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The American Journal of Managed Care October 2011
Does Telephone Care Management Help Medicaid Beneficiaries With Depression?
Sue E. Kim, PhD, MPH; Allen J. LeBlanc, PhD; Charles Michalopoulos, PhD; Francisca Azocar, PhD; Evette J. Ludman, PhD; David M. Butler, MA; and Greg E. Simon, MD, MPH
Absenteeism and Productivity Among Employees Being Treated for Hepatitis C
Richard A. Brook, MS, MBA; Nathan L. Kleinman, PhD; Jun Su, MD, MSc; Patricia K. Corey-Lisle, PhD; and Uchenna H. Iloeje, MD, MPH
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Irena Pesis-Katz, PhD; Geoffrey C. Williams, MD, PhD; Christopher P. Niemiec, PhD; and Kevin Fiscella, MD, MPH
Pharmacist-Provided Telephonic Medication Therapy Management in an MAPD Plan
Melea A. Ward, PharmD, MS; and Yihua Xu, PhD
High-Deductible Insurance: Two-Year Emergency Department and Hospital Use
J. Frank Wharam, MB, BCh, BAO, MPH; Bruce E. Landon, MD, MBA; Fang Zhang, PhD; Stephen B. Soumerai, ScD; and Dennis Ross-Degnan, ScD
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Francois de Brantes, MS, MBA; Amita Rastogi, MD, MHA; and Christina M. Soerensen, MPH
Absenteeism and Productivity Among Employees Being Treated for Hepatitis C
Richard A. Brook, MS, MBA; Nathan L. Kleinman, PhD; Jun Su, MD, MSc; Patricia K. Corey-Lisle, PhD; and Uchenna H. Iloeje, MD, MPH
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Bruce Y. Lee, MD, MBA; Ann E. Wiringa, MPH; Elizabeth A. Mitgang; Sarah M. McGlone, MPH; Abena N. Afriyie, BS; Yeohan Song, BS; and Richard H. Beigi, MD, MSc
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Yoona A. Kim, PharmD; Aimee Loucks, PharmD; Glenn Yokoyama, PharmD; James Lightwood, PhD; Karen Rascati, PhD; and Seth A. Serxner, PhD, MPH
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Brian J. Quilliam, PhD; Jason C. Simeone, PhD; A. Burak Ozbay, PhD; and Stephen J. Kogut, PhD
Routine Pre-cesarean Staphylococcus aureus Screening and Decolonization: A Cost-Effectiveness Analysis
Bruce Y. Lee, MD, MBA; Ann E. Wiringa, MPH; Elizabeth A. Mitgang; Sarah M. McGlone, MPH; Abena N. Afriyie, BS; Yeohan Song, BS; and Richard H. Beigi, MD, MSc
Increasing Pharmaceutical Copayments: Impact on Asthma Medication Utilization and Outcomes
Jonathan D. Campbell, PhD; Felicia Allen-Ramey, PhD; Shiva G. Sajjan, PhD; Eric M. Maiese, PhD; and Sean D. Sullivan, PhD
The Incidence and Costs of Hypoglycemia in Type 2 Diabetes
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Increasing Pharmaceutical Copayments: Impact on Asthma Medication Utilization and Outcomes
Jonathan D. Campbell, PhD; Felicia Allen-Ramey, PhD; Shiva G. Sajjan, PhD; Eric M. Maiese, PhD; and Sean D. Sullivan, PhD
Pharmacist-Provided Telephonic Medication Therapy Management in an MAPD Plan
Melea A. Ward, PharmD, MS; and Yihua Xu, PhD
High-Deductible Insurance: Two-Year Emergency Department and Hospital Use
J. Frank Wharam, MB, BCh, BAO, MPH; Bruce E. Landon, MD, MBA; Fang Zhang, PhD; Stephen B. Soumerai, ScD; and Dennis Ross-Degnan, ScD
Cost-Effectiveness of Intensive Tobacco Dependence Intervention Based on Self-Determination Theory
Irena Pesis-Katz, PhD; Geoffrey C. Williams, MD, PhD; Christopher P. Niemiec, PhD; and Kevin Fiscella, MD, MPH
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Francois de Brantes, MS, MBA; Amita Rastogi, MD, MHA; and Christina M. Soerensen, MPH
Does Telephone Care Management Help Medicaid Beneficiaries With Depression?
Sue E. Kim, PhD, MPH; Allen J. LeBlanc, PhD; Charles Michalopoulos, PhD; Francisca Azocar, PhD; Evette J. Ludman, PhD; David M. Butler, MA; and Greg E. Simon, MD, MPH

Increasing Pharmaceutical Copayments: Impact on Asthma Medication Utilization and Outcomes

Jonathan D. Campbell, PhD; Felicia Allen-Ramey, PhD; Shiva G. Sajjan, PhD; Eric M. Maiese, PhD; and Sean D. Sullivan, PhD
Even small changes in average copayment for long-term controller asthma medications can result in significant reductions in medication use and increases in healthcare services.

Objectives: Unintended consequences may result from changes in pharmacy benefit design. The objective was to determine the impact of increasing patient prescription copayments for guidelinerecommended, long-term asthma controller (LTC) medications on asthma-related medication use and healthcare services.


Study Design: We used 2005 MarketScan healthcare and pharmacy claims data to identify asthma (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] diagnosis code 493.xx) patients aged 12 to 64 years who were continuously enrolled through 2006 with >1 claim for an asthma medication in 2005. LTCs included: inhaled corticosteroid (ICS) (n = 10,251), ICS plus long-acting beta agonist (COMBO) (n = 27,407), and leukotriene receptor antagonist (LTRA) (n = 20,664).

 

Methods: Using multivariable models, we estimated the associations between changes in LTC copayments and LTC consumption and asthmarelated outpatient and emergency department (ED) visits.

 

Results: Patients were dichotomized into >$5 average increase in patient copayments per month of medication supplied (yes/no). The mean annual change (2005-2006) in copayments per month was $13.23 versus –$3.88 (ICS), $11.76 versus –$3.06 (COMBO), and $9.78 versus –$2.06 (LTRA). The >$5 group experienced a significant decline in average annual days of medication supplied of –47.1 days of ICS (95% CI –43.5 to –50.8), –35.3 days of COMBO (–32.4 to –38.2), and –47.5 days of LTRA (–43.2 to –51.7). Among COMBO and LTRA medication users, the >$5 copayment increase was associated with more asthma-related outpatient visits and ED visits compared with the <$5 group.

 

Conclusions: The findings suggest that even small changes in average copayment for asthma medications can result in significant reductions in medication use and\ unintended increases in healthcare services.


(Am J Manag Care. 2011;17(10):703-710)

  • Patients were dichotomized into >$5 average increase in patient copayments per month of medication supplied (yes/no).

 

  • A >$5 increase in copayment was associated with more than 1 month’s supply less utilization of long-term controller medications over the course of 1 year.

 

  • For certain classes of long-term controller medications, a >$5 increase in copayment was associated with more subsequent oral corticosteroid bursts, increases in asthma outpatient visits, and increases in asthma emergency department visits.

 

  • The study findings should be considered when designing drug benefit decisions that change formulary patient copayment structures.
As the costs of healthcare rise, healthcare payers struggle to balance access and affordability for patients and plan sponsors. To mitigate overconsumption of pharmaceuticals, many US pharmacy benefits have built-in, out-of-pocket (OOP) payments for pharmaceuticals. Historically, the patient’s contribution to pharmaceutical purchases (copayments) has been quite low, on the order of 10% to 15% of the average market price. In recent years, however, payers have increased patient copayment substantially and have created tiered pharmacy benefits and step-edits to countermand increasing demand for expensive drugs.1 For example, a 3-tier pharmacy benefit may require a monthly patient (OOP) cost of $10 for less costly generic drugs, a $25 copayment for preferred branded drugs, and a $50 copayment for nonpreferred branded drugs. This type of system is intended to incentivize the patient to move toward less costly substitutes. Substitutes are not, however, always available at the lower copayment level.

An unintended and possibly harmful consequence of changes in pharmacy benefit design is the impact that higher copayments have on clinically beneficial or optimal medication consumption.2,3 Several studies have shown that increasing OOP costs for prescription drugs reduces the rate of utilization of medications for patients with chronic diseases.4-6 However, the literature is limited on the impact that changes in health benefit design have on asthma controller medication utilization. Canadian researchers have found that increases in patient contributions to controller medications, such as inhaled corticosteroids (ICS), have reduced ICS utilization.7,8 In the United States, findings on the impact of changes in health benefit design have been mixed. Fung et al showed a reduction in ICS use with increased demand barriers on the Medicare population,9 whereas Crown et al suggested a limited change in patient-level treatment patterns due to higher patient contributions.10 The latter did, however, suggest that physician and practice prescribing preferences influenced patient treatment.10

An important unanswered question is to what extent changes in consumption resulting from alterations in pharmacy benefit design impact health outcomes. Our study objective fills a gap in the literature that relates changes in longterm asthma controller (LTC) medication patient copayment with LTC utilization and with asthma health outcomes. We tested whether or not an increase in patient-level average LTC prescription copayment per month would result in lower LTC utilization and higher rates of asthma-related health services, which are typically thought of as components of asthma exacerbations. Asthma is a convenient disease state to test these hypotheses using years 2005 and 2006 claims data because: (1) LTCs are guideline-recommended therapies; (2) LTCs prevent inflammation and reduce the risk of asthma exacerbations but many LTC users do not necessarily observe noticeable and immediate benefits from LTCs; (3) some consequences of LTC medication failure can be observed in health insurance claims data; and (4) during the study period, no known large changes occurred to the LTC market in terms of new LTCs or new generics.

METHODS

Data Source

We performed a retrospective cohort analysis using the Thompson Healthcare MarketScan commercial database (29 million covered lives in all geographic regions of the United States). MarketScan captures medical (inpatient, outpatient, and emergency care) and pharmacy claims information including the claim-level patient copayment amount, as well as eligibility status, from employees of large corporations. MarketScan is known for its high standard of claims-based information that is representative of the privately insured US population.11

Study Design

We used the 2005 and 2006 years of the MarketScan claims database to identify the study cohort and test our hypotheses. Inclusion criteria for the study (Figure) were: (1) a 2005 diagnosis of asthma defined by 1 of the following criteria: at least 2 outpatient claims with primary or secondary diagnoses of asthma (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] diagnosis code 493.xx) OR at least 1 emergency department (ED) or hospitalization claim with primary diagnosis of asthma (493.xx); (2) continuous enrollment during 2005 and 2006; (3) age >12 and <64 years on January 1, 2005; and (4) at least 1 drug claim for an LTC medication (ICS, ICS combined with long-acting beta-2 agonist [LABA], leukotriene receptor antagonist [LTRA], mast cell stabilizers, or omalizumab) with >30 days supply during 2005. Patients were excluded (Figure) if they had: (1) a diagnosis of chronic obstructive pulmonary disease (ICD-9-CM 491.2, 493.2, 496, 506.4), or at least 1 claim for an anticholinergic medication; (2) a diagnosis of emphysema (ICD-9-CM 492.x, 506.4, 518.1, or 518.2); (3) a diagnosis of cystic fibrosis (ICD-9-CM 277.0x); or (4) were enrolled in Medicare.

We linked national drug codes in the Medstat data with classes as defined in the Healthcare Effectiveness Data and Information Set 2009 Final NDC table.12 Upon reviewing the LTC utilization patterns of the study cohort during the year 2005 (Figure), we included the following most common LTC classes for analysis: ICS, ICS plus long-acting beta agonist (COMBO), and LTRA. The primary exposure variable of interest was the average change in patients’ monthly prescription copayment from 2005 to 2006 for each LTC class.

The average copayment per patient month for a given LTC class within a claim year was estimated by averaging all of the LTC claims filled for a patient and the patient OOP payment (copayment) divided by the number of months supplied (assuming 100% medication adherence). The months supplied were estimated using the days supplied field in the claims data. Patients who filled an LTC class in 2005 but not in 2006 were assigned the plan-level average monthly copayment for 2006. In this way, we assumed such patients would have faced this copayment had they filled the same LTC class in 2006. The change in copayment was calculated for each LTC class and patient by taking the average copayment per month supplied in 2006 and subtracting the average copayment per month supplied in 2005.

The outcome measures captured from 2006 pharmacy and medical claims included the following for 2005 LTC users: LTC utilization (yes/no), LTC days supplied, LTC substitution and switching patterns, oral corticosteroid bursts, asthma-related outpatient visits (primary or secondary diagnosis of asthma with ICD-9-CM 493.xx), asthma related ED visits (primary asthma diagnosis with ICD-9-CM 493.xx) and asthma-related hospitalizations (primary asthma diagnosis with ICD-9-CM 493.xx). LTC utilization was characterized in terms of average days supplied and also adherence for those who had at least 30 days supplied. Adherence was defined as the medication possession ratio where the total days supplied in a year was divided by the number of days in 1 year.13

Statistical Methods

The distribution of patient copayment change (primary exposure measure) was split into those experiencing >$5 average increase in monthly copayment versus <$5, based on an empiric analysis. We also had interest in evaluating an economically significant change of at least a $5 increase because previous evaluations suggested that this exposure variable is likely to not be linearly related to outcome measures.10 We used descriptive statistics to display the 2005 demographics and clinical characteristics and the 2005 versus 2006 LTC utilization by copayment change category for each LTC. Differences in continuous characteristics were tested using t tests and differences in the categorical characteristics and utilization proportions were tested using X2 test. For each LTC, we used linear regression to test for differences in the continuous outcome of 2006 days supplied and Poisson (negative binomial distribution for asthma-related hospitalizations) regression to test for differences in 2006 count outcomes, including oral corticosteroid bursts, asthma-related outpatient visits, asthma-related ED visits, and asthma-related hospitalizations.

We adjusted all regression analyses for 2005 baseline and clinical characteristics including: age, gender, insurance plan type, comorbidities, LTC use in terms of 2005 annual days supplied, asthma-related outpatient visits, oral corticosteroid bursts, asthma-related ED visits, asthma-related hospitalizations, and total OOP patient expenditures. We applied a modified Charlson Index (Quan et al index) to generate scores on the level and burden of comorbidity for the study cohorts to adjust for the potential confounding of health status.14 The Quan et al index draws on diagnostic information from ICD 9-CM codes and procedure codes, resulting in conditions that are weighted based on the adjusted risk of 1-year mortality. The index score is the sum of the weights for all of a patient’s conditions, with higher numbers indicating increased levels of comorbidity.

We conducted 2 sensitivity analyses on key exposure and outcome variables. First, we examined the >$5 average increase in monthly copayment only in those who filled the same LTC in both 2005 and 2006 (a subgroup of the base case cohort). Second, we examined the effect of a >$10 average increase in monthly copayment cutoff on the base case cohort.

RESULTS

Descriptive Analyses

Of a possible 2,434,764 patients with claims in the 2005 MarketScan claims data set, our study cohort was a sample size of 40,784 (Figure). Of the overall study cohort, 10,251 (25.1%) patients filled at least 30 days supplied of ICS; 27,407 (67.2%) filled at least 30 days of COMBO; and 20,664 (50.7%) filled at least 30 days of LTRA. Note that the LTC categories are not mutually exclusive. A patient could be counted in more than 1 LTC category if he or she filled at least 30 days supplied in each category.

The 2005 mean copayment per month supplied was $18.51 with standard deviation (SD) of $15.10 for the ICS cohort, $19.16 for the COMBO cohort (SD = $13.10), and $16.46 for the LTRA cohort (SD = $10.60). The mean copayment per month supplied from 2005 to 2006 for all 3 LTC class cohorts changed less than $1.00 in absolute value. Patients in all 3 cohorts with <$5 change in copayment per month supplied had, on average, a reduction in monthly copayment from 2005 to 2006 (Table 1). Conversely, patients in all 3 cohorts with >$5 increase in copayment per month supplied had, on average, an increase in monthly copayment from 2005 to 2006 (Table 1).

 
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