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Impact of Health Reform on Young Adult Prescription Medication Utilization
Amy Pakyz, PharmD, PhD, MS; Hui Wang, PhD; and Peter Cunningham, PhD
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Impact of Health Reform on Young Adult Prescription Medication Utilization

Amy Pakyz, PharmD, PhD, MS; Hui Wang, PhD; and Peter Cunningham, PhD
The dependent coverage provision was associated with an increase in total and private expenditures and a decrease in out-of-pocket medication expenditures paid, especially among higher-income groups.
Table 1 displays adjusted differences in outcomes between the groups (full regression results are available in eAppendix II). For total expenditures, by the DID estimate, there was a significant increase of 3.8 percentage points among young adults aged 19 to 25 years compared with those aged 26 to 34 years. There was also a significant increase in private expenditures (7.6 percentage points) among young adults compared with those aged 26 to 34 years. The provision was associated with significant decreases in OOP expenditures (4.4 percentage points) and in the share of total expenditures paid OOP (1.2 percentage points). No differences were found in regard to whether or not there was a time in the past year they were unable to get medications due to cost. 

With regard to the evaluation of postpolicy trends by year, the DID estimates showed that for total expenditures, significant increases were seen by those aged 19 to 25 years in years 2012 and 2013 only (17.4 and 3.4 percentage points, respectively, compared with those aged 26-34 years). Private expenditures increased in each postpolicy year by 14.0, 5.5, and 3.8 percentage points, respectively, for 2011, 2012, and 2013. For expenditures paid OOP, a significant decrease was seen only for 2013 (12.8 percentage points), whereas the share of total expenditures paid OOP significantly decreased in 2 years (3.1 and 2.5 percentage points, respectively, for 2012 and 2013). 

For most outcomes, there were differences across income categories (Table 1). For example, for total expenditures, there was a significant 11.3 percentage-point increase among young adults in the highest income group (≥300% of FPL), whereas significant decreases were noted among lower-income groups (13.2 and 13.0 percentage points for ≤100% and 101%-299% of FPL groups, respectively). Among the income levels, individual-year DID estimates were largely similar to the pooled-year estimates for expenditures in terms of direction (increase, decrease) and significance, but were not consistent in magnitude over time (Table 1). 

Overall, DID estimates were similar in direction and significance in sensitivity analyses, whereby the study sample was restricted to those who were privately insured (eAppendix III). There were some notable differences in the magnitude of some estimates. For example, total expenditures increased by 5.7 and fell by 23.4 percentage points for all groups and the middle income level for young adults aged 19 to 25 years, respectively, for the reduced sample. An increase of 3.8 and decrease of 13.0 percentage points, respectively, was found for the full sample. 

Proportions of prescriptions for major therapeutic classes out of all medications filled by the target and comparison groups are displayed in Table 2. In both groups, the most commonly used agents were anti-infective, CNS, hormone, respiratory, psychotherapeutic, and topical medications. These classes composed more than 80% of total prescriptions (88% and 87% of total, for the pre- and postperiods, respectively, for the target group, and 84% and 83%, respectively, for comparisons). For both groups, the proportion of use of some of the commonly used classes changed modestly, by –8.0% and +8.3% (for anti-infectives), +5.5% and –4.5% (for CNS agents), and +4.0% and 0% (for hormones), for pre-post periods and target and comparison groups, respectively. However, the proportion of respiratory and metabolic agents decreased by 16% and 8%, respectively, for the target group. Table 3 displays DID estimates for expenditures by class. There were significant increases in anti-infective expenditures, whereas there were decreases for hormone and psychotherapeutic expenditures among young dependents in the postperiod compared with the pre-implementation period. DID estimates for different classes by year were not always significant or consistent in direction of pooled estimates (Table 3). 


Findings of the dependent coverage provision’s impact on medication expenditures show that it was associated with increases in total and private insurance expenditures of 3.8 and 7.6 percentage points, respectively, and decreases in OOP and share of total expenditures OOP of 4.4 and 1.2 percentage points, respectively, among young adults aged 19 to 25 years versus a slightly older group. Increases in total and private expenditures and decreases in OOP were concentrated in groups with higher incomes. Opposite effects were observed in lower-income groups. The ACA’s effect by postpolicy year was, to a large degree, consistent in direction as to pooled estimates, but the effect was not found to be either increasing or decreasing consistently over time. Results were generally robust in terms of direction and significance when comparing DID estimates generated from a reduced study sample not inclusive of publicly insured persons, although some estimates were larger, such as those for total and OOP expenditures. 

Regarding the impact of the provision on prescription medication utilization, Chua et al15 found no difference between young adults aged 19 to 25 years and those aged 26 to 34 years in the proportion that had at least 1 medication fill within the previous year when evaluating the provision for 2011. Shane et al17 found no differences in medication fills when examining MEPS data through 2012. In the current study, there were no significant differences in total expenditures in 2011, but there were significant increases in 2012 (17.4 percentage points) and in 2013 (3.4 percentage points). The impact may be more evident by medication expenditures, as in the current study, compared with utilization measured by fills. Look et al16 evaluated total and medication expenditures by payment source. In unadjusted analyses, it was found that OOP medication expenditures significantly decreased from 2009 to 2011 among those in the age group affected by the provision, but there were no differences in private insurance expenditures. 

Previous work16 has shown that increases in medication insurance coverage (in 2011) were observed predominantly among young adult higher-income groups (14.5 percentage points) compared with nonsignificant increases and decreases in coverage among middle- and lower-income groups, respectively. The differential impact of the provision on expenditures by income in the current study is not unexpected, given that it primarily affected higher-income groups, with changes in coverage due to Medicaid expansion among lower-income groups occurring later in the ACA-implementation timeline (2014).23

We found that anti-infectives, CNS agents, and hormones were commonly used among young adults. Look et al16 noted that medication fills for asthma increased significantly in 2011 compared with 2009 among young adults affected by the ACA provision, and anti-infective medication fills increased for a control group, but no differences were seen for others. We found that expenditures for respiratory agents increased significantly (by 6.6 percentage points), whereas hormone expenditures increased by 1.7 percentage points (not significant) and psychotherapeutic expenditures significantly decreased (by 10.9 percentage points) in 2011. Overall decreases in hormone-related expenditures are likely due to the ACA provision mandating that private health insurance include oral contraceptives with no cost sharing.24 Further research is needed to determine what agents in particular, and for what indications, are associated with prescription coverage due to the dependent coverage provision. 

It is possible that there could be unintended consequences of increased coverage. In the case of anti-infectives, for example, it was estimated that approximately half of the time, they are prescribed inappropriately during ambulatory care visits, especially for acute respiratory infections.25 Given that MEPS data were found to be more accurate for medications used to treat chronic conditions compared with intermittently used medications, including anti-infectives,21 exploration of facets of anti-infective drug use in particular by young adults, including indications and agent selection, is warranted. Overall, medication types prescribed to young adults in both age groups in the current study differed from those that are prescribed to older adults, in that medications for hypertension, diabetes, and hyperlipidemia account for a large proportion of medications used among those aged 40 to 64 years.26 This can be explained by the lower prevalence of these conditions in younger adults.


There are limitations to this study. First, although MEPS medication data are self-reported, the data were validated and shown to have a high agreement rate with matched Medicare Part D claims data.21 The medication types that did not match as well were designed for short-term use, such as anti-infectives, which were among the more highly used medications among young adults in the current study. It is possible that the ACA had an even higher impact on medication utilization if anti-infective expenditures were underreported. Second, although the models were adjusted for socioeconomic and employment status factors, other economic conditions during the study period, such as the recession beginning in 2008, may have differentially affected the 2 groups in terms of medication use behaviors and coverage. 


The ACA dependent coverage provision was associated with an increase in total prescription expenditures, predominantly among those with higher incomes. Further, the young adult age group affected by the ACA had decreased prescription OOP medication expenditures, particularly in the middle-income group. In analyses of the policy’s impact through each postpolicy year across outcomes, there were not consistencies regarding level and direction of the ACA's impact. Further data are needed regarding the impact of the ACA provision on increased prescription medication access over time, including the specific types of agents being used more frequently and their impact on the health of young adults. 

Author Affiliations: Department of Pharmacotherapy and Outcomes Science, School of Pharmacy (AP), and Department of Health Behavior and Policy (PC), School of Medicine, Virginia Commonwealth University, Richmond, VA. At the time of study conduction, Department of Biostatistics (HW), School of Medicine, Virginia Commonwealth University, Richmond, VA.

Source of Funding: None.

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 (AP, PC); acquisition of data (HW); analysis and interpretation of data (AP, HW, PC); drafting of the manuscript (AP); critical revision of the manuscript for important intellectual content (PC); statistical analysis (HW, PC); administrative, technical, or logistic support (HW); and supervision (AP). 

Address Correspondence to: Amy Pakyz, PharmD, PhD, MS, Virginia Commonwealth University, 410 N 12th St, Box 980533, Richmond, VA 23298. E-mail: 

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