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Cost Sharing, Adherence, and Health Outcomes in Patients With Diabetes
Teresa B. Gibson, PhD; Xue Song, PhD; Berhanu Alemayehu, DrPH; Sara S. Wang, PhD; Jessica L. Waddell, MPH; Jonathan R. Bouchard, MS, RPh; and Felicia Forma, BSc
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Cost Sharing, Adherence, and Health Outcomes in Patients With Diabetes

Teresa B. Gibson, PhD; Xue Song, PhD; Berhanu Alemayehu, DrPH; Sara S. Wang, PhD; Jessica L. Waddell, MPH; Jonathan R. Bouchard, MS, RPh; and Felicia Forma, BSc

Higher cost-sharing levels reduced adherence to antidiabetic medications in patients with type 2 diabetes.

Objectives: To assess the relationship between cost sharing and adherence to antidiabetic medications in patients with type 2 diabetes and to examine the relationship between medication adherence and outcomes, including complication rates, medical service utilization, and workplace productivity measures.

 

Study Design: A retrospective, cross-sectional study analyzing the healthcare experience of patients with type 2 diabetes on oral antidiabetic medication (OAD) with or without insulin (n = 96,734) and patients on OAD only (n = 55,356) with employer-sponsored insurance in the 2003-2006 MarketScan Database.

 

Methods: Using a 2-stage residual inclusion model, the first stage estimated the effects of cost sharing on adherence to antidiabetic medications in an 18-month time frame (January 2003 through June 2004). Adherence was determined from the percentage of days covered. The second stage estimated the effects of adherence on complication rates (eg, retinopathy, neuropathy, peripheral vascular disease), medical service utilization rates, and measures of productivity (absence days and short-term disability days) in the subsequent 2 years (July 2004 through June 2006).

 

Results: A $10 increase in the patient cost-sharing index resulted in a 5.4% reduction in adherence to antidiabetic medications for patients on OAD only and a 6.2% reduction in adherence for patients on OAD with or without insulin. Adherence was associated with lower rates of complications (eg, amputation/ulcers, retinopathy) and also was associated with fewer emergency department visits and short-term disability days.

 

Conclusions: Medical plans, employers, and policy makers should consider implementing interventions targeted to improve antidiabetic medication adherence, which may translate to better outcomes.

 

(Am J Manag Care. 2010;16(7):589-600)

This retrospective, cross-sectional study investigated the relationships between cost sharing and adherence to antidiabetic medication, and among adherence, diabetes-related complications, and utilization measures.

  • Higher levels of patient cost sharing for antidiabetes medications were associated with lower levels of adherence (percentage of days covered) to antidiabetic medications. For example, among patients on oral antidiabetic medications only, those whose cost-sharing amount was $10 higher had adherence rates that were 5.4% lower.
  • Antidiabetic medication adherence was associated with lower rates of many diabetes-related complications (eg, amputation/ulcer and retinopathy), and with fewer inpatient visits, emergency department visits, and short-term disability days.
  • Medical plans, employers, and policy makers should consider ways to promote adherence to medications, including reduced patient cost sharing.
Approximately 23.6 million individuals in the United States have diabetes, a serious metabolic disorder that affects all systems of the body, particularly the neurologic and cardiovascular systems.1 Proper medication management among patients with diabetes is a key component of preventing diabetes-related complications.2

Inadequate medication adherence among patients with chronic illness has been associated with increased healthcare utilization, costs, and risk for adverse health outcomes.3,4 Encinosa and colleagues studied adherence among privately insured patients with diabetes on oral antidiabetic medication (OAD), finding that improved adherence was associated with decreased hospitalization and emergency department (ED) costs.5 Similarly, Sokol and colleagues found that a high level of medication adherence among privately insured patients with diabetes was associated with decreased condition-specific medical spending.6 Regarding health outcomes, Ho and colleagues found that nonadherence to OAD among privately insured patients with diabetes was associated with an increase in glycosylated hemoglobin (A1C) levels, all-cause hospitalizations, and all-cause mortality.7 Such evidence underscores the value of medication adherence to patient health.

These findings also suggest that important differences may exist between patients who are adherent and those who are nonadherent, and these potential selection effects may affect the relationship between adherence and outcomes. Thus, rigorous methods must be adopted to account for possible endogeneity in the relationship between adherence and outcomes.

Barriers to medication adherence such as high patient cost sharing for prescription drugs inhibit patient adherence.3,4,8 Few studies have linked the effects of cost sharing to adherence, and subsequently, to outcomes. Hunt and colleagues measured the relationships between cost sharing and adherence and between adherence and glycemic control among patients with diabetes, finding a positive relationship between cost sharing and A1C level.9 However, the ultimate effects of cost sharing on diabetes-related complications, through adherence, are not yet well known.

This study contributes to the literature in several ways. First, we investigated the relationships between cost sharing and adherence to antidiabetic medication. Second, we addressed the relationship among adherence, diabetes-related complications, and utilization measures using rigorous methods. We assumeda more comprehensive view of the impact of medication adherence, also incorporating measures of productivity for employees with diabetes. We used 2-stage residual inclusion models to estimate these  relationships and produce consistent estimates.

METHODS

This study is based upon the Thomson Reuters MarketScan Database, 2002-2006, which represents the healthcare experience of more than 21 million enrollees with  employer-sponsored benefits annually. Inpatient medical, outpatient medical, and outpatient pharmacy claims, absenteeism data (dates of absence from work due to illness), and claims for short-term disability benefits were linked to enrollment information to create the analytic data set.

A retrospective, cross-sectional study was conducted among patients aged 18 years or older with diabetes who used OAD (sulfonylureas, meglitinides, biguanides,  thiazolidinediones, or alpha-glucosidase inhibitors) and were continuously enrolled from January 1, 2002, through June 30, 2006. Patients were included if they filled at least 2  prescriptions for an antidiabetic agent from January 1 through June 30, 2003, and had a diagnosis of diabetes (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 250.xx) as indicated by 1 ED visit, 1 inpatient admission, or 2 outpatient visits at least 30 days apart. Patients also were required to have the first  observed fill for an OAD occurring in 2002 or the first quarter of 2003. Patients with a diagnosis of type 1 diabetes or gestational diabetes (ICD-9-CM code 648.8x) were excluded. The final samples consisted of 96,734 patients with type 2 diabetes on OAD with or without insulin in the full sample and 55,356 patients who filled an OAD prescription only (no insulin). We created 2 additional subsets of patients who were employees with available absenteeism data (n = 1829; n = 1040 OAD only) and short-term disability data (n =   3027; n = 1753 OAD only).

Measures

Adherence was measured as the percentage of days covered (PDC), expressed as the percentage of days with an antidiabetic medication on hand during the 18-month time period (January 2003 through June 2004).10 The PDC was first calculated for each therapeutic class (ie, sulfonylureas, meglitinides, biguanides, thiazolidinediones, alpha-glucosidase  inhibitors, insulin) based on prescription drug claims, using the fill date and the intended days supply of medication from each claim. Information from prescriptions filled in the fourth quarter of 2002 provided prescription utilization information for early 2003. If a patient refilled the same medication before the end of the days supply from the previous prescription fill, then the days supply for the new prescription was appended to the end of the previous fill. If a patient switched medication within a therapeutic class, the remainder of the previous prescription was discarded and coverage commenced with the supply of the new medication. Days of hospitalization were counted as adherent days (to at least 1 antidiabetes medication), as some of the factors that influence patient medication adherence may change during days of hospitalization. For insulin prescriptions, where the days supply may not indicate the full extent of coverage, we multiplied the days supply of each fill by 1.5.11 We produced results using various algorithms for insulin adherence and adherence to OAD alone for those patients who used insulin with no material change in findings.

After calculating the number of days that medication was on hand in each medication class, we compiled the information from all therapeutic classes into a single measure and measured adherence based on whether a patient had any antidiabetes medication on hand on each day. Consistent with previous studies, patients were classified as adherent to antidiabetic medications if the PDC equaled or exceeded 80%,7,12 a threshold at which clinical benefits are most likely to occur.

Complications were recorded using dummy variables that indicated the complication occurred on a claim from July 2004 through June 2006. Codes for each complication are noted in Table 1. Utilization events for July 2004 through June 2006 included physician office visits, ED visits, and inpatient admissions, coded as the number of events in the 24-month  period. Patients with productivity data available (with days of absence and short-term disability reported) were included in the productivity analysis, even if zero days were reported.

Explanatory Variables

Patient cost sharing for antidiabetic medications was measured, using a cost-sharing index created for each employer/plan combination. The index was based on the average  cost-sharing amount (ie, copayment, coinsurance) per prescription (standardized to a 30-day supply) for brand and generic drugs in each antidiabetic medication class. The index  aggregated the brand and generic copayments using weights, developed from the overall proportion of utilization of brand and generic drugs within each medication class.13,14 If we were to examine cost sharing for the medications filled by each patient, this method might introduce selection bias, as more adherent consumers might be selecting medications (eg, generics) on the basis of cost-sharing amounts. Thus, aggregating cost sharing into levels for each employer/plan combination reduced the effects of selection bias related to actual, individual-level cost sharing and related choices. The coinsurance flag indicated which plans used coinsurance (a percentage of the total payment) for   prescription drug cost sharing versus a flat fee copayment. Any mail-order use in the past year, which can be associated with higher levels of adherence,15 also was indicated. As outpatient physician visit cost sharing has been associated with reductions in the use of prescription drugs,16 the per-visit amount was included in the models.

Other explanatory variables associated with medication adherence were included in the models. Patient-level sociodemographic characteristics included sex, age, census region,  urban residence, and median income in the patient’s area of residence (by ZIP code) from the US Census files. An indicator for employee status (vs spouse/dependent) was  included, along with plan type (eg, health maintenance organization, preferred provider organization). An indicator for a visit to a related specialist (ie, cardiologist, endocrinologist) in the past year accounted for disease severity and possible differences in practice patterns.

To account for differences in health status, the following explanatory variables were incorporated into the models as well. Because newly diagnosed patients may have different utilization patterns than patients with existing disease,17 a flag indicated whether a patient was newly diagnosed with type 2 diabetes in 2003. Scores on the Charlson Comorbidity Index, a numeric scale reflecting the risk of death or serious disability in the next year based on the presence of a diagnosis for 1 of 19 conditions (eg, diabetes, heart disease,  cancer) in the 12-month preindex period, were included.18 The Charlson Comorbidity Index is associated with cost and other utilization measures such as length of stay and readmissions.18 The total patient out-of-pocket burden for chronic conditions (medical and drug) in the preindex year also may reflect lower health status. For prescription drug claims, chronic out-of-pocket spending was classified per claim by using the National Drug Code and Redbook for drug claims (claims with a drug type of “maintenance”) and for  medical claims by using the chronic conditions listed in the Charlson Comorbidity Index (as identified by a nosologist).

Analytic Framework

We analyzed the relationships among patient cost sharing for antidiabetic medication, adherence, and diabetes-related events or outcomes by first estimating the relationship  between patient cost sharing for antidiabetic medication and adherence to antidiabetic medications (controlling for covariates) during an 18-month time frame (January 2003 through June 2004). We then estimated the relationship between adherence in the initial time frame and outcomes, controlling for covariates in the subsequent 2 years, July 2004 through June 2006.

Several hypotheses based on existing evidence that higher patient cost sharing reduces medication adherence3,4 informed our approach. We anticipated that adherence would be associated with lower rates of ED visits and hospital admissions,6 and would reduce the risk of diabetes-related events or outcomes, particularly for sequelae likely to develop in the near term.2,7,19 For employees with productivity data, we hypothesized that adherence might have translated into higher levels of productivity.

Multivariate Approach

 
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