little is currently known about screening in this population. Latinas tend to receive disproportionate care in community health centers (CHC).
Methods:
A retrospective analysis of electronic health record data from a national network of US CHCs included Latinas and non-Hispanic Whites (NHW) aged >45 with known birth country and at least one in-person primary care visit between 2014 and 2022, across 527 community-based clinics in 15 states. We used generalized estimating equations logistic regression to examine covariate-adjusted receipt of cytology, overall and by country of origin.
Results:
Among 34,135 patients, Mexican Latinas had the highest unadjusted prevalence of receiving cytology or cotesting at 56%, whereas NHWs had the lowest prevalence at 37%. We found that Latina groups, except for US-born Latinas, individually had higher odds of receiving cytology or cotesting compared with NHWs. Latina groups born in Mexico [OR (95% confidence interval, CI), 1.44 (1.09–1.90)], Honduras [OR (95% CI), 1.39 (1.06–1.82)], El Salvador [OR (95% CI), 1.38 (1.09–1.73)], and Nicaragua [OR (95% CI), 1.36 (1.01–1.83)] had higher odds than NHWs.
Conclusions:
CHCs have important strengths in reaching diverse patient populations, with higher rates of cervical cancer screening in middle-aged to older Latinas than NHWs.
Impact:
This study adds novel information about screening rates among a heterogeneous sample outside of their reproductive years and in a large, multistate sample of CHCs. We add to a growing body of literature about the distinctive environment of CHCs.
Introduction
Cervical cancer is highly preventable with clear screening guidelines. However, adherence to cervical cancer screening guidelines has historically been documented as less common among Latinas than non-Hispanic Whites (NHW) in the wider and general healthcare system, hindering early detection and survival (1). Recent studies show that at the national level, NHWs may be doing better than Latinas (2). Latinas receive a disproportionate amount of primary care in community health centers (CHC), which are a vital component for cancer screening and prevention (3–5). CHCs deliver affordable health services to many, and since the early 2000s, they have grown because of federal investments in CHC capacity and the expansion of Medicaid eligibility (5, 6). We know much less about cervical cancer rates in a CHC setting. Relative to the general population, individuals visiting CHCs have disproportionately low income (less than 200% of the federal poverty level), racial/ethnic minorities, and uninsured or Medicaid-insured (6–8). A key element of CHCs is that they provide culturally competent, comprehensive primary care that is accessible to all patients regardless of their ability to pay. The CHCs must develop a system of care that is responsible for the unique needs of the population they serve (9). CHCs serve as a usual source of care for large shares of immigrant adults who are Latina/o (41%), report undocumented status (42%), have limited English proficiency (39%), and have lower income (37%; refs. 10, 11). Mexican immigrants, compared with the general population, have disproportionately low income, have fewer years of formal education, and are more likely to be uninsured (12–15). Only 12% of CHCs were ranked high in cervical cancer screening performance (in 2019, across 933 CHCs, 52% of all eligible patients were screened; ref. 3). At the same time, studies have demonstrated that CHCs may have better screening outcomes among Latinos (3, 16–18). Some targeted interventions to increase cervical cancer screening among the general population in CHCs have shown success, including education-based (provider or patient knowledge; refs. 19, 20) or utilizing a patient reminder system (20, 21). CHCs are crucial to better understanding and improving cervical cancer screening among Latinas, but currently, we do not know what the patterns are among screening practices, especially among middle-aged to older Latinas specifically.
Human papillomavirus (HPV) vaccination is not a preventive option for middle-aged to older Latinas (>45 years); they are often outside their reproductive years but remain at risk for cervical cancer (22, 23). For this population, cytology is critical to identify and treat precancerous lesions. When the data for this study were collected, according to the United States Preventive Services Task Force/American College of Obstetricians and Gynecologists guidelines, people with a cervix were recommended to start receiving cytology at age 21 and continue every 3 to 5 years until age 65. However, since then, these guidelines have been updated to specify cytology for ages 21 to 29 every 3 years and HPV testing for ages 30 to 65 every 5 years, with a self-sampling option (24, 25). Considerable gaps persist between Latinas and NHWs in receiving these screens (30, 31). Research suggests that 67.2% of Latinas self-report a recent receipt of cytology, compared with NHW women who are screened at a rate of 80% (30). Latinas are also more likely than NHWs to be diagnosed with advanced cervical cancer, which leads to poorer outcomes (26–28). Research has shown that there are higher rates of cervical cancer diagnosis among Latinas than among NHWs at older ages (29). Thus, timely cervical cancer screenings are critical for middle-aged to older Latinas, but little is currently known about screening rates for this population (37, 38).
The research that does exist tends to focus only on particular groups of Latinas and/or collapses all Latinas into a very heterogeneous population (30). However, there are important differences among various groups of Latinas that are crucial to consider. Foreign-born Latinas, for example, are less likely to receive cytology and have a higher incidence of cervical cancer compared with US-born women (31–34). Foreign-born Latinas are more likely than US-born Latinas to have a late-stage cervical cancer diagnosis (35, 36). As of 2021, there were >23 million immigrant women in the United States, with Mexican-born women accounting for more than a fifth of this population (15). As the country’s single largest share of immigrant women, extensive efforts are needed to ensure that Mexican-born women are being screened appropriately while also considering other subgroups of Latinas, such as Cubans, Puerto Ricans, and/or Colombians. More research is needed to examine the unique differences in cervical cancer screening among a growing and aging group of Latinas in the United States. There is little work describing these differences across community healthcare settings.
In this study, we leverage a multistate network of CHCs that allows for assessing the utilization of cervical cancer screening. Our aim was to determine the prevalence of one cytology or cotesting among middle-aged to older foreign-born Latinas, US-born Latinas, and NHWs with a cervix who are seen in CHCs. We hypothesize that Latinas, both foreign-born and >45 years of age, were less likely to have received guideline-based cervical cancer screening than US-born Latinas or NHWs.
Materials and Methods
Data source
This study used electronic health record (EHR) data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Research Network, a member of PCORnet. ADVANCE integrates outpatient health record data and community-level data. ADVANCE is a multicenter collaborative led by OCHIN Inc. (not an acronym), a nonprofit organization that provides a single instance of OCHIN Epic EHR. OCHIN Inc. is not a place of care but houses a database pulling data from CHCs, part of the national network. Data for this study were extracted from EHR fields for patients across 527 community-based primary care clinics from January 1, 2014, to September 14, 2022. These clinics were in 15 states (CA, FL, GA, IN, MA, MN, MT, NC, NM, OH, OR, TX, UT, WA, and WI). This study was approved by the Oregon Health & Science University Institutional Review Board (study #00023320) and conducted in accordance with recognized ethical guidelines. The data used in this study were collected during routine primary care visits, and consent from patients to use data in research was obtained from clinics when care was initiated.
Study population
The study population included Latina and NHW women older than 45 years of age with a known birth country and at least one in-person primary care visit between January 1, 2014, and September 14, 2022 (n = 37,113). Race, ethnicity, and birthplace data were self-reported in the course of routine care delivery. Patients were excluded if they had a full or partial hysterectomy (n = 2,341), had a prior diagnosis of cervical cancer (n = 76), or were pregnant at any point in the study period (n = 561). Routine cytology practices and guidelines differ during pregnancy (37, 38).
Dependent variables
The binary dependent variable was measured if patients were ever given any cytology or HPV test during their study period. The dependent variable was determined using lab and procedure codes from the EHR.
Independent variable
The independent variable indicated ethnicity and country of birth for the patients. This included (i) NHW female, (ii) US-born Latina, and 11 other groups, including Latinas born in (iii) Colombia, (iv) Cuba, (v) the Dominican Republic, (vi) Ecuador, (vii) Guatemala, (viii) Honduras, (ix) Mexico, (x) Nicaragua, (xi) Peru, and (xii) other (including Uruguay, Paraguay, Panama, Guyana, Costa Rica, Chile, Brazil, Bolivia, and Belize). The “other” category includes patients from the countries listed above, combined due to small sample size (<100 per group).
Covariates
The following patient-level characteristics were extracted from the EHR and included in regression models as potential confounders (see Table 1): age at first encounter (continuous), household income (as a percentage of federal poverty level; always ≤138%, above and below, always >138%, never documented), insurance status over the study period (always, sometimes, never), diagnosis of diabetes (yes/no), diagnosis of obesity (yes/no), a high blood pressure measurement at any time during the study period (yes/no), ever received a mammogram (yes/no), Charlson comorbidity index score (continuous), social deprivation index (SDI) score (continuous),if the patient’s primary provider speaks Spanish (yes/no), and yearly number of visits (continuous; ref. 39). The primary provider was determined based on which provider the patient saw most often. The clinical conditions were included to indicate overall health status and to identify other care received to reflect utilization patterns, given that those with additional conditions may be going to the provider more often. We attempted to add region as a covariate, but due to one region with a small sample size, the model would not converge.
Table 1.
Patient characteristics by ethnicity/country of birth.
| Characteristic | NHW | USB Latina | Colombia | Cuba | Dominican Republic | Ecuador | El Salvador |
|---|---|---|---|---|---|---|---|
| Number of patients (%) | 9,536 (27.94) | 4,621 (13.54) | 193 (0.57) | 188 (0.55) | 2,660 (7.79) | 163 (0.48) | 3,833 (11.23) |
| Age at first encounter [mean (SD)] | 55.66 (8.37) | 54.25 (8.03) | 55.54 (8.54) | 52.35 (7.47) | 55.97 (9.55) | 54.44 (8.45) | 56.05 (8.39) |
| Years in study period [mean (SD)] | 3 (3.15) | 2.25 (2.29) | 2.33 (2.64) | 2.66 (3.07) | 3.44 (2.52) | 1.77 (2.45) | 2.85 (2.83) |
| Number of visits [mean (SD)] | 19.48 (30.35) | 15.03 (18.35) | 12.72 (14.12) | 18.41 (22.85) | 20.64 (20.20) | 11 (18.20) | 18.16 (18.66) |
| Provider speaks Spanish (%) | | | | | | | |
| Yes | 1,129 (11.8) | 1,046 (22.6) | 39 (20.2) | 54 (28.7) | 1,382 (52) | 25 (15.3) | 1,072 (28) |
| Income as percentage of the federal poverty level (%) | | | | | | | |
| Above and below | 1,242 (13) | 232 (5) | 19 (9.8) | 41 (21.8) | 283 (10.6) | 20 (12.3) | 365 (9.5) |
| Always ≤138% | 4,296 (45.1) | 1,694 (36.7) | 140 (72.5) | 117 (62.2) | 2,014 (75.7) | 110 (67.5) | 3,166 (82.6) |
| Always >138% | 1,807 (18.9) | 295 (6.4) | 18 (9.3) | 11 (5.9) | 109 (4.1) | 19 (11.7) | 183 (4.8) |
| Never documented | 2,191 (23) | 2,400 (51.9) | 16 (8.3) | 19 (10.1) | 254 (9.5) | 14 (8.6) | 119 (3.1) |
| Insurance (%) | | | | | | | |
| Always | 4,892 (51.3) | 3,210 (69.5) | 98 (50.8) | 121 (64.4) | 1,004 (37.7) | 59 (36.2) | 1,898 (49.5) |
| Never | 878 (9.2) | 255 (5.5) | 25 (13) | <11 (5.3) | 164 (6.2) | 34 (20.9) | 287 (7.5) |
| Sometimes | 3,766 (39.5) | 1,156 (25) | 70 (36.3) | >56 (30.3) | 1,492 (56.1) | 70 (42.9) | 1,648 (43) |
| Charlson comorbidity index score [mean (SD)] | 2.55 (2.88) | 1.96 (2.35) | 0.72 (1.26) | 1.39 (1.83) | 1.72 (1.97) | 0.57 (0.90) | 1.07 (1.38) |
| Ever obese (%) | | | | | | | |
| Yes | 3,127 (32.8) | 2,264 (49) | 52 (26.9) | 57 (30.3) | 988 (37.1) | 44 (27) | 1,977 (51.6) |
| Ever high blood pressure (%) | | | | | | | |
| Yes | 7,797 (81.8) | 3,955 (85.6) | 143 (74.1) | 161 (85.6) | 2,424 (91.1) | 102 (62.6) | 3,128 (81.6) |
| Ever mammogram (%) | | | | | | | |
| Yes | 3,099 (32.5) | 1,031 (22.3) | 61 (31.6) | 28 (14.9) | 1,909 (71.8) | 36 (22.1) | 706 (18.4) |
| Diabetes diagnosis (%) | | | | | | | |
| Yes | 1,585 (16.6) | 1,427 (30.9) | 29 (15) | 37 (19.7) | 797 (30) | 24 (14.7) | 1,253 (32.7) |
| SDI score [mean (SDI)] | 47.97 (31.53) | 78 (21.13) | 73.80 (25.65) | 76.05 (23.19) | 84.76 (18.92) | 71.21 (28.28) | 88.14 (16.12) |
| Either cytology or HPV test (%) | | | | | | | |
| Yes | 3,494 (36.6) | 2,124 (46) | 90 (46.6) | 101 (53.7) | 1,226 (46.1) | 72 (44.2) | 1,899 (49.5) |
| | | Guatemala | Honduras | Mexico | Nicaragua | Peru | Other |
|---|---|---|---|---|---|---|---|
| Number of patients (%) | | 2,493 (7.3) | 740 (2.17) | 9,167 (26.86) | 172 (0.5) | 172 (0.5) | 197 (0.58) |
| Age at first encounter [mean (SD)] | | 54.08 (8.22) | 53.40 (7.92) | 52.89 (7.93) | 55.33 (8.08) | 56.49 (8.82) | 57.17 (9.54) |
| Years in study period [mean (SD)] | | 3.24 (2.78) | 2.41 (2.70) | 2.59 (2.84) | 2.94 (2.78) | 2.87 (2.82) | 2.39 (2.73) |
| Number of visits [mean (SD)] | | 19.10 (18.66) | 14.54 (18.12) | 14.95 (17.64) | 17.13 (17.68) | 17.44 (22.68) | 12.73 (16.45) |
| Provider speaks Spanish (%) | | | | | | | |
| Yes | | 749 (30) | 159 (21.5) | 1,838 (20.1) | 37 (21.5) | 28 (16.3) | 46 (23.4) |
| Federal poverty level (%) | | | | | | | |
| Above and below | | 251 (10.1) | 76 (10.3) | 1,328 (14.5) | 16 (9.3) | 23 (13.4) | 20 (10.2) |
| Always ≤ 138% | | 2,113 (84.8) | 563 (76.1) | 6,251 (68.2) | 133 (77.3) | 119 (69.2) | 137 (69.5) |
| Always > 138% | | 68 (2.7) | 62 (8.4) | 723 (7.9) | >12 (8.7) | 16 (9.3) | 17 (8.6) |
| Never documented | | 61 (2.4) | 39 (5.3) | 865 (9.4) | <11 (4.7) | 14 (8.1) | 23 (11.7) |
| Insurance (%) | | | | | | | |
| Always | | 1,155 (46.3) | 293 (39.6) | 4,309 (47) | 93 (54.1) | 81 (47.1) | 107 (54.3) |
| Never | | 138 (5.5) | 115 (15.5) | 1,245 (13.6) | 14 (8.1) | 17 (9.9) | 22 (11.2) |
| Sometimes | | 1,200 (48.1) | 332 (44.9) | 3,613 (39.4) | 65 (37.8) | 74 (43) | 68 (34.5) |
| Charlson comorbidity index score [mean (SD)] | | 1.04 (1.35) | 0.98 (1.35) | 1.01 (1.43) | 1.05 (1.53) | 0.84 (1.18) | 1.20 (1.56) |
| Ever obese (%) | | | | | | | |
| Yes | | 1,202 (48.2) | 395 (53.4) | 4,554 (49.7) | 86 (50) | 53 (30.8) | 55 (27.9) |
| Ever high blood pressure (%) | | | | | | | |
| Yes | | 2,039 (81.8) | 623 (84.2) | 7,277 (79.4) | 136 (79.1) | 130 (75.6) | 154 (78.2) |
| Ever mammogram (%) | | | | | | | |
| Yes | | 917 (36.8) | 131 (17.7) | 1,272 (13.9) | 37 (21.5) | 49 (28.5) | 70 (35.5) |
| Diabetes diagnosis (%) | | | | | | | |
| Yes | | 829 (33.3) | 209 (28.2) | 3,039 (33.2) | 39 (22.7) | 29 (16.9) | 35 (17.8) |
| SDI score [mean (SD)] | | 88.93 (15.83) | 86.03 (18.50) | 84.52 (18.55) | 89.07 (15.51) | 74.87 (24.52) | 68.66 (25.18) |
| Either cytology or HPV test (%) | | | | | | | |
| Yes | | 1,354 (54.3) | 397 (53.6) | 5,170 (56.4) | 81 (47.1) | 93 (54.1) | 82 (41.6) |
NOTE: Other includes Uruguay, Paraguay, Panama, Guyana, Costa Rica, Chile, Brazil, Bolivia, and Belize.
Abbreviations: SD, standard deviation; USB, US-born.
Statistical analysis
Patient characteristics were first described by ethnicity/nativity group. To examine the receipt of at least one cytology or HPV test during the study period, we used generalized estimating equations (GEE) logistic regression with indicator variables representing ethnicity and country of birth categories (reference set to NHW) and all covariates listed above. The model used a robust sandwich variance estimator to account for patient clustering within states. Covariate-adjusted odds ratios and their corresponding 95% confidence intervals (CI) derived from the GEE logistic model were reported. Analyses were conducted in R version 4.1.2 and SAS version 14.3 Statistical significance was set at a P value<0.05.
Results
The total study population consisted of 34,135 women (Table 1). The three largest groups were NHW (28%), Mexican (27%), and US-born Latinas (14%). Our population included Latina patients born in a broad number of countries including Colombia (n = 198), Cuba (n = 188), the Dominican Republic (n = 2,660), Ecuador (n = 163), El Salvador (n = 3,833), Guatemala (n = 2,493), Honduras (n = 740), Mexico (n = 9,167), Nicaragua (n = 172), Peru (n = 172), and finally other countries (n = 197), including Uruguay, Paraguay, Panama, Guyana, Costa Rica, Chile, Brazil, Bolivia, and Belize. The average number of visits ranged from 11 to 20. Most Cuban- and US-born Latina patients had insurance continuously during the study period, whereas the other groups had continuous insurance about half the time or less. A much smaller percentage never had any insurance during the study period. The mean SDI score was higher for all Latina groups compared with NHW patients (Table 1).
NHW women had the lowest unadjusted prevalence of receiving either cytology or cotesting at 37%, with Mexican Latinas having the highest unadjusted prevalence of 56%.
The adjusted model (Table 2) showed that compared with NHW women, Latina groups from Colombia, Cuba, the Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, and Peru had higher odds of receiving either cytology or cotesting compared with NHWs. There was not enough evidence to indicate a difference between NHW and US-born Latinas and NHW and Latinas from other countries. Specifically, with respect to Mexican-born Latinas, the model indicated 1.44 times the odds of screening with cytology or HPV testing compared with NHW patients [OR (95% CI), 1.44 (1.09–1.90)].
Table 2.
Covariate-adjusted ORs of receiving either cytology or cotesting during the study period.
| Ethnicity/country of birth group | Covariate-adjusted ORs (95% CIs) |
|---|---|
| NHW | Reference |
| US-born Latina | 1.28 (0.80–2.07) |
| Colombia | 1.42 (1.07–1.87) |
| Cuba | 1.34 (1.03–1.73) |
| Dominican Republic | 1.70 (1.41–2.06) |
| Ecuador | 1.80 (1.09–2.96) |
| El Salvador | 1.38 (1.09–1.73) |
| Guatemala | 1.44 (1.12–1.85) |
| Honduras | 1.39 (1.06–1.82) |
| Mexico | 1.44 (1.09–1.90) |
| Nicaragua | 1.36 (1.01–1.83) |
| Peru | 2.07 (1.37–3.14) |
| Othera | 2.13 (0.92–4.92) |
NOTE: Logistic GEEs model clustered by state and adjusted for age at first encounter, household income (percentage of federal poverty level), insurance over the study period, diagnoses of diabetes, diagnosis of obesity, a high blood pressure measurement any time during the study period, mammogram, provider speaks Spanish, Charlson comorbidity index score, SDI score, and yearly number of visits. Bold text indicates statistical significance.
Includes Uruguay, Paraguay, Panama, Guyana, Costa Rica, Chile, Brazil, Bolivia, and Belize, which had fewer than 100 patients per country.
Discussion
This study adds novel information about screening rates among a heterogeneous sample of Latinas outside of their reproductive years and in a large, multistate sample. CHCs provide access to primary and preventive care for Latinos, more so for foreign-born and uninsured populations. Contrary to our hypothesis, we found foreign-born middle-aged to older Latinas from all countries had higher rates of cytology or cotesting compared with NHWs. All rates remain well below national cervical cancer targets for both Latinas and NHWs.
First, there remains work to be done in the context of CHC to improve cytology rates for both Latinas and NHWs. Recent data show that NHWs screening (ages 22–64) have dropped down to rates in the 60s compared with the 80s and are now slightly lower than Hispanics (65%; ref. 2). In our sample of middle-aged to older women, in the context of CHCs, nearly a third of NHWs had cytology compared with half among Latinas (33). These findings underscore the opportunity to continue to improve overall cervical cancer screening rates among CHCs across the nation that serve the most vulnerable and marginalized patient populations of all races/ethnicities.
Specifically, our findings of higher odds of screening among older foreign-born Latinas may reflect the unique role of CHCs, which provide critical healthcare safety nets by offering essential preventive services to often historically underserved populations, including uninsured and/or undocumented individuals. The majority of the Latinas in our study live in states that provide care to low-income people regardless of their immigration status. Recent research in women aged 37 to 54 has found that insurance status mediated more than half of the inequities in the diagnosis of advanced-stage cervical cancer among all other racial and ethnic groups compared with Whites (28). With the Affordable Care Act and Medicaid expansion, insurance coverage has increased access to preventive care (40–42). Other research has also found that among a network of CHCs, previously uninsured patients (ages 50–64) who are Spanish-preferring Latinas in Medicaid eligibility amendment states had significantly greater increases in up-to-date breast and cervical cancer screenings compared with nonamendment states (43). State-funded coverage expansions affect insurance status that may play a critical role in increasing cancer screening rates and potentially reducing the cancer burden among Latina CHC patients. Future research will need to explore why NHW patients in CHCs experience less cervical cancer screening and have not seemed to experience the access benefits that Latinas have in this context.
Additionally, there is a growing body of literature about the distinctive environment of CHCs and their unique approach to the use of “promotoras” and language or culturally tailored services, particularly in California, Arizona, Texas, and New Mexico (44–46). It is also plausible that the higher cervical cancer screening observed reflects such language and culturally tailored interventions within CHCs. In analyses of other longitudinal cancer and noncancer preventive services among CHCs, Latinas (including foreign-born and older Latinas) have utilized care more robustly than NHWs (3, 47). Middle-aged to older foreign-born Latinas may be more inclined to follow through and/or want to receive or complete cancer prevention services given their historical lack of access to healthcare. It is well-documented that foreign-born immigrants, migrants, and/or noncitizens are generally less likely to receive a wide range of preventive services, including cervical cancer screenings (48–50). A rich ethnographic study of CHCs would provide valuable insights into the contextual and environmental factors that drive increases in utilization. It would be beneficial to explore what factors in these contexts and environments lead to higher and/or lower utilization of cervical cancer screening services among all CHC patients.
Furthermore, in the CHC context, there is also some evidence that NHW patients tend to be unhealthier compared with the general population. CHCs provide care to millions of low-income White patients (51). All patients in this setting tend to be twice as likely as the general public to report being in only fair or poor health. Rates of chronic conditions are much higher among CHC patients with higher morbidity rates than non-CHC patients (51). A recent survey found that nearly two thirds of patients seen at CHCs live in poverty and another one quarter live between 100% and 200% of the federal poverty level (52). Additionally, patients seeking care in safety-net clinics are accruing chronic diseases at higher rates in middle age (53, 54). Multimorbid conditions among older adults are high in CHC settings. Our findings may also be unique because of our chosen sample of middle-aged and older people with a cervix. This study adds to the limited literature indicating that effort is needed to improve cervical cancer screening among middle-aged to older NHWs in CHCs. People who are older and reside in the United States may tend to have more visits and healthcare encounters, and when/if offered screening services, they might be more inclined to agree to have those services, creating this trend among middle-aged to older foreign-born Latina patient populations. For next steps, as self-collection HPV testing becomes implemented in clinics and offered as an alternative option, it will be imperative to assess how all populations’ screening rates will be affected in the CHC setting (24). CHCs have served and continue to serve an important safety-net healthcare delivery role for NHWs in the United States (55). Another possible explanation for the observed differences in the odds of cervical cancer screening may be related to healthcare providers and staff who work at CHCs and how their decision-making and recommendations can be influenced by patients’ racial/ethnic and/or socioeconomic status that has been documented to start as early as medical school training (56, 57). There may be bias in the self-selection of providers who decide to practice in CHC settings, as they are often drawn to serving populations that are characterized as underserved, marginalized, and/or disadvantaged. People who work in CHCs also often live in the communities being served by the CHC (8). There is some evidence from studies on other types of cancer screening and treatment that such provider behaviors can significantly reduce disparities, which may also apply in this context, particularly with follow-up results (58). Patient-centered communication and team-based care can better support cancer screening for breast, colorectal, and cervical cancer (58–60). Additionally, providers may review and prioritize preventive care with a greater sense of urgency given the population they are working with. Studies have documented that foreign-born populations tend to receive less cancer screening, and in order to counteract such trends, some providers may offer more screening and preventive care efforts when working with foreign-born patients (48, 61). It is possible that our findings may, therefore, reflect the unique characteristics and behaviors of providers in CHCs. Future research would benefit from analyzing provider-level data to better understand these dynamics, in addition to structural support that may facilitate the prioritization of preventative services (e.g., EHR reminders, quality metrics, and federal mandates).
Given that we did not have data from non-OCHIN network clinics, we were unable to see screenings that occurred outside these CHCs. We also were unable to report the timeliness of screening; it is possible for some to have received more than one screening elsewhere and/or for others to have only gotten one screening in a 10-year period. It is also possible that cervical cancer screening received outside of the CHC or prior to clinic enrollment might lead to under-reporting. Secondary EHR data could not only affect selection bias, but information bias and ascertainment bias are limited to what is only in the EHR (62). Future research should conduct a more nuanced analysis to determine not only if screening is occurring but also how often and if it is in accordance with the current guidelines that range between 3 and 5 years depending on the case, as well as examine the introduction of self-collection options. Similar research has been done with mammography (63). Additionally, although we adjusted for neighborhood factors by including the SDI score for patient location in the models, future research should consider how other specific area-level factors may be affecting and/or explaining higher levels of cancer screening among middle-aged to older foreign-born Latinas. Finally, future research should account for unique or different programs as well as incentives in the clinics. Another possible reason is that CHCs may have certain incentives to report, so they can see their rates from year to year. With recent alternative payment models, future research would need to take this into account (64). It is also possible that some clinics may implement public health programs, whereas others do not. ScreenWise, for example, was specifically intended to reduce barriers and increase cancer screening among low-income, uninsured, and medically underserved populations. Due to a lack of an appropriate sample size for all regions, we were unable to adjust by region in the model. Although our data were unable to map out clinic-level factors, we did cluster by clinics in analyses; future research is needed to better understand the drivers of rates in CHCs. Finally, our study may not be generalizable to screening practices outside of the CHC setting.
Overall, we found that among patients receiving care at CHCs, foreign-born middle-aged to older Latinas had more cytology or cotesting compared with NHWs. The unique context setting at CHCs may help explain these results. However, the prevalence of screening was less than the guideline-recommended national cervical cancer screening rates. Work needs to be done to ensure equitable and timely access to cervical cancer screening among NHWs and the Latina CHC patient population.
Acknowledgments
The research reported in this work was powered by PCORnet. PCORnet has been developed with funding from the Patient-Centered Outcomes Research Institute (PCORI) and conducted with the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Research Network (CRN). ADVANCE is a CRN in PCORnet led by OCHIN in partnership with Health Choice Network, Fenway Health, the University of Washington, and Oregon Health & Science University. ADVANCE’s participation in PCORnet is funded through the PCORI Award RI-OCHIN-01-MC. The funding is received from the NIH NCI (grant number: R01CA258464 to J.D. Heintzman) and the NIH NCI (grant number: K01CA292141 to C.E. Vasquez Guzman).
Data Availability
The data in this study were generated as part of routine healthcare and are used secondarily in this article. Data are only available to those who partner with OCHIN Inc. for research. Anyone not partnering with OCHIN Inc. will not have access to the data. To protect patient information, there are strict guidelines for all partners with OCHIN Inc. to adhere to, thereby limiting data availability.
Authors’ Disclosures
B.B. Green reports grants from the NCI and other support from the American Cancer Society during the conduct of the study. C. Morris reports grants from the NIH during the conduct of the study, as well as grants from the NIH outside the submitted work. J.D. Heintzman reports grants from the NIH, Silver Family Foundation, and Patient-Centered Outcomes Research Institute during the conduct of the study. No disclosures were reported by the other authors.
Authors’ Contributions
C.E. Vasquez Guzman: Conceptualization, funding acquisition, writing–original draft, writing–review and editing. T. Hodes: Formal analysis, methodology, writing–original draft. J.A. Lucas: Supervision, methodology, writing–review and editing. V. Leslie: Writing–review and editing. C. Maxwell: Writing–review and editing. M. Ramiro-Jenkins: Writing–review and editing. L. Garside: Writing–review and editing. M.P. Banegas: Writing–review and editing. B.B. Green: Writing–review and editing. W.P. Bensken: Writing–review and editing. S.M. Rushton: Writing–review and editing. M. Marino: Data curation, supervision, methodology, writing–review and editing. D.M. Harper: Writing–review and editing. C. Morris: Writing–review and editing. J.D. Heintzman: Conceptualization, funding acquisition, writing–original draft.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data in this study were generated as part of routine healthcare and are used secondarily in this article. Data are only available to those who partner with OCHIN Inc. for research. Anyone not partnering with OCHIN Inc. will not have access to the data. To protect patient information, there are strict guidelines for all partners with OCHIN Inc. to adhere to, thereby limiting data availability.