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Co-payment Policies and Breast and Cervical Cancer Screening in Medicaid
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Co-payment Policies and Breast and Cervical Cancer Screening in Medicaid

Lindsay M. Sabik, PhD; Anushree M. Vichare, PhD; Bassam Dahman, PhD; and Cathy J. Bradley, PhD
Co-payments for preventive services can discourage breast and cervical cancer screening among Medicaid enrollees, particularly breast cancer screening, which is more costly and time-consuming.

This paper considers how state co-payment policies affect breast and cervical cancer screening among low-income nondisabled women enrolled in FFS Medicaid. For both mammograms and Pap tests, women were less likely to receive screening when their state required co-payments for these services. We also compared women across states and years with different co-payment structures to understand whether there was a difference in screening among those required to pay co-payments that apply to all visits, those required to pay co-payments for most outpatient visits but for whom co-payments are waived for preventive services, and those without co-payments. For both types of screening, the group that had co-payments for some visits but had them waived for preventive care had the highest rates of screening. Counterintuitively, women with co-payments for preventive services are somewhat more likely to receive Pap tests compared with those who face no co-payments for any services. This difference in findings between Pap tests and mammograms may arise from differences in these screening procedures’ complexity and time costs; this warrants further investigation in future research.

Our results are strongest for mammography, with a bigger difference in screening rates observed for mammograms compared with Pap tests between those with co-payments for preventive services versus with those without co-payments for preventive care. Mammograms are likely to require a separate visit that may entail an additional co-payment, whereas a Pap test could be completed during a visit to an OB/GYN or other primary care physician. Therefore, co-payment policies appear to restrict services that require separate visits and additional costs for the patient.

Our findings suggest that Medicaid policies should consider the impact of co-payments on utilization of potentially high-value services such as screening. Although concerns have been raised regarding overscreening in older and higher-income populations,36,37 screening rates among the nonelderly Medicaid population are far below population-wide target levels.38 Thus, the influence of Medicaid policies, including cost-sharing requirements, on utilization of high-value services needs careful consideration before implementation. These policies could result in future higher utilization and costs.


Notably, annual screening rates in Medicaid claims data are lower than survey estimates for the general population, low-income population, or Medicaid-enrolled women. This might reflect a combination of low screening rates among Medicaid enrollees, inability to measure screenings not paid for by Medicaid, and overestimates of screening in survey data. Our study does not capture screenings completed outside the Medicaid program. We estimate all models for 2 samples: those continuously enrolled for all 12 months of a calendar year and those with at least 1 month of enrollment within the year. The first is a consistently enrolled Medicaid sample, whereas the second includes those who may have dropped out of Medicaid for a period of time and thus may have had a screening test outside of Medicaid reimbursement, but may also be more representative of a population known to churn in and out of Medicaid enrollment. Further, this study examines changes in annual screening for breast and cervical cancer over time in the context of changes in cost-sharing requirements; we do not capture whether the women in the sample receive guideline-recommended screening, and although our study uses multiple years of data, we capture just 3 nonadjacent calendar years, limiting the observation period. Therefore, we cannot assess longitudinal screening behavior outside these time frames. Other study limitations include the fact that we cannot control for all state-year differences in policy and health systems factors that may influence whether women receive recommended screenings. Further, the number of states that require co-payments for most services but waive them for preventive care is small. Finally, the data used are from the pre-ACA period, and the characteristics of nonelderly adult enrollees may have changed under Medicaid expansions.


Our results offer insight for policy, practice, and future research. First, state Medicaid programs that do not require co-payments for preventive services have higher rates of screening among nonelderly, nondisabled women. Second, rates of annual screening among women enrolled in Medicaid are low. Third, we find suggestive evidence that the full range of cost-sharing policies (including for other types of services) may affect utilization of preventive care in the Medicaid population. The use of longitudinal data could improve our understanding of cost-sharing policies and allow us to assess how these policies facilitate or create barriers to preventive services in low-income insured populations over time.


The authors would like to thank Yangyang Deng, MS, for programming support and Stephanie Hochhalter, MPH, MSW, for research assistance.

Author Affiliations: Department of Health Policy and Management, University of Pittsburgh (LMS), Pittsburgh, PA; Department of Health Policy and Management, George Washington University (AMV), Washington, DC; Department of Health Behavior and Policy, Virginia Commonwealth University (BD), Richmond, VA; University of Colorado Cancer Center (CJB), Aurora, CO; Department of Health Systems, Management, and Policy, Colorado School of Public Health (CJB), Aurora, CO.

Source of Funding: This work was supported by funding from the National Institutes of Health (R01CA178980, cofunded by the National Cancer Institute and the Office of Behavioral and Social Sciences Research).

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (LMS, BD, CJB); acquisition of data (LMS); analysis and interpretation of data (LMS, AMV, BD, CJB); drafting of the manuscript (LMS, AMV, CJB); critical revision of the manuscript for important intellectual content (LMS, AMV, BD); statistical analysis (LMS, BD); obtaining funding (LMS); and administrative, technical, or logistic support (LMS).

Address Correspondence to: Lindsay M. Sabik, PhD, Department of Health Policy and Management, University of Pittsburgh, 130 De Soto St, A613, Pittsburgh, PA 15261. Email:

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