`
`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication
`Adherence Among Patients with Type 2 Diabetes
`
`Wendy S. Bibeau, PhD, MEd; Haoda Fu, PhD; April D. Taylor, MSN, CNS, BC-ADM;
`and Anita Y.M. Kwan, MSc
`
`ABSTRACT
`BACKGROUND: Medication adherence is pivotal for the successful treat-
`ment of diabetes. However, medication adherence remains a major con-
`cern, as nonadherence is associated with poor health outcomes. Studies
`have indicated that increasing patients’ share of medication costs signifi-
`cantly reduces adherence. Little is known about a potential out-of-pocket
`(OOP) cost threshold where substantial reduction in adherence may occur.
`OBJECTIVE: To examine the impact of diabetes OOP pharmacy costs on
`antihyperglycemic medication adherence and identify the potential thresh-
`old at which significant reduction in adherence may occur among patients
`with type 2 diabetes mellitus (T2DM).
`METHODS: This was an observational, retrospective cohort study using
`longitudinal U.S. pharmacy and medical claims data from the IMS Health
`Medical Claims (Dx) database. Patients with T2DM who initiated therapy
`with a branded antihyperglycemic medication during the index period
`(January 1, 2011, to December 31, 2011) and had 3 years of follow-up data
`were included. The primary outcome was adherence to antihyperglycemic
`medications, measured as the number of days covered. Propensity scores
`were calculated using baseline sociodemographic and clinical characteris-
`tics to control for potential confounding factors. Four strata were created
`based on mean propensity scores. Across each stratum, patients were
`assigned to 5 diabetes OOP pharmacy (including generics) cost levels:
`$0-$10, $11-$40, $41-$50, $51-$75, and > $75. Multivariate regression
`models were used to estimate association of diabetes OOP pharmacy costs
`and adherence for each stratum. Sensitivity analyses were conducted to
`assess the impact of total OOP pharmacy costs and index drug category
`OOP costs on adherence.
`RESULTS: A total of 15,416 patients were assessed. Across each stratum in
`the diabetes OOP pharmacy cost analysis group, mean patient age ranged
`from 52.3 to 56.1 years, mean number of antihyperglycemic medication
`classes ranged from 1.5 to 3.2, and mean household income ranged from
`$60,763 to $79,373. Most patients used a commercial plan (55%-85%).
`The propensity-stratified multivariate regression model revealed an overall
`negative relationship between diabetes OOP pharmacy costs and adher-
`ence across several OOP cost levels. Diabetes OOP pharmacy cost level
`$51-$75 appeared as the threshold at which adherence reduced signifi-
`cantly (77-78 fewer days of coverage over 3 years of follow-up; P < 0.05)
`when compared with the lowest OOP costs ($0-$10) across all strata.
`Adherence reduced further (99-145 fewer days of coverage; P < 0.0001) for
`the higher diabetes OOP pharmacy cost levels (> $75) when compared with
`the lowest OOP cost levels. Sensitivity analyses with total OOP pharmacy
`costs and index drug category OOP costs revealed negative association
`with adherence across all strata.
`CONCLUSIONS: Diabetes OOP pharmacy cost was negatively associated
`with patient adherence, and a potential OOP cost threshold ($51-$75) was
`identified at which adherence reduced significantly. The study findings may
`be beneficial in informing the design of health care plans to achieve optimal
`adherence and improve disease management in patients with T2DM.
`
`J Manag Care Spec Pharm. 2016;22(11):1338-47
`
`Copyright © 2016, Academy of Managed Care Pharmacy. All rights reserved.
`
`What is already known about this subject
`
`• Adherence to therapy is a critical component in the successful
`management of diabetes. However, studies indicate that less than
`50% of patients achieve glycemic goals, which may be attribut-
`able to low medication adherence in patients with type 2 diabetes
`mellitus (TD2M).
`• Medication nonadherence has been reported to lead to poor
`clinical outcomes, high resource utilization, and increased costs
`in patients with diabetes. Out-of-pocket (OOP) costs have been
`shown to be negatively associated with medication adherence in
`patients with diabetes.
`• New strategies that shift costs to the patient in order to drive
`patient awareness about cost of care are, in part, responsible for
`the increase in patient OOP costs. However, studies suggest that
`switching to a health care plan that includes modest drug copays
`may not reduce medication use or lead to reduced adherence for
`chronic diseases.
`
`What this study adds
`
`• This study provides contemporary evidence that antihyperglyce-
`mic medication adherence differs by OOP cost levels in patients
`with T2DM.
`• The study findings indicate that there is a threshold at which
`OOP costs become a substantial barrier to attaining antihyper-
`glycemic medication adherence. Diabetes OOP pharmacy cost
`level $51-$75 was identified as the potential threshold at which
`significant reduction in adherence was observed. Sensitivity
`analysis revealed a higher threshold (OOP cost levels $91-$150)
`for total OOP pharmacy costs.
`• These results can be used to inform plan designs and tier structure
`to ensure copays do not negatively and substantially affect medica-
`tion adherence and thereby help to attain optimal adherence and
`reduce overall health care expenditures in patients with diabetes.
`
`Diabetes mellitus is a complex, multifactorial disease
`
`that affects approximately 29 million people in the
`United States.1 Diabetes and associated complications
`are expected to be the seventh leading cause of death by 2030.2
`Type 2 diabetes mellitus (T2DM) is the most common type
`and accounts for 90%-95% of all diagnosed cases.1 Lifestyle
`changes are recommended as the first-line therapy for patients
`
`1338 Journal of Managed Care & Specialty Pharmacy
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`JMCP November 2016 Vol. 22, No. 11 www.jmcp.org
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`with T2DM, and oral antihyperglycemic medications, with or
`without insulin, are used if adequate glycemic control is not
`achieved or maintained by lifestyle changes.3 A critical com-
`ponent in the successful management of diabetes is adherence
`to therapy.4 However, studies indicate that less than 50% of
`patients achieve glycemic goals, which may be attributable, in
`part, to low adherence to therapies.5
`Medication adherence is a major concern to providers,
`health care systems, and payers due to the increasing evidence
`that medication nonadherence is pervasive6 and associated
`with adverse health outcomes and high resource utilization
`(e.g., hospitalizations, emergency department [ED] visits,
`etc.) and costs.7 Medication nonadherence is responsible for
`substantial medication-related hospital admissions, ranging
`from 33% to 69%,8 and the suboptimal rates of medication
`adherence9 are estimated to cost the U.S. health care system
`between $100 billion and $300 billion annually.10 The medical
`cost burden of the least-adherent patients with T2DM ($21,421)
`is nearly 3 times higher than the most-adherent patients with
`T2DM ($7,692).11
` Conversely, evidence suggests that individuals with better
`medication adherence have better health outcomes and lower
`rates of health care resource utilization. It has been estimated
`that improved adherence to antihyperglycemic medications
`could avoid 699,000 ED visits and 341,000 hospitalizations
`annually.12 Also, it is estimated that every additional dollar
`spent on adhering to a prescribed medication would reduce
`total health care costs by $6.7 in patients with diabetes,13 and
`improved adherence could potentially lead to annual health
`care savings of up to $8.3 billion in the United States.12
`With continual increases in health care spending,14 strat-
`egies are being used to curb the overuse of unnecessary
`medications and shift costs to the patient, such as increase in
`patient copayments and coinsurance, increase in formulary
`listing restrictions, and mandatory substitution of branded
`products with less expensive generics.15 A 2015 annual census
`of U.S. health insurance companies has shown that enroll-
`ment in health savings account/high-deductible health plans
`has almost doubled in the last 5 years.16 These strategies are
`partly the reason for the increase in patient OOP costs, which
`increased by 1.3% to $329.8 billion in 2014 or 11% of total
`national health expenditures in 2014.14 Unfortunately, these
`strategies to reduce medication use may be counterproduc-
`tive, as studies have indicated that increasing patient share of
`medication costs is significantly associated with a decrease in
`adherence.17
`However, a study has reported that switching to a health care
`plan that includes modest drug copays may not reduce medica-
`tion use or lead to reduced adherence for chronic diseases.18
`Therefore, it is essential for managed care decision makers to
`identify the point at which additional OOP costs adversely affect
`medication adherence.15 Although a few studies have assessed
`
`the impact of patient copay levels on adherence in patients with
`T2DM,19-21 the threshold of OOP pharmacy costs that leads to
`significant reduction in adherence remains unclear. Also, the
`increasing trend of enrollment in high-deductible health plans
`in recent years indicates a need for ongoing research on the
`association of OOP costs and adherence.
`The objective of this study was to examine the impact of
`diabetes OOP pharmacy costs on adherence and identify the
`threshold of diabetes OOP pharmacy costs at which copays
`become a substantial barrier to attaining antihyperglycemic
`medication adherence, regardless of income and sociodemo-
`graphic and clinical characteristics.
`
`■■ Methods
`Data Source
`This study used longitudinal pharmacy and medical claims
`data from the IMS/Amundsen database. The IMS Health
`Medical Claims (Dx) database is a longitudinal dataset that
`captures information about patients’ medical diagnoses, pro-
`cedures, laboratory investigations, and other related medical
`claims activity from full-time office-based physicians across
`the United States.22 This dataset was used to identify other
`diagnosed comorbidities for the cohort of patients with diabe-
`tes and subsequently assign the appropriate number of points
`for the chronic disease score (CDS)23 and adapted diabetes
`complications severity index (aDCSI).24
`In addition, data from the formulary impact analyzer (FIA)
`were used to identify OOP costs for each claim. The FIA is a
`transactional claim dataset derived from the interaction and
`information passing between pharmacy outlets and payer adju-
`dication processes. The FIA is sourced from retail and mail-
`order pharmacies and is a nonprojected dataset (i.e., data are
`not projected up to estimate the total market, thereby allowing
`patient longitudinal analyses to be conducted) representing
`approximately 50% of claim volume for the diabetes market.
`Each claim was mapped to a de-identified patient in the IMS
`system using a proprietary and patented approach, enabling
`these FIA patients to be linked to the IMS system. Finally, the
`claims data were cross-matched with sociodemographic vari-
`ables through partnership with Experian, the global informa-
`tion services company, and the impact of these variables on the
`outcomes of interest was evaluated.
`
`Study Design
`This study was an observational, retrospective cohort analysis
`of patients with T2DM aged 18-85 years who initiated 1 or
`more branded antihyperglycemic products within selected
`Uniform System of Classification categories (Appendix A, avail-
`able in online article) during the index period (January 1, 2011,
`to December 31, 2011). Patients should have had (a) at least
`2 claims with a T2DM diagnosis (International Classification of
`Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] 250.x0,
`
`www.jmcp.org Vol. 22, No. 11 November 2016
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`JMCP Journal of Managed Care & Specialty Pharmacy 1339
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`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication Adherence Among Patients with Type 2 Diabetes
`
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`250.x2) on 2 dates during the pre-index period (6 months
`before the index date), (b) ≥ 6 months’ continuous eligibility
`in the pre-index period, and (c) ≥ 12 months’ continuous eligi-
`bility during the post-index period (3-year follow-up period).
`Patients with claims for a type 1 diabetes mellitus (ICD-9-CM
`250.x1, 250.x3) or gestational diabetes (ICD-9-CM 648.8x)
`diagnosis during the pre-index period were excluded.
`
`Measures
`Demographic characteristics were summarized for the target
`population, including age and sex at index period, and income,
`level of education, geographic location, marital status, and
`insurance plan type (commercial, Medicare Part D) at index
`and follow-up periods. Clinical variables such as CDS (score
`ranging from 0 to 36, with higher scores indicating poorer
`outcomes),23 aDCSI (score ranging from 0 to 13, with higher
`scores indicating increased risk of complications),24 and tar-
`geted comorbidities of interest were captured at index period
`(Appendix B, available in online article).
`The primary outcome measure was antihyperglycemic med-
`ication adherence, which was measured by the number of days
`covered during the follow-up period from January 1, 2012, to
`December 31, 2014. The number of days covered was defined
`as the number of days in the follow-up period during which
`the index medication was determined to be in hand based on
`the pharmacy claim fill date plus days supply. The follow-up
`period was 3 years for all patients.
`The first-year mode copay was used to determine patient
`OOP costs for each drug category. Diabetes OOP pharmacy
`costs were calculated by adding all first-year mode copay
`amounts across all diabetes medications including generics. On
`the basis of the data retrieved and the most logical or frequently
`observed cut points, patients were assigned to 5 diabetes OOP
`pharmacy cost levels based on monthly OOP costs: $0-$10,
`$11-$40, $41-$50, $51-$75, and > $75. Patients starting therapy
`in multiple index drug categories were assigned to cost cohorts
`in all the drug categories in which they initiated therapy during
`the index period, but the overall OOP costs were calculated at
`the patient level. The impact of diabetes OOP pharmacy costs
`on adherence was measured for patients for the OOP cost levels
`identified. For all patients, adherence as a function of diabetes
`OOP pharmacy costs was observed at the patient level, and
`patients were tracked over the follow-up period to determine
`the number of days covered.
`
`observed point of inflection of about $35.25 Confounders were
`selected based on Pearson’s correlation, and those with the
`highest coefficients were included. Confounders included age,
`income, number of diabetes medication classes, total num-
`ber of diabetes medications, CDS, number of all medication
`classes, total number of all medications, marital status, and
`type of insurance.
`Propensity scores were calculated to estimate the probabil-
`ity of OOP medication costs > $35 using baseline sociodemo-
`graphic and clinical characteristics. To minimize the impact
`of confounding variables, patients were divided into 4 strata
`based on Tukey’s Five Number Summary. Matching was not
`done, and propensity score stratification was used for adjust-
`ment in the analysis. A multivariate basic regression model
`was conducted to estimate the association of diabetes OOP
`pharmacy costs and antihyperglycemic medication adherence
`for each stratum. Diabetes OOP pharmacy costs and the strati-
`fications resulting from the propensity stratification were the
`independent variables, whereas total number of days covered
`for diabetes medications during the 3-year follow-up was the
`dependent variable in the multivariate analysis.
`Variables missing on more than 10% of the claims transac-
`tions were not included in the analyses. However, if a variable
`was considered crucial to an analysis and the volume became
`an issue per the rule above, claims with populated fields were
`included in the analysis.
`
`Sensitivity Analysis
`Patients with diabetes are at a high risk of coexisting medical
`conditions and may require multiple medications to manage
`not only hyperglycemia but also associated comorbidities, such
`as dyslipidemia, hypertension, and depression.26 Therefore, a
`sensitivity analysis was conducted to assess the impact of total
`OOP pharmacy costs on adherence. The total OOP pharmacy
`costs were calculated by adding first-year mode copay amounts
`across all therapy area medications, including generics. Patients
`were assigned to 6 total OOP pharmacy cost cohorts based on
`monthly OOP costs: $0-$30, $31-$60, $61-$90, $91-$150,
`$151-$200, and > $200. In addition, the association of the
`index diabetes medication (only 1 antihyperglycemic medica-
`tion) OOP costs and adherence was also assessed across several
`monthly OOP cost levels ($0-$10, $11-$40, $41-$50, $51-$75,
`and > $75) in the sensitivity analysis to account for the effect of
`patients’ characteristics at index period.
`
`Statistical Analysis
`The association of diabetes OOP pharmacy costs and adher-
`ence was assessed using a propensity-stratified combined
`impact model. A logistic regression analysis was conducted
`wherein the dependent variable was OOP medication cost
`> $35; the dependent variable, OOP medication cost > $35, was
`identified based on a generally linear trend with a commonly
`
`■■ Results
`At the beginning of the study, more than 6.5 million patients
`with diabetes were identified. After applying the inclusion and
`exclusion criteria, the majority of the patients were excluded
`because they had not initiated an index drug category treat-
`ment during the index period. On average, the index drug
`categories selected were more expensive than other agents such
`
`1340 Journal of Managed Care & Specialty Pharmacy
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`JMCP November 2016 Vol. 22, No. 11 www.jmcp.org
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`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication Adherence Among Patients with Type 2 Diabetes
`
`Novo Nordisk Exhibit 2521
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`IPR2023-00724
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`FIGURE 1
`
`Patient Selection Diagram
`
`Diabetes patients identified from the database in 2011
`N = 6,581,414
`
`Eligible study population for non-Experian metrics
`n = 116,975
`
`Complete eligible study population
`n = 56,298
`
`Final study sample
`n = 15,416
`
`T2DM = type 2 diabetes mellitus.
`
`Excluded:
`• Patients without branded index drug therapy initiation in 2011,
`n = 6,000,000
`• Patients without look-forward eligibility, n = 50,956
`• Patients without medical claims eligibility, n = 195,781
`• Patients without T2DM diagnosis, n = 87,979
`• Patients without reliable copay information, n = 120,372
`• Patients wihout a clear copay mode, n = 9,351
`
`Excluded:
`• Patients without Experian eligibility, n = 60,677
`
`Excluded:
`• Patients without age and/or sex information, n = 2,002
`• Patients without Experian information, namely marriage, income,
`or education, n = 38,880
`
`as metformin and sulfonylurea that were not included as index
`drug categories, but patients had different insurance coverages
`that allowed some patients to fill the selected agents at little
`to no cost, thus allowing a variety of costs to be included in
`the assessment of adherence. Approximately 116,975 patients
`with therapy initiation in 2011 and pharmacy claims data
`for the entire 3-year study period were eligible for the study.
`Considering patients whose cost information and socioeco-
`nomic data were available, the final sample size for each model
`was 15,416 patients (Figure 1).
`
`Baseline Characteristics
`The categorization of the 4 strata based on the probability of
`having a copay of > $35 is outlined in Table 1. Stratum 1 had
`the lowest probability of high OOP costs, whereas stratum 4
`had the highest probability of high OOP costs.
`At the index period, although significant differences were
`observed for some covariates, overall the covariates were
`balanced across the 2 OOP cost groups (> $35 and ≤ $35). The
`
`TABLE 1
`
`Copay Stratification Based on the
`Probability of OOP Medication
`Costs > $35
`
`Stratum
`1
`2
`3
`4
`OOP = out-of-pocket.
`
`N
`3,854
`3,854
`3,854
`3,854
`
`Propensity Scores (%)
`Average
`Minimum
`Maximum
` 3.0
` 0.1
` 5.4
` 7.8
` 5.4
`10.1
`13.5
`10.1
`18.1
`29.5
`18.1
`90.0
`
`number of diabetes medications and diabetes therapy classes
`used at index period were similar across all 4 strata (Table 2A).
`Across each stratum, the mean patient age ranged from 46.6 to
`61.6 years, mean CDS ranged from 5.4 to 7.0, mean number of
`diabetes medication classes ranged from 1.9 to 2.4, and mean
`household income ranged from $62,893 to $77,028. Most
`patients were married (mean range, 62%-98%) and some used
`
`www.jmcp.org Vol. 22, No. 11 November 2016
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`JMCP Journal of Managed Care & Specialty Pharmacy 1341
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`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication Adherence Among Patients with Type 2 Diabetes
`
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`46.6 ± 15.4a
`64,377 ± 48,174
`2.4 ± 1.1a
`2.8 ± 1.1
`7.0 ± 3.2a
`9.1 ± 3.9a
`9.6 ± 4.0a
`62
`72
` 0
`28
`
`54.1 ± 12.1
`75,941 ± 47,609
`2.2 ± 0.9
` 2.5 ± 1.0a
` 6.3 ± 2.9a
` 7.6 ± 3.4a
` 8.1 ± 3.4a
`96
`98
` 2a
` 0
`
`57.3 ± 12.2b
`77,028 ± 48,897
`1.9 ± 0.9
`2.1 ± 1.0
`5.4 ± 2.5
`5.7 ± 3.0
`6.2 ± 3.1
`95
`94
` 5a
` 0
`
`Stratum 4
`N = 3,854
`
`61.6 ± 13.0
`62,893 ± 45,947a
`1.9 ± 0.9a
`2.1 ± 1.0a
`6.2 ± 3.0a
`6.7 ± 3.8a
`7.1 ± 3.9a
`98
` 30a
` 60
` 0
`
`TABLE 2
`
`Demographic and Clinical Characteristics
`Stratum 1
`N = 3,854
`
`Stratum 2
`N = 3,854
`
`Stratum 3
`N = 3,854
`
`Confounders
`A. Characteristics at Index Period
`Age (years), mean ± SD
`Income, $, mean ± SD
`Diabetes medication class,c mean ± SD
`Diabetes therapies, mean ± SD
`CDS, mean ± SD
`Total medication class,d mean ± SD
`Total therapies, mean ± SD
`Married, %
`Commercial, %
`Part D, %
`Medicaid, %
`B. Characteristics of the Diabetes OOP Pharmacy Costs Group
`55.6 ± 15.2b
`55.5 ± 12.4
`56.1 ± 14.0
`52.3 ± 15.2
`Age (years), mean ± SD
`72,312 ± 48,630b
`67,787 ± 46,504b
`79,373 ± 51,444
`60,763 ± 43,577
`Income, $, mean ± SD
`1.5 ± 0.8a
`Diabetes medication class,c mean ± SD
`3.2 ± 0.7
`2.2 ± 0.5
`1.6 ± 0.6
`1.8 ± 0.9a
`3.4 ± 0.9
`2.4 ± 0.7
`1.8 ± 0.8
`Diabetes therapies, mean ± SD
`6.1 ± 2.7b
`6.3 ± 2.9b
`6.5 ± 3.2a
`6.0 ± 3.0
`CDS, mean ± SD
`8.3 ± 3.5a
`7.5 ± 3.5a
`6.5 ± 3.5b
`6.8 ± 4.3a
`Total medication class,d mean ± SD
`8.8 ± 3.6a
`7.9 ± 3.6a
`7.4 ± 4.3a
`6.9 ± 3.6
`Total therapies, mean ± SD
`94
`92
`89
`76
`Married, %
` 78a
` 76b
`85
`55
`Commercial, %
` 9a
` 18
`23
`17
`Part D, %
` 0
` 0
` 0
`28
`Medicaid, %
`Note: Patients were divided into 4 strata based on Tukey’s Five Number Summary to minimize the impact of confounding variables. P values indicate comparison of ≤ $35
`OOP cost group versus > $35 OOP cost group.
`aP<0.0001.
`bP<0.05.
`cDiabetes medication class is defined as the number of diabetes drug categories (including injectables) used by a patient simultaneously during the index period.
`dTotal medication class is defined as the number of all therapy area drug categories used by a patient simultaneously during the index period.
`CDS = chronic disease score; OOP = out-of-pocket; SD = standard deviation.
`
`a commercial plan (mean range, 30%-98%). Stratum 1 had the
`lowest mean age (46.6 years) and highest CDS (7.0) and was
`the only group with patients covered by a Medicaid plan (28%).
`Stratum 2 had the highest proportion of patients in a commer-
`cial plan (98%). Stratum 3 had the highest mean household
`income ($77,028), lowest CDS (5.4), and second-highest pro-
`portion of patients in a commercial plan (94%). Stratum 4 had
`the lowest mean household income ($62,893) and the highest
`proportion of patients in a Medicare Part D plan (60%).
`Similar to the index period, the covariates were balanced
`across the 2 OOP cost groups (> $35 and ≤ $35) for the diabetes
`OOP pharmacy cost analysis group, although significant differ-
`ences were observed for some covariates. The mean patient age
`ranged from 52.3 to 56.1 years, mean CDS ranged from 6.0 to
`6.5, mean number of diabetes medication classes ranged from
`1.5 to 3.2, and mean household income ranged from $60,763
`to $79,373 (Table 2B). Most patients were married (mean range,
`76%-94%) and used a commercial plan (mean range, 55%-85%).
`Stratum 1 had the lowest mean household income ($60,763) and
`
`was the only group with patients covered by a Medicaid plan
`(28%). Stratum 2 reported the highest proportion of patients in
`a Medicare Part D plan (23%). Stratum 3 had the second-highest
`number of diabetes medication classes (2.2) and second-
`highest proportion of patients in a commercial plan (78%).
`Stratum 4 had the highest mean household income ($79,373),
`highest total number of diabetes medication classes (3.2), and
`highest proportion of patients in a commercial plan (85%).
`
`OOP Pharmacy Costs and Adherence
`In the unadjusted analysis for the overall population, antihy-
`perglycemic medication adherence decreased as the diabetes
`OOP pharmacy costs increased. For patients on basal insulin,
`a continuous decrease in antihyperglycemic medication adher-
`ence was observed for diabetes OOP pharmacy cost levels ≥ $75,
`with patients in the diabetes OOP pharmacy cost levels
`$75-$99.99 reporting 464 days of antihyperglycemic medica-
`tion coverage compared with 508 days in the lowest diabetes
`OOP pharmacy cost levels ($0-$9.99). Similarly, patients on
`
`1342 Journal of Managed Care & Specialty Pharmacy
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`JMCP November 2016 Vol. 22, No. 11 www.jmcp.org
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`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication Adherence Among Patients with Type 2 Diabetes
`
`Novo Nordisk Exhibit 2521
`Mylan Pharms. Inc. v. Novo Nordisk A/S
`IPR2023-00724
`Page 00005
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`FIGURE 2
`
`Association of Diabetes OOP Pharmacy Costs and Antihyperglycemic Medication Adherence
`
`430.2b
`
`452.1b
`469.5b
`
`536.8
`529.2
`
`398.8b
`
`450.2b
`
`488.3a
`
`558.2a
`528.4
`
`383.4b
`
`416.8b
`
`467.9
`
`524.1b
`
`493.7
`
`344.3b
`
`412.5a
`
`489.1
`
`462.9
`
`489.2
`
`Number of Days Covered
`
`Stratum 1
`
`Stratum 2
`
`Stratum 3
`
`Stratum 4
`
`$0-$10
`
`$11-$40
`
`$41-$50
`
`$51-$75
`
`> $75
`
`Note: Patients were divided into 4 strata based on Tukey’s Five Number Summary to minimize the impact of confounding variables. P values indicate comparison with
`diabetes OOP pharmacy cost levels $0-$10 in respective strata.
`aP < 0.05.
`bP < 0.0001.
`OOP = out-of-pocket.
`
`rapid-acting insulin experienced a steady decrease in antihyper-
`glycemic medication adherence for diabetes OOP pharmacy cost
`levels ≥ $40, with patients in the diabetes OOP pharmacy
`cost levels $40-$49.99 reporting 401 days of coverage com-
`pared with 442 days in the lowest diabetes OOP pharmacy
`cost levels. A similar trend was observed for glucagon-like pep-
`tide-1 receptor agonists, with a steady reduction in adherence
`observed for diabetes OOP pharmacy cost levels $30-$39.99
`(422 days of coverage) and above. For dipeptidyl peptidase-4
`inhibitors, adherence decreased steadily up to diabetes OOP
`pharmacy cost levels $100-$124.99 (427 days of coverage) and
`a slight increase in adherence was observed for diabetes OOP
`pharmacy cost levels ≥ $125 (433 days of coverage).
`The propensity-stratified multivariate regression model
`revealed an overall negative relationship between diabetes OOP
`pharmacy costs and antihyperglycemic medication adherence
`across several OOP cost levels.27 The likelihood of adherence was
`significantly decreased for patients with diabetes OOP pharmacy
`costs > $50 (P < 0.05) compared with those with the lowest dia-
`betes OOP pharmacy cost levels ($0-$10) in each of the 4 strata
`(Figure 2). Diabetes OOP pharmacy cost levels $51-$75 appeared
`to be the threshold at which significant reduction in adherence
`was observed across all strata, with patients experiencing 77-78
`fewer days of coverage (P < 0.05) when compared with the
`
`lowest diabetes OOP pharmacy cost levels. The adherence levels
`reduced further for the higher diabetes OOP pharmacy cost lev-
`els, and patients with the highest diabetes OOP pharmacy costs
`(> $75) had 99-145 fewer days of coverage (P < 0.0001) compared
`with those with the lowest OOP cost levels.
`Results from the sensitivity analysis revealed a negative
`association between total OOP pharmacy costs and antihyper-
`glycemic medication adherence across several OOP cost levels
`(Figure 3). Adherence dropped significantly as OOP costs
`increased, especially for patients with total OOP pharmacy
`cost levels > $90 (P < 0.05) compared with those with the lowest
`OOP costs ($0-$30). Total OOP pharmacy cost levels $91-$150
`appeared to be the threshold at which adherence reduced sig-
`nificantly across each stratum, and patients experienced 51-83
`fewer days of coverage (P < 0.0001) when compared with the
`lowest total OOP pharmacy cost levels.
`Similar findings were reported for index drug category OOP
`costs. Across each stratum, patients with higher index drug
`category OOP costs were less adherent to antihyperglycemic
`medication than patients with lower OOP costs. For strata
`2 and 4, the index drug category OOP cost levels $11-$40
`appeared as the threshold at which antihyperglycemic
`medication adherence reduced significantly (P < 0.0001;
`compared with OOP cost levels $0-$10); whereas the threshold
`
`www.jmcp.org Vol. 22, No. 11 November 2016
`
`JMCP Journal of Managed Care & Specialty Pharmacy 1343
`
`Impact of Out-of-Pocket Pharmacy Costs on Branded Medication Adherence Among Patients with Type 2 Diabetes
`
`Novo Nordisk Exhibit 2521
`Mylan Pharms. Inc. v. Novo Nordisk A/S
`IPR2023-00724
`Page 00006
`
`
`
`FIGURE 3
`
`Association of Total OOP Pharmacy Costs and Antihyperglycemic Medication Adherence
`
`472.0b
`
`501.0a
`
`475.4b
`
`519.3
`
`542.3
`526.7
`
`461.7b
`471.3b
`478.1b
`497.5a
`
`523.4
`535.7
`
`360.5b
`
`427.7a
`432.4b
`
`463.2a
`477.7
`494.2
`
`327.9a
`342.0a
`354.1b
`
`405.6a
`418.9
`437.0
`
`Number of Days Covered
`
`Stratum 1
`
`Stratum 2
`
`Stratum 3
`
`Stratum 4
`
`$0-$30
`
`$31-$60
`
`$61-$90
`
`$91-$150
`
`$151-$200
`
`> $200
`
`Note: Patients were divided into 4 strata based on Tukey’s Five Number Summary to minimize the impact of confounding variables. P values indicate comparison with total
`OOP pharmacy cost levels $0-$10 in respective strata.
`aP < 0.05.
`bP < 0.0001.
`OOP = out-of-pocket.
`
`was > $75 and $51-$75 for stratum 1 and stratum 3, respectively
`(P < 0.05, for each comparison).
`
`■■ Discussion
`Adherence was consistently and negatively associated with
`OOP pharmacy costs in patients with T2DM. Within each
`stratification, the 3-year adherence decreased as OOP phar-
`macy costs increased. Similar findings have been observed in a
`literature review assessing the association of patient cost shar-
`ing and adherence, wherein 85% of articles reported that an
`increase in patients’ medication cost sharing was significantly
`associated with a decrease in adherence.15
`While not completely linear, adherence dropped with each
`level of OOP pharmacy cost increase, adjusting for age, income
`level, CDS, medication burden, and sociodemographic and
`clinical characteristics. The negative association of the level of
`OOP costs and adherence was also reported in earlier studies
`conducted in patients with T2DM as well as for other chronic
`conditions.19-21 A U.S. study demonstrated that an increase in
`cost sharing by $10 resulted in a 6.2% decrease in antihyper-
`glycemic medication adherence, and nonadherence led to an
`increase in diabetes-related complications and subsequent
`costs.20 Put into context, for every $10 increase in copay, a
`patient on oral antihyperglycemic medication therapy was
`reported to be 26% more likely to become nonadherent.19
`
`On the contrary, a reduction in copayment for antihypergly-
`cemic medications from $15.3 to $10.1 was reported to increase
`the probability of adherence from 75.3% to 82.6%.21 These
`findings indicate that increases in the patients’ share of copay
`by health care plans may indirectly lead to poor outcomes and
`increases in health care costs due to nonadherence.
`It is apparent from this study that there is a threshold at
`which OOP pharmacy costs become a barrier to antihypergly-
`cemic medication adherence. At index period, the threshold
`for index drug category OOP costs appeared to differ widely
`between the 4 strata. However, the threshold of OOP costs did
`not vary widely across strata when diabetes OOP pharmacy
`costs and total OOP pharmacy costs were considered. For the
`diabetes OOP pharmacy cost analysis, $51-$75 was identified
`as the threshold of OOP costs that led to significant reduction
`in adherence. Over the 3-