eFigure 1. Study Cohort Selection
eTable 1. Baseline Characteristics of Children and Adults in the Study Population, Before Matching
eFigure 2. Aggregate Interrupted Time Series Regression Results for Monthly 30-day Fill Rates for High-Deductible Health Plan (HDHP) and Control Enrollees and the Difference Between Them From Baseline Period (Months 1 – 12) to Follow-Up Period (Months 13-24)
eFigure 3. Aggregate Interrupted Time Series Regression Results for Monthly Rates of Asthma Exacerbations (Oral Steroid Bursts (OCS) and Asthma-Related Emergency Department (ED) Visits) for High-Deductible Health Plan (HDHP) and Control Enrollees and the Difference Between Them From Baseline Period (Months 1 – 12) to Follow-Up Period (Months 13-24)
eTable 2. Adjusted Rates of Asthma Controller Medication Use, Adherence, and Exacerbations Before and After Switching to an HDHP Compared With a Control Group Remaining in a Traditional Plan, Among Adults and Children With Three or More Controller Fills
eTable 3. Adjusted Rates of Asthma Controller Medication Use, Adherence, and Exacerbations Before and After Switching to an HDHP Compared With a Control Group Remaining in a Traditional Plan, Among Adults and Children Between 2009-2014
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Galbraith AA, Ross-Degnan D, Zhang F, et al. Controller Medication Use and Exacerbations for Children and Adults With Asthma in High-Deductible Health Plans. JAMA Pediatr. 2021;175(8):807–816. doi:10.1001/jamapediatrics.2021.0747
Is enrollment in a high-deductible health plan (HDHP) associated with changes in asthma controller medication use and outcomes?
In this cohort study of 7275 children and 17 614 adults with HDHPs, among children with asthma in a setting where most HDHPs exempted medications from the deductible, children who switched to HDHPs had minimal or no significant reductions in 30-day fills and adherence for controller medications relative to those staying in traditional plans and no significant differences in asthma exacerbations. Findings among adults with asthma were similar.
These findings suggest that enrollment in HDHPs may not be associated with changes in asthma medication use or exacerbations when medications are exempt from the deductible.
High-deductible health plans (HDHPs) are increasingly common and associated with decreased medication use in some adult populations. How children are affected is less certain.
To examine the association between HDHP enrollment and asthma controller medication use and exacerbations.
Design, Setting, and Participants
For this longitudinal cohort study with a difference-in-differences design, data were obtained from a large, national, commercial (and Medicare Advantage) administrative claims database between January 1, 2002, and December 31, 2014. Children aged 4 to 17 years and adults aged 18 to 64 years with persistent asthma who switched from traditional plans to HDHPs or remained in traditional plans (control group) by employer choice during a 24-month period were identified. A coarsened exact matching technique was used to balance the groups on characteristics including employer and enrollee propensity to have HDHPs. In most HDHPs, asthma medications were exempt from the deductible and subject to copayments. Statistical analyses were conducted from August 13, 2019, to January 19, 2021.
Employer-mandated HDHP transition.
Main Outcomes and Measures
Thirty-day fill rates and adherence (based on proportion of days covered [PDC]) were measured for asthma controller medications (inhaled corticosteroid [ICS], leukotriene inhibitors, and ICS long-acting β-agonists [ICS-LABAs]). Asthma exacerbations were measured by rates of oral corticosteroid bursts and asthma-related emergency department visits among controller medication users.
The HDHP group included 7275 children (mean [SD] age, 10.8 [3.3] years; 4402 boys [60.5%]; and 5172 non-Hispanic White children [71.1%]) and 17 614 adults (mean [SD] age, 41.1 [13.4] years; 10 464 women [59.4%]; and 12 548 non-Hispanic White adults [71.2%]). The matched control group included 45 549 children and 114 141 adults. Compared with controls, children switching to HDHPs experienced significant absolute decreases in annual 30-day fills only for ICS-LABA medications (absolute change, −0.04; 95% CI, −0.07 to −0.01). Adults switching to HDHPs did not have significant reductions in 30-day fills for any controllers. There were no statistically significant differences in PDC, oral steroid bursts, or asthma-related emergency department visits for children or adults. For the 9.9% of HDHP enrollees with health savings account–eligible HDHPs that subjected medications to the deductible, there was a significant absolute decrease in PDC for ICS-LABA compared with controls (−4.8%; 95% CI, −7.7% to −1.9%).
Conclusions and Relevance
This cohort study found that in a population where medications were exempt from the deductible for most enrollees, HDHP enrollment was associated with minimal or no reductions in controller medication use for children and adults and no change in asthma exacerbations. These findings suggest a potential benefit from exempting asthma medications from the deductible in HDHPs.
Asthma is a major cause of preventable disease burden for children and adults, with substantial socioeconomic disparities.1-4 Despite guidelines recommending use of controller medications such as inhaled corticosteroids (ICS), leukotriene inhibitors (LTIs), or combination ICS and long-acting β2-agonists (ICS-LABAs) and demonstrated efficacy,5-13 adherence is suboptimal, placing patients at risk for asthma exacerbations.11-14 High out-of-pocket costs have been associated with decreased controller medication use and adverse asthma outcomes over 12-month periods for children and adults.15-19
Out-of-pocket costs can be substantial in high-deductible health plans (HDHPs). Approximately one-half of people with employer coverage and the majority with individual coverage have HDHPs.20-23 For the 24% of employees with HDHPs eligible for health savings accounts (HSAs), deductibles are greater than $1400 and apply to all services except preventive care.24 Most HDHP enrollment is in non–HSA-eligible plans, which often exempt services such as medications from the deductible.21 However, copayments in non-HSA HDHPs may still be substantial, and enrollees might still broadly reduce health care use owing to lack of awareness of cost-sharing exemptions or by avoiding related services that are subject to the deductible.25-27 Studies of HDHPs have found decreased use of medications generally28-34 but mixed results for asthma medications,35-37 and few have assessed effects on clinical outcomes.38
Concern has been raised about the effect of HDHPs on children, especially those with special health care needs.39 Evidence about HDHPs comes mostly from adult-focused studies and whether these findings can be applied to children is unclear. Some studies suggest that children are protected from reductions in care due to cost,40,41 whereas others have found that both children and adults are vulnerable.42,43
In this study, we examined the association between HDHP enrollment and asthma controller medication fills, adherence, and exacerbations in a national, commercially insured population of children and adults in which most HDHPs exempted medications from the deductible. We hypothesized that HDHP enrollment would be associated with decreased asthma controller medication fills and adherence and increased asthma exacerbations.
This cohort study included enrollees with employer-sponsored insurance from a large, national, commercial (and Medicare Advantage) database between January 1, 2002, and December 31, 2014. We identified adults (aged 18-64 years) and children (aged 4-17 years) with medical and pharmacy coverage who had at least 24 months of continuous enrollment, during which they had at least 1 claim for an outpatient visit, emergency department (ED) visit, or hospitalization with an asthma diagnosis (International Classification of Diseases, Ninth Revision 493.XX) (eFigure 1 in the Supplement). Of these enrollees, we selected individuals with persistent asthma in the year before the baseline period using the Johns Hopkins ACG System, version 11.1 (Johns Hopkins University) persistent asthma designation, which aligns with the Health Effectiveness Data and Information Set definition (asthma diagnosis in 1 inpatient stay or ED visit, or in 4 outpatient visits plus 2 asthma medication fills, or 4 asthma medication fills within 12 months).44 We excluded enrollees with a diagnosis code for another serious comorbid pulmonary condition.17,45,46 This study was approved by the Harvard Pilgrim Health Care Institutional Review Board, which waived the requirement for informed consent because data were deidentified. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Insurance plans were categorized as HDHP (annual individual deductible of $1000 or more) or a traditional plan (deductible of $0-$500). Although the federal minimum deductible level for an HSA-qualified HDHP changes annually, from $1000 in 2004 to $1400 in 2020, we chose a $1000 deductible to define HDHPs to more broadly include the majority of HDHPs that are not HSA eligible.21,23 We directly measured deductible levels when available and otherwise imputed this information using aggregated out-of-pocket spending among employees within an employer.47,48 High-deductible health plans on average required substantially higher cost-sharing for specialist, acute care, and ED visits than traditional plans; prescription drugs were usually subject to copayments, except for HSA HDHPs for which drugs were subject to the deductible.
In order to reduce member selection bias, we included only enrollees whose employers offered only 1 deductible level (high or low/none) in each study year. The HDHP group included enrollees with employers who switched to only offering an HDHP after a baseline period of 12 months in a traditional plan, then had continued enrollment in the HDHP for a follow-up period of 12 months. The date of the plan switch was the index date. The control group comprised enrollees with employers that offered only traditional plans for at least 24 months. We assigned the plan anniversary date as the index date for control group enrollees. Enrollees aged 18 years or older before the end of their follow-up period were categorized as adults.
We used a coarsened exact match that included employer propensity to switch to offering HDHPs and enrollee-level propensity to be employed by these employers.47-51 Variables included in the models were chosen based on a theorized or demonstrated relationship with HDHP enrollment and asthma medication use and exacerbations. Individual-level propensity models included the following baseline variables: index month and year, age at index, sex, Johns Hopkins ACG morbidity score, number of chronic conditions,44,52 number of family members sharing the insurance plan and number with asthma, race/ethnicity, month and year starting the enrollment episode, and census tract–level education and poverty. Employer-level propensity models included mean employee age, mean employee ACG morbidity score, percent of employees by region, race/ethnicity, census tract–level poverty and education, mean total standardized health spending per member (intercept and trend), and ratio of out-of-pocket to standardized total cost for the employer. We categorized employer and enrollee propensity scores into tertiles and used these tertiles in the coarsened exact match along with adult and child status, region, month, and year of first asthma diagnosis, enrollee out-of-pocket spending trend during baseline, employer size, and mean monthly out-of-pocket spending per enrollee for the employer during baseline. We included all available matched controls. For subgroup analyses, we conducted separate matches within each stratum, within controller class for proportion of days covered (PDC) analyses, and within users of any controller for exacerbation analyses, using the same method, resulting in variable ratios for HDHP and controls depending on the number of available matched controls in each subgroup.48,51,53
We used a difference-in-differences design to assess changes in outcomes from baseline to follow-up for HDHP enrollees relative to controls. The main study outcomes were controller medication fills, adherence, and asthma exacerbations. We identified all filled prescriptions for ICS, LTIs, and ICS-LABAs during the baseline and follow-up periods. We then used the days supplied for each fill to calculate the number of 30-day fills per enrollee per controller class in each study period. We identified members who never had deductible costs for controller fills in the follow-up period and paid only copayments, and among them, we measured the mean copayment per fill by controller class. We measured adherence using the PDC for each controller class among enrollees with at least 1 fill in the first 6 months of the baseline period.14,54 Going forward from the first fill of the baseline period through the end of the follow-up period, we measured the days supplied for medications of that class in each study period. Because the number of days in the denominator varied based on the date of the first fill, we standardized the number of days supplied to a 365-day denominator and used the standardized days supplied in models, then calculated the PDC as the proportion of days supplied out of 365 days.
We measured asthma exacerbations among enrollees who used any controller medication in the baseline period. Asthma exacerbations were measured as rates of oral corticosteroid (OCS) bursts and asthma-related ED visits. We defined OCS bursts as a dispensing of a 3- to 21-day supply after a “clean period” of at least 30 days without an OCS dispensing.46 We defined asthma-related ED visits as all ED visits with a principal diagnosis of asthma, or with any diagnosis of asthma in combination with a diagnosis of a related condition.45,46
In addition to the covariates described previously, we used 2008-2012 American Community Survey data at the census tract level to categorize enrollees’ neighborhood education according to the percent of residents with less than a high school education and categorize neighborhood income as low if the percent of residents below the poverty level was greater than or equal to 10.0%.55-57 Because race/ethnicity is a potential confounder of health care use, we used geocoding to classify participants as being from predominantly White, Black, Hispanic, or mixed neighborhoods and used a superseding Hispanic or Asian categorization based on the E-Tech System (Ethnic Technologies), which analyzes full names and geographic locations of individuals.47,48,58-60 Only 0.2% of the population had missing data, occurring for income, education, race/ethnicity, and region; these enrollees were dropped from analyses.
Statistical analyses were conducted from August 13, 2019, to January 19, 2021. We applied match-generated weights in all statistical analyses.48,49,51,61 We compared baseline characteristics of the study groups using standardized mean differences.62 To assess for parallel baseline trends, we calculated the difference between monthly HDHP and control group rates of 30-day fills and exacerbations and used aggregate-level interrupted time series segmented linear regression to model the trend for the difference.63 We used generalized estimating equations, accounting for within-enrollee clustering over time, and applied the robust sandwich estimator, assuming an exchangeable working correlation structure,64 in an effort to compare changes in outcomes from baseline to follow-up (before and after enrollment in an HDHP) vs controls. We removed the last month of the baseline period and first month of the follow-up period to exclude the potential for stockpiling medications in anticipation of the HDHP transition. We used a negative binomial distribution for count outcomes (30-day fills, OCS bursts, and ED visits) and binomial distribution for the PDC, which was modeled as the number of days supplied out of 365 days. Models were adjusted for index month and year, first asthma diagnosis month and year, sex, number of chronic conditions, ACG morbidity score, race/ethnicity, neighborhood income and education, and number of family members plus number of family members with asthma, with an interaction between study group (HDHP vs control) and time period (baseline vs follow-up year). Using terms from the regression model, we then applied marginal effects methods65 to calculate mean adjusted baseline and follow-up outcome rates and the PDC as well as absolute changes. We used the Holm-Bonferroni correction for multiple comparisons to establish the P-value thresholds for statistical significance for the set of statistical tests for each subgroup (adults, children, HSA HDHPs, etc). These P values were less than the standard .05 but not the same across subgroups.66 We conducted secondary analyses among several subgroups within the combined population of adults and children: enrollees in HSA HDHPs and non-HSA HDHPs, those living in low-income neighborhoods,55-57 those with 3 or more controller fills of 1 class, and those enrolled more recently (index dates, 2009-2014). For subgroup analyses, we applied the same methods and outcomes described previously. Statistical analyses were conducted using Stata, version 15 (StataCorp LLC).67
After matching, the HDHP group included 7275 children (mean [SD] age, 10.8 [3.3] years; 4402 boys [60.5%], 5172 non-Hispanic White children [71.1%]) and 17 614 adults (mean [SD] age, 41.1 [13.4] years; 10 464 women [59.4%], 12 548 non-Hispanic White adults [71.2%]). The control group included 45 549 children and 114 141 adults. Groups were balanced with respect to baseline characteristics as indicated by standardized mean differences less than 0.2 (Table 1; eTable 1 in the Supplement).62,68 The majority of participants had enrollment through small employers, were from the South or Midwest, and lived in predominantly White and well-educated neighborhoods; more than 30% lived in low-income neighborhoods. The majority of children were boys, whereas the majority of adults were women. Among those in the HDHP group, 2500 of 24 889 (10.0%) had HSA HDHPs. Among those in non–HSA-eligible HDHPs, 17 543 of 18 798 (93.3%) paid copayments for controller fills in the follow-up period with a mean copayment per fill of $30.30 for ICS, $33.10 for LTI, and $41.80 for ICS-LABA; copayments were $26.50, $26.80, and $35.80, respectively, for controls.
Interrupted times series analyses revealed either parallel baseline trends or, among the minority of measures that did not have parallel trends, effect estimates that were consistent with difference-in-differences analyses (eFigures 2 and 3 in the Supplement), except for children’s ICS-LABA fills.
In difference-in-differences analyses among children, the HDHP group had absolute reductions in 30-day fills for ICS-LABA (−0.04; 95% CI, −0.07 to −0.01) compared with controls (Table 2). Changes in fill rates for other controllers among children were not statistically significant after adjustment for multiple comparisons. There were no significant changes in the PDC for any controller class or in rates of OCS bursts or asthma-related ED visits for HDHP children relative to controls.
Among adult HDHP enrollees, there were no significant pre-to-post differences in 30-day fills or the PDC relative to controls for any controller class or for OCS bursts or asthma-related ED visits (Table 2). Notably, 85 201 of 131 755 adults (64.7%) and 32 394 or 52 824 children (61.3%) did not fill any controller medications in the baseline year.
Among the subgroup of enrollees switching to HSA HDHPs, we found no significant differences in 30-day fills relative to controls, but a significant absolute reduction in the PDC for ICS-LABA (−4.8%; 95% CI, −7.7% to −1.9%) (Table 3). Those switching to non-HSA HDHPs also did not have significant changes relative to controls for controller fills and the PDC except for an absolute reductions in 30-day fills for ICS-LABA (−0.03; 95% CI, −0.06 to −0.01). There were no significant differences in OCS bursts or asthma-related ED visits.
Findings among enrollees living in low-income neighborhoods were similar to the overall findings, with absolute reductions in the PDC for ICS-LABA for the HDHP group vs controls (−2.4%; 95% CI, −4.1% to −0.7%) but otherwise no significant differences in controller fills, PDC, or exacerbations (Table 4). Findings for enrollees with greater baseline controller use (3 or more fills) and those in more recent years (2009-2014) showed no significant differences between HDHP and control groups (eTables 2 and 3 in the Supplement).
In this cohort study of children and adults with persistent asthma but low use of controller medications insured by a national commercial health plan where HDHPs largely exempted medications from the deductible, we found small reductions in ICS-LABA fills for children switching to HDHPs compared with those staying in traditional plans but no significant decreases in other controller medication fills or adherence. We found no worsening of asthma outcomes as measured by OCS bursts and asthma-related ED visits. The response to HDHPs was generally similar for adults.
Although some studies in adults have found reductions in medication use in HDHPs,32,35,36 this study is consistent with other adult studies that found minimal to no reduction in medication use without detectable changes in health outcomes.33,37,69-71 Unlike in other studies, we did not find that adults were more likely than children to underuse care when faced with cost burden.40,41
The lack of substantial reduction in asthma controller use in HDHPs in our study may stem from the fact most HDHPs in our study exempted medications from the deductible and instead applied copayments, which is largely the case nationally.21 For HSA HDHP enrollees, there was an associated greater reduction in ICS-LABA use than for non-HSA HDHP enrollees, although the smaller number of HSA HDHP enrollees limits power for statistical comparison. The protective effect of exempting certain health care services from the deductible37,72-76 is the premise behind value-based insurance designs, which seek to reduce cost-sharing for important preventive and chronic illness care and have been shown to improve adherence to chronic medications and reduce medication cost burden.76-78 Policy makers should consider adopting value-based designs and other policies that exempt important medications for asthma and other chronic conditions from the deductible, which might prevent adverse clinical outcomes in HDHPs.79
Another potential explanation for the lack of adverse asthma outcomes found in HDHPs in our study is that small reductions in controller use may be inconsequential for the large proportion of enrollees with milder asthma or low levels of baseline adherence.80 It is notable that baseline controller adherence was not high in our study and declined considerably through the follow-up period for both HDHP and control groups. However, we also did not see worse outcomes in subgroup analyses of HDHP enrollees with more baseline controller fills. Enrollees at greater risk for asthma exacerbations may prioritize using controllers despite the potential for higher cost burden.70 Asthma outcomes may not substantially change in HDHPs if enrollees with more severe asthma anticipate reaching their deductible early in the year or if asthma costs are offset with HSA funding. The HDHP enrollees may have had increased symptoms or asthma exacerbations that could not be measured in claims data, such as missed school or workdays. Additionally, asthma exacerbations were measured based on utilization that may have also been discouraged by deductible costs in HDHPs.38,81,82
Our findings were not substantively different among subgroups from low-income neighborhoods, with greater baseline controller medication use, or with more recent enrollment. As with the main analyses, small reductions were found for HDHP enrollees in use of ICS-LABA, a more costly class of controllers83,84 with higher copayments paid per fill in our study.
Several limitations should be noted. Because this is an observational study in which insurance plan type was not randomly assigned, selection effects may exist. Findings for ICS-LABA fills for children should be interpreted with the caveat that the parallel trends assumption for difference-in-differences analyses was not met, and that interrupted time series analysis did not detect a statistically significant change in the follow-up period. Although our data do not allow us to detect whether employers offered plans from other carriers, most enrollees in our study population had small employers (employers with less than 100 employees), who tend to offer only 1 plan.85 We were unable to account for potential within-employer correlations owing to computational challenges and unmet assumptions. For subgroup analyses and less frequent outcomes, such as asthma-related ED visits, power to detect smaller differences was limited. We lacked individual-level data on income and other socioeconomic characteristics but used well-established methods based on proxy census tract–level attributes.48,56-58 Findings may not generalize to populations with public insurance, more severe asthma, more regular baseline controller use, or comorbid pulmonary conditions.
In this cohort study of commercially insured children with persistent asthma but low use of controller medications, results suggest that switching to HDHPs that largely exempted medications from the deductible was associated with small to no reductions in use of controller medications and no change in asthma exacerbations. Findings for adults were similar. As the prevalence of HDHPs continues to increase, these findings suggest that HDHP enrollment may not be associated with negative outcomes in some situations, for example, when medications are exempt from the deductible or for those with low baseline asthma controller use. These findings suggest value-based designs as an approach for policy makers, payers, and families in the quest to balance affordable coverage with access to necessary asthma care.
Accepted for Publication: January 27, 2021.
Published Online: May 10, 2021. doi:10.1001/jamapediatrics.2021.0747
Corresponding Author: Alison A. Galbraith, MD, MPH, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Dr, Ste 401, Boston, MA 02215 (firstname.lastname@example.org).
Author Contributions: Dr Galbraith had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Galbraith, Ross-Degnan, Peltz, Wharam.
Acquisition, analysis, or interpretation of data: Galbraith, Ross-Degnan, Zhang, Wu, Sinaiko, Xu, Wallace, Wharam.
Drafting of the manuscript: Galbraith, Peltz, Xu.
Critical revision of the manuscript for important intellectual content: Ross-Degnan, Zhang, Wu, Sinaiko, Peltz, Wallace, Wharam.
Statistical analysis: Zhang, Sinaiko, Xu, Wharam.
Obtained funding: Galbraith.
Administrative, technical, or material support: Ross-Degnan, Wallace, Wharam.
Supervision: Wu, Peltz, Wallace, Wharam.
Conflict of Interest Disclosures: Dr Galbraith reported receiving grants from the Patient-Centered Outcomes Research Institute (PCORI), the Agency for Healthcare Research and Quality, and Harvard Pilgrim Health Care during the conduct of the study. Dr Ross-Degnan reported receiving grants from PCORI during the conduct of the study. Dr Zhang reported receiving funding from PCORI during the conduct of the study. Dr Wu reported receiving funding from GlaxoSmithKline for research outside the submitted work and funding from PCORI during the conduct of the study. Dr Sinaiko reported receiving grants from PCORI during the conduct of the study. Mr Xu reported receiving funding from PCORI during the conduct of the study. Dr Wallace reported receiving grants from PCORI during the conduct of the study. Dr Wharam reported receiving grants from PCORI during the conduct of the study. No other disclosures were reported.
Funding/Support: This work was supported by grant IHS-1602-3433 from a PCORI Project Program award (Dr Galbraith).
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: All statements in this report, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the PCORI, its Board of Governors, or its Methodology Committee. Dr Galbraith is an Associate Editor of JAMA Pediatrics, but she was not involved in any of the decisions regarding review of the manuscript or its acceptance.
Meeting Presentations: Abstracts describing study findings were presented at the annual Pediatric Academic Societies, April 30, 2019, Baltimore, Maryland; at the Society for General Internal Medicine, May 9, 2019, Washington, DC; and at the Academy Health 2019 Annual Research Meeting, June 2, 2019, Washington, DC.
Additional Contributions: We thank our partners on the AFFORD (Asthma in Families Facing Out-of-pocket Requirements with Deductibles) project: the Asthma and Allergy Foundation of America, the AFFORD Advisory Board, and the AFFORD Patient and Family Advisory Council. We also thank Lauren Cripps, MA, for project management, Mikaela Batista, MA, for administrative support, and Robert LeCates, MA, for programming support; all are affiliated with the Harvard Pilgrim Health Care Institute and were compensated for their efforts through project funds (Ms Cripps and Mr LeCates) and departmental funds (Ms Batista).