The effect of the Affordable Care Act on patient out-of-pocket cost and use of preventive cancer screenings in Massachusetts

Abstract

In an effort to increase use of preventive health care, The Patient Protection and Affordable Care Act (ACA) eliminated cost-sharing for preventive cancer screening services for the privately insured. The impact on patient spending and use of these screenings is still poorly understood. We used an interrupted time series analysis with the Massachusetts All-Payer Claims Database (2009–2012) to assess changes in trends in costs and use of breast, cervical and colorectal cancer screenings after the ACA policy. We find that the ACA was associated with a 0.024 (95% CI: −0.031, −0.017, p < 0.001) and 0.424 (95% CI: −0.481, −0.368, p < 0.001) percentage point decrease in the likelihood of a copayment each week for preventive breast and cervical cancer screenings respectively. The likelihood of copayment for colon cancer screening declined throughout the study period, with the rate of decline slowing following the ACA (trend in percent of screenings with copayment −0.130 before vs −0.071 after ACA, p = 0.014). Overall, we find only weak evidence that the ACA policy increased screenings. We find no significant effect on utilization for cervical cancer or colon cancer screening. For breast cancer screening, we find a small immediate increase in the utilization rate in the month after the policy change, with no change in trend after the ACA policy. Policy makers may need to consider other complementary policy options to increase screening rates.

Access to Care as a Barrier to Mammography for Black Women

“…Among the privately insured, the ACA eliminated the cost sharing for preventive cancer services. In Massachusetts, this ACA policy resulted in an immediate increase in breast cancer screenings per 1,000 encounters (Steenland et al., 2019). In the states that elected to participate in Medicaid expansion, women with Medicaid are similarly afforded breast cancer screening services at no cost (Kaiser Family Foundation, 2019).…”

Interrupted Time-Series for the Evaluation of Affordable Care Act Impact on Stereotactic Radiosurgery for the Treatment of Brain Metastases

“…Whereas ACA was associated with decline in weekly copayment for preventive breast and cervical cancer screenings, the likelihood of copayment for colon cancer screening declined throughout the study period, with decline rate slowing after ACA (20). There was, however, only weak evidence for ACA impact on increased rates of cancer screening (20). Lu and colleagues performed ITS analyses using JPS Center for Cancer Care institutional registry data on 4808 urban, underserved, adult patients diagnosed with a rst primary invasive solid tumor between 2008 and 2015, to examine the impact of ACA implementation on stage at diagnosis in Texas, a Medicaid nonexpansion state (15).…”

“…Previously conducted ITS analyses focused on the potential role of ACA on utilization of healthcare services have examined speci c ACA provisions, including Medicaid expansion (9,10,12,13,16,21), elimination of cost-sharing expenses for preventive services (8,17,18,20) and overall ACA implementation (8,11,15,17,19,20). Given the complexity of this issue, few studies speci cally focused on cancer diagnosis, prevention and treatment prepost ACA and these studies yielded inconsistent ndings, with evidence for improved healthcare access among underserved populations (8,10,11,14,15,(17)(18)(19)(20)(21). For instance, Carlos and colleagues used patient-level analytic les on 1763959 commercially insured women aged 40 to 74 years from the 2004-2014 Clinformatics Data Mart to evaluate changes in mammography cost sharing and utilization pre-post ACA, while comparing these outcomes by age group, and found limited impact of ACA on cost-sharing and utilization due to simultaneous revision of USPSTF guidelines (11).…”

“…We used time point-speci c prevalence rates to perform comparative ITS analyses by examining differences in levels and slopes over time between periods prepost ACA implementation, before and after stratifying by patient or hospital characteristics (20). ITS analysis is a robust quasi-experimental method for evaluating the impact of population-level interventions through estimation of change in outcome around the time of an intervention while avoiding individual-level unmeasured confounding and controlling for pre-existing time trends prior to that intervention (10,15,20). All ITS models included indicator variables for time point (year and quarter coded as 51,…,144), post-intervention status and an interaction term between time point and post-intervention status (18).…”

“…All ITS models included indicator variables for time point (year and quarter coded as 51,…,144), post-intervention status and an interaction term between time point and post-intervention status (18). We applied post-estimation to calculate change in intercept and slope for pre-post ACA prevalence rates (11,21), and calculated Newey-West standard errors to adjust for autocorrelation (10,15,20). We also constructed Poisson regression models whereby each patient and hospital characteristic, post-ACA status and their interactions were examined as predictors of prevalent radiation therapy and SRS.…”