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The American Journal of Managed Care December 2013
Implementing Effective Care Management in the Patient-Centered Medical Home
Catherine A. Taliani, BS; Patricia L. Bricker, MBA; Alan M. Adelman, MD, MS; Peter F. Cronholm, MD, MSCE, FAAFP; and Robert A. Gabbay, MD, PhD
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Medication Utilization and Adherence in a Health Savings Account-Eligible Plan
Paul Fronstin, PhD; Martin-J. Sepulveda, MD; and M. Christopher Roebuck, PhD, MBA
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Yuan-Ting Lo, PhD; Mark L. Wahlqvist, MD; Yu-Hung Chang, PhD; Senyeong Kao, PhD; and Meei-Shyuan Lee, DPH

Medication Utilization and Adherence in a Health Savings Account-Eligible Plan

Paul Fronstin, PhD; Martin-J. Sepulveda, MD; and M. Christopher Roebuck, PhD, MBA
A consumer-directed health plan with a health savings account was associated with reduced adherence for 4 of 5 conditions.
Baseline adherence as measured by the average PDC ranged from 0.59 for asthma/COPD to 0.91 for hypertension. Using the commonly used threshold of 0.80, the percentage of patients who were adherent prior to CDHP adoption was 88% for hypertension, 75% for dyslipidemia, 84% for diabetes, 39% for asthma/COPD, and 70% for depression. As expected from the coarsened exact matching process, no statistically significant differences were observed in baseline mean values between the CDHP and control groups.

Prescription Drug Utilization and Adherence by Year/Group

Table 3 presents mean levels of the number of prescriptions, PDC, and proportion adherent (PDC >0.80) for each of the 5 chronic diseases by year and group. By design of the matching process, baseline (2006) values were not statistically significant across the CDHP and control groups except for number of depression prescriptions—a point we will return to. With most of the chronic diseases, the 3 outcome measures decreased from 2006 to 2007 for both groups, although the 2007 levels were significantly (P <.05) lower in the CDHP group for all conditions except asthma/COPD. For example, the percentage of hypertension patients who were adherent fell from 88% to 73% for CDHP enrollees compared with a drop from 88% to 78% among control group members, representing a statistically significant (P <.05) difference of 5 percentage points. By 2008, the CDHP hypertension and depression groups had lower drug utilization and PDC than their control counterparts. Moreover, 2008 levels of all 3 measures for dyslipidemia

were significantly (P <.01) lower for the CDHP group.

Regression Analysis

Table 4 presents estimates of the impact of the CDHP-HSA on prescription drug utilization and adherence in 2007 and 2008. After adjusting for the characteristics in Table 2 using the difference-in-differences multivariate models described above, the differential changes in the mean values of the measures observed in the bivariate analysis (Table 3) were confirmed. Specifically, adoption of the CDHP-HSA was associated with decreases in the number of prescriptions filled, the PDC, and the percentage of individuals who were adherent to their medications in the first year for hypertension, dyslipidemia, and diabetes. The magnitudes of the reductions for these 3 chronic diseases in 2007 ranged from –1.2 to –2.4 prescriptions, –0.05 to –0.09 PDC, and –0.04 to –0.13 in the proportion of patients who were adherent. No significant effects were detected in the asthma/COPD analyses. In patients with depression, only the PDC significantly (P <.05) declined, which may suggest a greater rate of first- and secondfill drop-offs (ie, the lower end of the PDC distribution) because the proportion adherent (ie, the higher end of the PDC distribution) was not significantly affected.

The reductions observed in the first year after adoption of the CDHP-HSA appear to have diminished in its second year (2008). Dyslipidemia and hypertension were the only chronic conditions in which changes after CDHP adoption persisted for 2 or more measures of drug utilization and adherence for 2 years. The PDC among CDHP enrollees with depression also remained significantly lower after 2 years. We explicitly tested whether the changes in the measures from 2007 to 2008 were statistically significant, and year-over-year improvements did emerge after CDHP-HSA implementation (Table 4, righthand column). Specifically, the number of prescriptions filled for diabetes and hypertension significantly increased. More over, the proportion adherent among individuals with dyslipidemia and diabetes was 0.03 and 0.07 higher, respectively, in 2008 than in 2007, and the PDC for hypertension patients was also slightly higher.


This study evaluated the impact of a full-replacement CDHP-HSA on utilization of and adherence to medications for 5 chronic conditions. In the first year under the new plan, the number of prescriptions filled, the PDC, and the proportion of patients who were adherent declined for all conditions except asthma/COPD, although for depression, only the drop in PDC was statistically significant. These results are consistent with existing literature indicating that increased patient cost-sharing is associated with decreased health services utilization, 36 specifically prescription drug consumption.13 Except for asthma/COPD, these effects emerged across our fairly heterogeneous set of conditions, a finding also consistent with prior work.28,29 During the second year of the new plan, CDHP-HSA effects persisted in individuals with hypertension, dyslipidemia, and depression, but levels were not as low due to some significant increases in utilization and adherence from year 1 to year 2, particularly among patients with diabetes. It is possible that second-year improvements were due to members learning about the importance of medication adherence and the  parameters of their new CDHP. Alternatively, beneficiaries may have had residual funds in their HSAs—rolled over from the first year—that they used to purchase more prescription drugs.

These findings have important policy implications. Notwithstanding the presence of HSAs and employer contributions, medication utilization and adherence declined when high deductibles were imposed. If these reduced levels of medication adherence for chronic conditions are sustained, it is likely that they will increase medical costs and adversely impact worker productivity.13,37 This cost-shift impact on adherence may be mitigated by designing CDHPs with first-dollar coverage for chronic disease medications using HRAs. Regulatory change is required for first-dollar coverage for HSA-associated CDHPs, as exemptions to the deductible are governed by law. Finally, it appears prudent for plan sponsors to provide education and ongoing support to encourage appropriate use of account funds so that prescription drug use for chronic conditions is prioritized by members, even when budgets are stressed.

Our study has several strengths, the first of which is the use of a matched comparison group of employees of another company that did not alter health benefits. This group allowed for statistical control of some common medication utilization and adherence confounders such as demographics, general health status, and underlying secular trends in prescription drug supply and demand. Moreover, because the study employer fully replaced existing coverage for all employees, our results are robust to selection bias, which often plagues analysis of enrollees in CDHPs introduced as alternatives to other plans. Our study also extends the CDHP literature by reporting on experience under an HSA, as opposed to the more commonly studied HRA-linked CDHP. Finally, the examination of 2 years of data after CDHP-HSA adoption is key because we found some increases and differential effects in the second year.

Our study also has several limitations. Because our study cohort was a single manufacturing employer concentrated in the Midwest, results may not be generalizable to the broader population of national employment-based health plans implementing CDHP-HSAs. Furthermore, although a control group was utilized in the analysis, estimated impacts might still be biased if unobserved characteristics correlated with CDHP were also associated with medication utilization and adherence. For example, if despite being paired with individuals similar with respect to demographics, disease burden, and baseline utilization/adherence rates, socioeconomic status was significantly different for CDHP members compared with control group participants, then our estimates could remain biased, given this factor’s influence on health-related behavior. Participantlevel income data were not available for analysis, nor was the pool of members used in the matching process large enough to include geo-linked sociodemographic variables. 

Similarly, although we matched on Charlson Comorbidity Index score, it is still possible that CDHP and control group members had different comorbidities at baseline, including but not limited to the diseases under study. If true, results might be biased if patients chose to decrease prescription drug utilization for some conditions (eg, asymptomatic ones) over others. We conducted an exploratory re-analysis of the multivariate models on subsamples of individuals with more than 1 of the 5 chronic diseases. While results were qualitatively similar, differences in effect sizes suggest that individuals may make trade-offs among their concomitant therapies when faced with plan design changes that alter out-of-pocket costs. On a related note, depression has been identified as a risk factor for medication nonadherence in patients with other comorbidities.38 Compared with the CDHP cohort, the depression control group had 12% more 30-day adjusted prescriptions at baseline, yet was nearly identical in terms of PDC. This indicates that the 2 groups differed slightly in terms of either their concomitant use or switching of antidepressants, which may suggest a difference in depression severity. Future research should delve more deeply into how patients with greater disease burden respond to increased cost sharing.

Another limitation is that we interpreted the medication utilization and adherence effects as being due to the newly adopted CDHP-HSA itself, or more specifically, the high deductible. It is possible that the plan’s newness itself caused these disruptions. Prior research has found that preventive services not subject to the deductible were associated with lower use of those services

after a CDHP was adopted.19 However, a portion of our control group also likely changed plans during the study period. Therefore, plan change would not be a plausible explanation for persistent second-year impacts. Finally, we did not possess data on HSA balances and could not address key questions related to account dynamics such as contributions, withdrawals, and rollovers, and their association if any with medication utilization by account holders and their enrolled dependents.

Broader implementation of CDHPs is likely as healthcare costs continue their upward climb.18 To ensure that these plans deliver on their promise of wiser consumption of health services while supporting chronic care needs including medication, better insight into longer-term behaviors under CDHPs is needed. Studying lengthier time periods before and after CDHP adoption, and unraveling the influences of socioeconomic and multimorbidity profiles, are good candidates for future research. Collection of biometric data—including side effect profiles—would be highly valuable to allow researchers to tease apart the causes of medication nonadherence.

Author Affiliations: From Employee Benefit Research Institute (PF), Washington, DC; IBM Corporation (M-JS), Southbury, CT; RxEconomics LLC (MCR), Hunt Valley, MD.

Funding Source: None.

Author Disclosures: The authors (PF, M-JS, MCR) 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 (PF, MCR); acquisition of data (PF); analysis and interpretation of data (PF, MCR); drafting of the manuscript (PF, M-JS, MCR); critical revision of the manuscript for important intellectual content (PF, M-JS, MCR); statistical analysis (MCR); administrative, technical, or logistic support (PF, MCR); and supervision (PF, M-JS, MCR).

Address correspondence to: Paul Fronstin, PhD, Director, Health Research and Education Program, Employee Benefit Research Institute, 1100 13th St, NW, Ste 878, Washington, DC 20005. E-mail:
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