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  • KPT-185 br Previous studies demonstrated changing patterns o


    Previous studies demonstrated changing patterns of health in-surance coverage among patients seen in CHCs after the ACA insurance policies were implemented, including increased rates of Medicaid-paid (in expansion states) and privately-paid (in non-expansion states) visits and decreased uninsured visit rates compared to before the ACA in-surance policies were implemented (Angier et al., 2017a; Fedewa et al., 2015; Hong et al., 2017; Hoopes et al., 2016; Huguet et al., 2017). As CHCs have a high percentage of uninsured patients most likely to be impacted by ACA insurance policies, it KPT-185 is a good setting to understand the impact of the ACA insurance policies on cancer screening pre-valence. Several studies assessed the impact of some of the ACA pro-visions on national rates of cancer screenings with mixed results (Sabik and Adunlin, 2017). Some found no improvement in colorectal or breast cancer screening post-ACA (Han et al., 2015; Mehta et al., 2015; Simon et al., 2017), while others found that changes in reducing cost sharing or co-payments were positively associated with screening (Cooper et al., 2016; Jena et al., 2017; Richman et al., 2016; Sabatino et al., 2016). Several studies speculated that ACA Medicaid expansion would exacerbate disparities in cancer screening between expansion and non-expansion states because non-expansion states had lower screening rates pre-ACA than those that expanded (Choi et al., 2015; Sabik et al., 2015). Yet, to date no study focused specifically on how ACA Medicaid expansions impacted cancer screenings by comparing expansion and non-expansion states.
    Therefore, the objective to this study is to assess changes in the prevalence of cervical and colorectal cancer screening in a national network of CHCs pre- to post-ACA Medicaid expansion. We focus on cervical and colorectal cancer [limited to fecal occult blood test/fecal immunochemical test (FOBT/FIT)] screenings as they are proven ef-fective (U.S. Preventive Services Task Force, 2018) and available within the clinic setting (i.e., patients do not need to be referred to another healthcare organization to receive the screening). We compared rates in Medicaid expansion and non-expansion states, and evaluated hetero-geneity of the Medicaid health policy impact by health insurance type and race/ethnicity.
    2. Methods
    Electronic health record (EHR) data were obtained KPT-185 from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) clinical data research network (CDRN) of CHCs, one of the CDRNs participating in PCORnet (DeVoe et al., 2014). AD-VANCE data used for this study are from OCHIN and Health Choice Network (HCN). OCHIN is the largest network of CHCs utilizing a single  Preventive Medicine 124 (2019) 91–97
    instance of one EHR system. Similarly, HCN is a group of CHCs on a single EHR system. The data from OCHIN and HCN are centralized and standardized in the ADVANCE warehouse using the PCORnet common data model. The study CHCs represent approximately 14% of the CHC population across the 13 states included in the analysis; representa-tiveness varies by state, from a high of 83% in Oregon to a low of 4% in North Carolina. The characteristics of the patient population in the ADVANCE data are similar to that of CHCs across the US (National Association of Community Health Centers, 2018). We restricted our clinic study sample to states with CHCs in the ADVANCE network that were ‘live’ on their EHR system as of 1/1/2012, remained active throughout the study period, and provided adult primary care services; resulting in 203 participating CHCs. Data were collected on all non-pregnant patients (n = 624,601) aged 21–64 at any point in the study period, who were alive throughout the study period, and had at least one ambulatory visit between 2012 and 2015. There is different Med-icaid eligibility for pregnant women, which is unrelated to ACA ex-pansions, so they were excluded from this study. Patients included in the screening analyses had to be eligible for colorectal and/or cervical cancer screening during the study period (screening eligibility was as-sessed separately for the pre-ACA [2012−2013] and post-ACA [2014–2015] periods) (Angier et al., 2017b).
    Our primary independent variable was state Medicaid expansion status. For the purpose of this study, we defined expansion states in our sample as those that expanded Medicaid on 1/1/2014; non-expansion states were those who did not expand Medicaid through from 1/1/2014 to 12/31/2015. Expansion states in our sample included: California, Hawaii, Maryland, New Mexico, Ohio, Oregon, Rhode Island, Washington, and Wisconsin; non-expansion states were Florida, Kansas, Missouri, and North Carolina. Wisconsin was considered an expansion state because although they did not expand Medicaid to 138% FPL, they opened enrollment to adults up to 100% FPL on 1/1/2014, thus be-having more like an expansion state (Angier et al., 2017a; Huguet et al., 2017).