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The American Journal of Managed Care April 2018
Delivering on the Value Proposition of Precision Medicine: The View From Healthcare Payers
Jane Null Kogan, PhD; Philip Empey, PharmD, PhD; Justin Kanter, MA; Donna J. Keyser, PhD, MBA; and William H. Shrank, MD, MSHS
Care Coordination for Children With Special Needs in Medicaid: Lessons From Medicare
Kate A. Stewart, PhD, MS; Katharine W.V. Bradley, PhD, MBA; Joseph S. Zickafoose, MD, MS; Rachel Hildrich, BS; Henry T. Ireys, PhD; and Randall S. Brown, PhD
Cost Sharing and Branded Antidepressant Initiation Among Patients Treated With Generics
Jason D. Buxbaum, MHSA; Michael E. Chernew, PhD; Machaon Bonafede, PhD; Anna Vlahiotis, MA; Deborah Walter, MPA; Lisa Mucha, PhD; and A. Mark Fendrick, MD
The Well-Being of Long-Term Cancer Survivors
Jeffrey Sullivan, MS; Julia Thornton Snider, PhD; Emma van Eijndhoven, MS, MA; Tony Okoro, PharmD, MPH; Katharine Batt, MD, MSc; and Thomas DeLeire, PhD
A Payer–Provider Partnership for Integrated Care of Patients Receiving Dialysis
Justin Kindy, FSA, MAAA; David Roer, MD; Robert Wanovich, PharmD; and Stephen McMurray, MD
Currently Reading
Financial Burden of Healthcare Utilization in Consumer-Directed Health Plans
Xinke Zhang, PhD; Erin Trish, PhD; and Neeraj Sood, PhD
Physician and Patient Tools to Improve Chronic Kidney Disease Care
Thomas D. Sequist, MD, MPH; Alison M. Holliday, MPH; E. John Orav, PhD; David W. Bates, MD, MSc; and Bradley M. Denker, MD
Limited Distribution Networks Stifle Competition in the Generic and Biosimilar Drug Industries
Laura Karas, MD, MPH; Kenneth M. Shermock, PharmD, PhD; Celia Proctor, PharmD, MBA; Mariana Socal, MD, PhD; and Gerard F. Anderson, PhD
Provider and Patient Burdens of Obtaining Oral Anticancer Medications
Daniel M. Geynisman, MD; Caitlin R. Meeker, MPH; Jamie L. Doyle, MPH; Elizabeth A. Handorf, PhD; Marijo Bilusic, MD, PhD; Elizabeth R. Plimack, MD, MS; and Yu-Ning Wong, MD, MSCE

Financial Burden of Healthcare Utilization in Consumer-Directed Health Plans

Xinke Zhang, PhD; Erin Trish, PhD; and Neeraj Sood, PhD
Enrollment in a consumer-directed health plan increases the financial burden associated with healthcare utilization, especially for those with lower incomes and with chronic conditions.
RESULTS

Baseline Enrollee Characteristics

There were a total of 689,542 enrollees in our sample, consisting of 36,387 enrollees in the CDHP group and 653,155 enrollees in the traditional plan group. The baseline characteristics of each group are shown in Table 1. The χ2 test indicates that CDHP enrollees differed from traditional plan enrollees in terms of age, education, gender, health status, region, and race and ethnicity. There were no statistically significant differences in predicted annual household income between the 2 groups.

Trends in OOP Spending and Financial Burden

Both the levels and trends in our key outcome variables were similar for the CDHP and the traditional plan group during the pre-CDHP enrollment period of up to 2 years (eAppendix Figures 1 and 2). Within the first year of CDHP enrollment, the percentage of CDHP enrollees having excessive financial burden rose from 9.7% (95% CI, 9.4%-10.0%) to 16.0% (95% CI, 15.7%-16.4%) for the full sample, compared with a slight increase from 9.0% (95% CI, 8.9%-9.1%) to 9.8% (95% CI, 9.7%-9.9%) among traditional plan enrollees (eAppendix Figure 2).

The impact of CDHP enrollment on financial burden was more pronounced among the lower-income and chronic conditions subgroups: The percentage of CDHP enrollees having excessive financial burden among these subgroups rose from 32.9% (95% CI, 31.4%-34.5%) to 47.7% (95% CI, 46.1%-49.4%) and from 25.3% (95% CI, 24.1%-26.5%) to 33.9% (95% CI, 32.7%-35.2%), respectively (eAppendix Figure 2). The effects of CDHP enrollment persisted for 2 years; OOP spending increased among CDHP enrollees while OOP spending for traditional plan enrollees remained stable (eAppendix Figure 1).

Regression Results

The effects of CDHP enrollment on mean OOP spending are shown in Table 2. In the first year of CDHP enrollment, the mean marginal increase in OOP spending was $285 (41% increase; 95% CI, $271-$299; <.001). CDHP enrollment resulted in larger marginal increases in OOP spending for the lower-income ($306; 44% increase; 95% CI, $257-$354; <.001) and chronic conditions ($387; 56% increase; 95% CI, $339-$435; <.001) subgroups. By the second year of CDHP enrollment, mean marginal OOP spending increased by $306 among the full sample (44% increase; 95% CI, $286-$325; <.001), $364 (53% increase; 95% CI, $300-$429; <.001) among the lower-income subgroup, and $428 (62% increase; 95% CI, $364-$492; <.001) among the chronic conditions subgroup. The larger increases in OOP spending in the second year of CDHP enrollment are consistent with prior work which has found that utilization increases in the second year of CDHP enrollment.8,9

Table 3 presents the QDID estimates of the impact of CDHP enrollment at each decile across the distribution of OOP spending. Generally, the marginal effect of CDHP enrollment increased with higher levels of OOP spending. For example, among the full sample, CDHP enrollment led to a $162 (95% CI, $150-173; <.001) marginal increase in OOP spending at the median in the first year compared with a $726 (95% CI, $678-$773; <.001) marginal increase in OOP spending at the 90th percentile. That is, the marginal impact of CDHP enrollment on OOP spending (compared with traditional plan enrollees) was greater for those at the higher end of the OOP spending distribution. For the lower-income and chronic conditions subgroups, the marginal increases at the median were $241 (95% CI, $200-$282; <.001) and $480 (95% CI, $425-$535; <.001), respectively, and the marginal increases at the 90th percentile were $715 (95% CI, $558-$871; <.001) and $647 (95% CI, $495-$799; <.001), respectively.

The adjusted and counterfactual OOP spending distributions for the traditional plan group are shown in the Figure. As expected, the counterfactual OOP spending distributions fall above the predicted OOP spending distribution, suggesting that traditional plan enrollees would have had higher OOP spending if they had switched to a CDHP (Figure). As a sensitivity analysis, we also separately estimated the magnitude of these counterfactual spending estimates if the traditional plan group switched to CDHP/HRAs compared with CDHP/HSAs (based on separate underlying QDID regressions for the CDHP/HRA and CDHP/HSA populations). We found that increased OOP spending after enrollment in a CDHP tended to be larger for enrollees in CDHP/HRAs versus CDHP/HSAs across nearly all of the OOP spending distributions (eAppendix Figure 3). This is consistent with prior work, which has found that enrollees in CDHP/HSAs had significantly greater reductions in utilization than did enrollees in CDHP/HRAs, potentially because employees with HSAs have a stronger incentive to save money because HSA account balances are owned by the employee whereas HRA account balances are owned by the employer.23

CDHP enrollment also increased the probability of having very high OOP spending. For example, the percentage of enrollees spending more than $2000 increased by nearly 10 percentage points for the full sample and for the lower-income subgroup and by about 15 percentage points for the chronic conditions subgroup (Figure). These findings regarding the impact of CDHPs on the probability of having very high OOP spending are supported by the results of the impact of CDHP enrollment on the probability of having excessive financial burden (Table 2b). For the entire sample, enrollment in a CDHP increased the probability of an enrollee being exposed to excessive financial burden (defined as OOP spending being ≥3% of household income) by 4.3 percentage points (95% CI, 4.0-4.6; ​<.001; baseline, 9.7%). The effects were about 3 times larger for the lower-income subgroup (12.3 percentage points; 95% CI, 10.7-13.8; <.001; baseline, 32.9%) and 2 times larger for the chronic conditions subgroup (8.0 percentage points; 95% CI, 6.9-9.1; <.001; baseline, 25.3%). These effects persisted in the second year of CDHP enrollment and were robust to alternative definitions of excessive financial burden (Table 2b).



 
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