Racial Inequality in Inhaler Fills for COPD - A Trial of Reduced Cost-Sharing
Phase: NA
Conditions: Chronic Obstructive Pulmonary Disease
Sponsor: Harvard Medical School (HMS and HSDM)

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Racial Inequality in Inhaler Fills for COPD – A Trial of Reduced Cost-Sharing 
Protocol and Analysis Plan 
 
August 4, 2022 
 
ClinicalTrials.gov Identifier: NCT05497999 
 
Study Team 
Harvard Medical School: Michael Chernew, Michael McWilliams, Sumit Agarwal 
Humana: Ben Conway, Brian Powers, Dana Drzayich Antol, Elizabeth Metzler, Emily 
Boudreau, Emily Thomas, Marc McKenna, Matthew Benge, Michelle Martin, Sam Cole, 
William Shrank 
University of Chicago: Valerie Press 
 
 
 
 
 
 
 
Disclaimer: The statements contained in this document are solely those of the authors and do not 
necessarily reflect the views or policies of the Centers for Medicare and Medicaid Services. The 
authors assume responsibility for the accuracy and completeness of the information contained in 
this document. 
 
 

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Table of Contents 
 
Section A. Introduction …………………………………………………………………… 
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Section B. Treatment ……………………………………………………………………… 3 
 
 
Section C. Randomization and Patient Eligibility ………………………………………… 4 
 
 
Section D. Data, Study Sample, Outcomes, and Other Variables ………...………………. 5 
 
 
Section E. Statistical Analysis ……………………………………………….……………. 7 
 
 
Section F. Tables …………………………………………………………………………. 
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A. Introduction 
The prevalence of and morbidity from chronic obstructive pulmonary disease (COPD) is higher 
among Black populations than other racial groups in the United States. In this study, we will 
examine how elimination of cost-sharing for maintenance inhalers could potentially mitigate 
racial disparities in the care of patients with COPD. Maintenance inhalers for COPD are highly 
effective in reducing patient morbidity and mortality, but cost-sharing may reduce their 
utilization, particularly among vulnerable patient populations. Despite its ubiquity, there is little 
rigorous evidence on how cost-sharing might contribute to health disparities. 
In partnership with a large Medicare Advantage (MA) insurer (Humana Inc.) and as part of a 
Center for Medicare and Medicaid Innovation demonstration program of Value-Based Insurance 
Design (VBID), we propose to study a randomized controlled quality improvement trial in which 
Humana randomized MA beneficiaries with COPD to receive proactive outreach for a VBID 
benefit that provided large reductions in cost-sharing for their maintenance inhalers and 
telephone-based COPD medication management services in 2020 and 2021. We will analyze 
changes in racial disparities for inhaler fills, clinical outcomes, health care spending, and acute 
care utilization. This proposal and analysis plan detail the intervention, randomization, and data 
source. Importantly, while this analysis plan is specified after the conduct of the trial, it does pre-
specify the outcomes and statistical analysis prior to analysis of the trial data. Power analyses 
were conducted to inform the pre-specification of primary and secondary outcomes. No analyses 
of post-intervention outcomes were conducted prior to drafting and posting this proposal and 
analysis plan. 
 
B. Treatment 
The treatment is proactive outreach that sought to enroll individuals in a VBID program that was 
available to all eligible beneficiaries and provided: 1) large reductions in cost-sharing for 
maintenance inhalers, and 2) telephone-based COPD medication management services. Proactive 
outreach for those randomized to the treatment arm included, at a minimum, a phone call and 
letter in the mail from Humana. Proactive outreach could also have included an email, text 
message, and/or provider referral. Control group participants received no proactive outreach but 
could call to enroll themselves in the VBID program if they learned about it through traditional 
means, such as the benefits description manual. (As discussed in further detail below, the 
primary analysis will be on an intent-to-treat basis to account for incomplete take-up after 
outreach and crossover; in a separate analysis, we will also estimate a local average treatment 
effect using an instrumental variables approach.) 
As noted above, the VBID program had two components. The first was a substantial reduction in 
beneficiary cost-sharing for maintenance inhalers. The specific maintenance inhalers eligible for 
cost-sharing reduction were those on tier 3 of the insurer’s formulary (see Table 1 for full list). 
All other maintenance inhalers remained on a higher tier (i.e., tier 4) or were non-formulary, 
neither of which were eligible for cost-sharing reduction. Nebulized versions of these 
medications, regardless of tier, were similarly not eligible.  

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The cost-sharing reduction brought the out-of-pocket payment down to $0 if the participant 
elects to receive a 90-day supply at a preferred pharmacy (e.g., for delivery), or $10 if the 
participant elects to receive a 30-day supply at other in-network pharmacies. For beneficiaries in 
the deductible phase of their MA plan, the monthly payment for an inhaler therefore can go 
down from over $400 (maximum of $445 in 2021 and $435 in 2020) to either $0 or $10. For 
beneficiaries in the initial coverage phase of their MA plan, the monthly payment for an inhaler 
goes down from about $50 to either $0 or $10. For beneficiaries in the coverage gap phase or 
catastrophic phase of their MA plan, there is no additional cost-sharing reduction for participants 
who enrolled in the program. Individuals can be on more than one inhaler, and the cost-sharing 
reduction applies to all eligible tier 3 inhalers. 
The second component of the program was up to three telephone calls for medication 
management services focused on addressing educational barriers to using the inhaler as 
prescribed. Participants enrolling in the VBID program were required to participate in the phone 
calls to receive the cost-sharing reduction. During the first phone call, a pharmacist ensured that 
the individual was on optimal therapy for COPD management, followed-up with the prescriber if 
the patient needed a new prescription, and connected the patient with a preferred pharmacy if 
desired. If the individual had their inhaler available at time of the first phone call, the pharmacist 
proceeded with additional education that included administering a COPD Assessment Test and 
adherence survey as well as coaching the individual on proper inhaler administration using the 
teach-to-goal methodology, an evidence-based technique that involves up to three iterative 
rounds of assessment and teaching. If the individual did not have their inhaler at the time of the 
first phone call, a subsequent phone call would be scheduled about 30 days later to complete the 
aforementioned activities. During the last phone call, which occurred about 60 days afterwards, a 
COPD Assessment Test was re-administered, and further coaching on proper inhaler 
administration was provided. If a beneficiary had entered, or would be likely to enter, the 
coverage gap phase of their prescription drug benefit (under which the cost-sharing reduction no 
longer applied), he or she would be counseled and referred for further assistance. Enrollees in 
2021 who completed all three phone calls received a $75 gift card. 
 
C. Randomization and Patient Eligibility 
C.1. Randomization 
Randomization occurred during the 2020 calendar year and again during the 2021 calendar year. 
In 2020, 51 MA plans with Medicare Part D prescription drug coverage (i.e., MAPD plans) 
across 16 states participated in the trial. In 2021, 138 MAPD plans across 25 states participated 
in the trial. MAPD plan participation was voluntary across Humana’s local markets, and the 
VBID benefit was offered to all eligible beneficiaries enrolled in participating plans. 
Randomization into treatment (proactive outreach) versus control occurred at the patient level. 
After applying the inclusion and exclusion eligibility criteria detailed below, randomization was 
conducted by Humana in a one-to-one allocation between treatment and control. (As discussed in 
further detail below, the primary analysis will be pooled across both the 2020 and 2021 cohorts.) 

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After randomization and as discussed above, there was proactive outreach via phone and mail to 
those beneficiaries randomized to the treatment group to enroll them in the VBID program 
consisting of reduced cost-sharing for maintenance inhalers and telephone-based medication 
management services. Beneficiaries in the control group received usual care (no proactive 
outreach). 
 
C.2. Patient Eligibility 
• 
Inclusion Criteria 
 Has COPD diagnosis 
 Receives health services and prescription drug benefits through a Humana 
Medicare Advantage plan that includes Part D coverage 
 Has at least one prior fill of a COPD maintenance inhaler in the prior 12 months 
 Not fully adherent to maintenance inhaler (PDC < 80%) in year prior to 
randomization 
• 
Exclusion Criteria 
 Enrolled in Part D Low-Income Subsidy program 
 On hospice 
 Has end-stage renal disease 
 Has mild COPD (i.e., COPD diagnosis but no maintenance inhaler fill, no 
pulmonary function tests in year prior year, and no acute care use for COPD) 
 Enrolled in Humana plan for less than 3 months 
 In the coverage gap phase of MA plan at time of assignment 
 Receives primary care at select locations of Humana subsidiaries (CenterWell or 
Conviva) 
 
D. Data, Study Sample, Outcomes, and Other Variables 
D.1. Data and Study Sample 
We will use Humana Medicare Advantage claims data for all participants from January 2019 
through December 2021. The study sample includes all MA beneficiaries in both the 2020 cohort 
and 2021 cohort who underwent randomization. 
 
D.2. Planned Outcomes 
All outcomes will be on a per-patient basis, annualized (for the utilization and spending 
outcomes), and measured using claims data for the year in which the participant was in the trial.  
1. Primary Outcome 
a. Maintenance inhaler adherence 

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i. A maintenance inhaler is defined as any inhaler with an inhaled 
corticosteroid, long-acting beta-agonist, and/or long-acting antimuscarinic 
antagonist. This list includes but is not limited to the inhalers in Table 1. 
ii. The proportion of days covered (PDC) is a common claims-based measure 
of adherence. It is calculated by dividing number of days covered by a 
prescription by the total number of days eligible for the medication. In 
constructing the measure, days covered (numerator) will be number of 
days on any maintenance inhaler (whether one of a single class, multiple 
of differing classes, or changes between inhalers), and the days eligible 
(denominator) will be number of days in the observation period. Early fills 
of the same medication will be moved to the end of the current fill period. 
In sensitivity analyses, we will ensure our results are robust to different 
versions of the PDC. The primary analysis will treat PDC as a continuous 
measure, but we will also dichotomize PDC to examine “full” adherence, 
which is defined as a PDC of 0.8 or greater. 
iii. Because PDC is a rescaled and trimmed measure of number of inhalers 
filled, we will also assess number of inhalers filled, the underlying 
variable for our primary outcome. 
 
2. Secondary Outcomes 
a. Frequency of acute moderate-to-severe exacerbations 
i. An exacerbation is defined as any acute worsening of symptoms that 
requires antibiotics or systemic steroids.  
ii. We will also assess exacerbations disaggregated by severity. Moderate 
exacerbations are those that do not result in hospitalization or death and 
therefore captures those exacerbations treated on an outpatient basis. 
Severe exacerbations are exacerbations that result in hospitalization. 
b. Number of short-acting inhaler filled 
i. A short-acting inhaler is defined as any inhaler with a short-acting beta 
agonist and/or short-acting antimuscarinic antagonist. 
c. Total spending 
i. Total spending includes both the insurer’s payments and beneficiary’s out-
of-pocket payments.  
ii. We will also examine disaggregated spending according to payer (i.e., 
beneficiary out-of-pocket payment), type of service (i.e., drug spending) 
and setting (i.e., acute care spending, where “acute care” refers to 
emergency department visits, observation stays, and inpatient 
hospitalizations). 
 
D.3. Covariates and Patient Characteristics 
The data includes information on participants’ age, sex, race, disability status, and geography. 
Using pre-randomization claims, we will also calculate or determine participants’ COPD stage, 
presence of other chronic conditions, Hierarchical Condition Category (HCC) risk score, area-
level sociodemographic characteristics, and utilization/spending prior to randomization. We 

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anticipate minimal missing data for these covariates. In the event that there are high levels of 
missingness for any key covariate (i.e., >2%), multiple imputation methods will be used. 
Race is a key variable in our analysis. The race variable is derived from the Medicare enrollment 
database and comes from self-reported data on Social Security applications. Based on power 
calculations and the reliability of identifying racial/ethnic groups in the data, we focus 
specifically on Black versus White racial disparities.  
 
E. Statistical Analysis 
E.1. Evaluation of randomization, balance, and attrition 
We will test for balance between treatment and control based upon observable baseline 
characteristics for the overall study population. These pre-randomization characteristics include 
those described in section D.3. 
Because differential attrition correlated with treatment could introduce bias into our results, we 
will also evaluate the attrition rate and assess for balance between treatment and control based 
upon both baseline characteristics for the final analytic sample (and attritors) and potential 
causes of attrition (e.g., death, disenrollment).  
 
E.4. Intent-to-treat analysis 
Our primary analytic approach is an analysis based on the intent-to-treat principle that compares 
outcomes for those who were randomized into the treatment (proactive outreach) group to those 
who were randomized into the control group, regardless of actual enrollment to receive the 
supplemental cost-sharing reduction and care coordination benefits. We will estimate the 
following linear regression model: 
𝑦𝑦𝑖𝑖= 𝛽𝛽0 + 𝛽𝛽1𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖∗𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑖𝑖+ 𝛽𝛽2𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖+ 𝛽𝛽3𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑖𝑖+ 𝛽𝛽4𝑿𝑿𝒊𝒊+ 𝛽𝛽5𝑽𝑽𝒊𝒊+ 𝛽𝛽6𝜃𝜃𝜏𝜏
+ 𝜀𝜀𝑖𝑖 
(1) 
In equation (1), 𝑦𝑦𝑖𝑖 is the adherence, utilization, or spending outcome for participant 𝑖𝑖. See section 
D.2. for a list of our primary and secondary outcomes. “𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖” is an indicator for whether 
individual 𝑖𝑖 was randomized into the treatment group. “𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑖𝑖” is an indicator for whether 
individual 𝑖𝑖 identified his/her/their race as Black. 𝑿𝑿𝒊𝒊 is a vector of covariates, specifically patient 
characteristics (sex, age, geography), which are not explicitly necessary since they should be 
unrelated to treatment status, but they may increase the precision of our estimates to the extent 
that they explain some of the variance in the outcome. 𝑽𝑽𝒊𝒊 represents the baseline value of the 
outcome 𝑦𝑦. The rationale for including baseline values in the model is to improve precision as 
well as account for potential imbalance after randomization or regression to the mean. Finally, 𝜃𝜃𝜏𝜏 
is a fixed effect for month of randomization because randomization occurred on monthly basis 
within each cohort. 

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As described in section C.1. above, randomization and treatment assignment were done at the 
level of the individual and occurred for one cohort of patients in the year 2020 and again for a 
new cohort of patients in the year 2021. We will examine cohort-specific outcomes, but our 
primary analysis will be pooled across both the 2020 and 2021 cohorts. To do so, we will include 
a cohort-specific fixed effect in equation (1) and saturate the model with corresponding 
interaction effects such that our parameter of interest is estimated within a single regression 
model. 
𝛽𝛽1 is the coefficient on the interaction between the “𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖” and “𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑖𝑖” indicator 
variables, and it is our main coefficient of interest. It represents the additional effect of being in 
the treatment group on Black patients beyond the effect of being in the treatment group on White 
patients. In addition to our primary specification (1), which we expect to be more efficient than 
individual regressions by subpopulation, we will also estimate the overall effect, regardless of 
race (i.e., pooled), and separately by race in a model similar to (1) but without the race indicator 
or interaction term. All observations will be weighted by number of months spent in the study 
after randomization. Standard errors will be adjusted for heteroskedasticity. 
 
E.5. Local-average-treatment-effect analysis 
In addition to our primary intent-to-treat analysis, we will also conduct a local-average-
treatment-effect analysis, also known as the average causal effect on the compliers, pooled and 
separately by race. While the intent-to-treat analysis provides an estimate of the effect of being 
randomized into the treatment (proactive outreach) group on the outcomes, the local-average-
treatment-effect analysis provides an estimate of the VBID program (i.e., reduced cost-sharing 
for maintenance inhalers and telephone-based medication management services) on the 
outcomes.  
For this analysis, we use randomization into the treatment group as an instrument for receiving 
the supplemental benefits and estimate the following two-stage least squares (2SLS) model: 
𝑦𝑦𝑖𝑖𝑖𝑖= 𝜋𝜋0 + 𝜋𝜋1𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖+ 𝜋𝜋2𝑿𝑿𝒊𝒊𝒊𝒊+ 𝜋𝜋3𝑽𝑽𝒊𝒊𝒊𝒊+ 𝜋𝜋4𝜃𝜃𝑡𝑡+ 𝑣𝑣𝑖𝑖𝑖𝑖 
(2) 
where 𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖 in equation (2) is estimated via the following first-stage regression: 
𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖= 𝛿𝛿0 + 𝛿𝛿1𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖𝑖𝑖+ 𝛿𝛿2𝑿𝑿𝒊𝒊𝒊𝒊+ 𝛿𝛿3𝑽𝑽𝒊𝒊𝒊𝒊+ 𝛿𝛿4𝜃𝜃𝑡𝑡+ 𝜇𝜇𝑖𝑖𝑖𝑖 
(3) 
In equation (2) and (3), 𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖 is an indicator variable for whether after being randomized to the 
treatment group, the patient subsequently enrolled to receive cost-sharing reduction (CSR) for 
maintenance inhalers and care management calls. 𝜋𝜋1 is the local average treatment effect 
(LATE) of receiving the cost-sharing reduction (CSR) for maintenance inhalers and care 
management calls.  
 
E.4. Alternative specifications and sensitivity analyses 

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Our primary specification includes baseline values of the outcome in the model to improve 
power as well as account for regression to the mean and any chance imbalance between the study 
arms after randomization. As described in section E.1., we will compare covariates between the 
treatment and control groups, and as a sensitivity check, we will exclude baseline values of the 
outcome in the model. 
To ensure our estimates are robust to method of estimation, we will also estimate generalized 
linear models assuming a negative binomial distribution for the count utilization outcomes, a 
generalized linear model with a Bournoulli distribution and logit link function for the binary 
PDC outcome, and generalized linear models with a gamma distribution and log link for the 
continuous adherence and spending outcomes. In a final robustness check, we will Winsorize the 
spending measure to ensure that our estimates are not sensitive to outliers. 
 
E.5. Statistical significance and adjustments for multiple comparisons 
Statistical significance was defined as two-sided P<0.05 for the primary outcome. Because we 
have one prespecified primary outcome and a single prespecified coefficient of interest from 
estimating equation (1), we will not make any adjustments for multiple inference. For our 
secondary outcomes, we will the Benjamini-Hochberg procedure to calculate adjusted p-values 
that account for testing of multiple outcomes. 
 

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F. Tables 
Table 1. Maintenance Inhalers Included for Cost-Sharing Reduction 
Advair Diskus 100 mcg-50 mcg/dose powder for inhalation 
Advair Diskus 250 mcg-50 mcg/dose powder for inhalation 
Advair Diskus 500 mcg-50 mcg/dose powder for inhalation 
Advair HFA 115 mcg-21 mcg/actuation aerosol inhaler 
Advair HFA 230 mcg-21 mcg/actuation aerosol inhaler 
Advair HFA 45 mcg-21 mcg/actuation aerosol inhaler 
Arnuity Ellipta 100 mcg/actuation powder for inhalation 
Arnuity Ellipta 200 mcg/actuation powder for inhalation 
Arnuity Ellipta 50 mcg/actuation powder for inhalation 
Breo Ellipta 100 mcg-25 mcg/dose powder for inhalation 
Breo Ellipta 200 mcg-25 mcg/dose powder for inhalation 
Breztri Aerosphere 160 mcg-9mcg-4.8mcg/actuation HFA aerosol inhaler 
Flovent Diskus 100 mcg/actuation powder for inhalation 
Flovent Diskus 250 mcg/actuation powder for inhalation 
Flovent Diskus 50 mcg/actuation powder for inhalation 
Flovent HFA 110 mcg/actuation aerosol inhaler 
Flovent HFA 220 mcg/actuation aerosol inhaler 
Flovent HFA 44 mcg/actuation aerosol inhaler 
Fluticasone-Salmeterol 100-50 
Fluticasone-Salmeterol 113-14 
Fluticasone-Salmeterol 232-14 
Fluticasone-Salmeterol 250-50 
Fluticasone-Salmeterol 500-50 
Fluticasone-Salmeterol 55-14 
Spiriva Respimat 1.25 mcg/actuation solution for inhalation 
Spiriva Respimat 2.5 mcg/actuation solution for inhalation  
Spiriva with HandiHaler 18 mcg and inhalation capsules 
Stiolto Respimat 2.5 mcg-2.5 mcg/actuation solution for inhalation 
Striverdi Respimat 2.5 mcg/actuation solution for inhalation  
Symbicort 160 mcg-4.5 mcg/actuation HFA aerosol inhaler  
Symbicort 80 mcg-4.5 mcg/actuation HFA aerosol inhaler 
Trelegy Ellipta 100 mcg-62.5 mcg-25 mcg powder for inhalation 
Trelegy Ellipta 200 mcg-62.5 mcg-25 mcg powder for inhalation 
Wixela Inhub 100 mcg-50 mcg/dose powder for inhalation  
Wixela Inhub 250 mcg-50 mcg/dose powder for inhalation   
Wixela Inhub 500 mcg-50 mcg/dose powder for inhalation