Value-Based Design and Prescription Drug Utilization Patterns Among Diabetes Patients
Published Online: June 06, 2013
Teresa B. Gibson, PhD; John J. Mahoney, MD; Karlene Lucas, MBA; Kim Heithoff, ScD; and Justin Gatwood, MPH
Faced with increasing costs and a challenging economic climate, many US firms continue to increase the health insurance contribution required of their employees. Since 2001, worker contributions to employersponsored health insurance have increased 131%, outpacing the 113% increase in premiums over the same period.1 Specific changes have included alterations in the structure and amounts of prescription drug cost sharing. In the past decade, the average cost-sharing amount for generic medications has grown 25% from $8 to $10 between 2001 and 2011; there have been larger changes in cost sharing for preferred and nonpreferred brand medications, with increases of 93% and 69%, respectively.1
One strategy to address specific healthcare costs that has gained traction in recent years is the use of value-based benefit design (VBID). This approach utilizes incentives within the employee benefit structure to encourage the use of high-value health services.2 Lowering out-of-pocket exposure for particular classes of drugs is a popular mechanism of value-based plans, and has been an especially prevalent method to address diabetes, a condition whose annual economic toll in the United States is approaching $200 billion.3 Reducing medication out-of-pocket costs for patients with diabetes has had several positive effects across multiple studies, including improvements in medication initiation and adherence, lower treatment discontinuation rates, and decreased disease-related costs.4-9
Recently, Gibson and colleagues8 assessed the effects of a value-based pharmacy access program that lowered the out-of- pocket costs of all brand diabetes medications to the lowest (generic) tier for employees, spouses, and dependents of 2 units of a large, multi-industry firm. They observed that the value-based program, when combined with concurrent disease management (DM), was associated with an increase in adherence to diabetes medical guidelines and a positive return on investment for diabetes-related spending.8
Additionally, an increase in adherence to diabetes medication was observed over time; however, these results were reported for the entire antidiabetic medication drug class.
The purpose of this investigation was to estimate the effects of the pharmacy program on utilization of generic and brand antidiabetic oral medications and insulin. Results of this study will provide needed information regarding the differential effects of cost-sharing changes on adherence to generic and brand medications, which will aid in the design of future programs.
Typically, brand and generic medications have been viewed as substitutes for each other; however, the body of literature comparing these medications suggests there may be a more complex relationship. There is some concern that value-based programs that lower only brand name out-of-pocket exposure will prove to be costly, as they may give patients an incentive to replace lower-cost generic medications with higher-cost brand name medications, running contrary to cost-sharing trends that place brand medications at the highest cost-sharing levels. Such a pattern was observed by Nair and colleagues,9 who examined the effects of a value-based program that lowered all brand medications to the first (generic) tier. They found higher utilization of brand name diabetes medications in each of the 2 years following the copayment reduction, but no difference in diabetes generic medication utilization in the fi rst year and a drop in the second year, although a comparison group was not used to control for important contemporaneous trends such as generic introductions or new brand name medications.9
Conversely, several studies have examined the effects of higher brand name copayments on generic use in several medication classes, holding copayments for generic medications constant. In these studies, for the most part,use of brand name medications went in the expected downward direction due to the out-of-pocket increase in price.10-17 However, utilization of generic medications has been seen to increase,10 decrease,11,12,16 or stay the same12,14,15,16 following an increase in brand name copayments (not generic copayments), varying by medication class and the cost-sharing structure. Importantly, the size of the difference between brand and generic cost-sharing amounts (ie, the brand-generic “differential”) is important in the relative use of brand and generic medications.17
The Truven Health Advantage Suite data warehouse for the firm implementing the pharmacy access program was used for this investigation. This data warehouse contains the inpatient and outpatient medical claims, outpatient prescription drug claims, and enrollment information along with patient characteristics such as age, sex, health plan, and length of enrollment. In additionto the internal comparison groups, firms were selected from the Truven Health MarketScan Commercial Claims and Encounters Database to serve as a comparison group for the enrollee cohort who participated in the pharmacy access program.
Pharmacy Access Program
Beginning January 1, 2006, the firm implemented a voluntary DM program for all individuals covered under their medical plan. Similar to programs offered by other major firms, this program included targeted mailings, condition-specific workbooks, telephone nurse outreach services, educational mailings, coaching, and periodic monitoring. A letter describing the program components was provided to employees in the affected business units; further communication regarding the program continued throughout the follow-up period.
Concurrently, the firm offered a diabetes value-based pharmacy program to employees and dependents of 2 US-based business units. Through this program, cost sharing was lowered to 10% for all diabetes medications (see eAppendix A) from original levels of 10% for generic, 20% for preferred brand, and 35% for nonpreferred brand medications. Both the value-based and DM programs were implemented separately, and the DM vendor was unaware of the specific groups receiving the value-based benefit.
The baseline year for the study was 2005—before the intervention began—and the 3 subsequent years (2006, 2007, and 2008) were included in the postintervention period. All enrollees under the age of 65 years who had at least 4 contiguous quarters of enrollment in 2005 through 2008 were selected.
Our analysis focused on the effects of the value-based pharmacy program on enrollees with DM. Variations in program implementation allowed for the analysis of a natural, internal comparison group: plan enrollees with DM who worked in business units where the value-based program was not offered. Subsequently, enrollees in both the value-based and DM programs were matched to enrollees with DM only. As a secondary analysis, a comparison group was constructed from firms in the MarketScan Database without a value-based program. We ensured that the overall characteristics of the firms, their spending trends before the study period, and their adherence trends (2005) were similar to those of the intervention firm.
Matching was performed using propensity score estimation based on the probability of being in a specific program. This was done using a collection of variables: age, sex, area of residence, employment classification and status, relationship to employee, median income and college graduates in the zip code of residence, plan type, health status, and length of plan enrollment. Applying the resulting propensity score, program enrollees were then matched to enrollees in each of the comparison groups.
A panel data file was constructed with enrollee as the cross-sectional unit and calendar quarter as the unit of time. Enrollee experience was captured in quarterly increments throughout the benefit enrollment time frame or through the end of December 2008, whichever was later. We used an intent-to-treat framework, assigning enrollees to their initial plan or program; therefore, any rare instances of crossover would likely bias our results downward. This approach also retains nonusers of medications in each quarter.
The medication possession ratio (MPR), a metric representing fill adherence, was calculated as the percentage of days covered by medications within the calendar quarter for generic and brand oral antidiabetic medications and for insulin. The MPR was calculated using the fill dates and days of supply on the prescription drug claims to determine the number of days that medications were on hand. The MPR can range from 0% to 100%, and was calculated separately for oral antidiabetic medications and insulin. Prescription drug fills prior to 2005 were not available. Because the days on hand early in 2005 were likely a result of fills made in 2004, the adherence measure for the fi rst quarter of 2005 was not utilized for analyses as it was likely to be understated.
A user rate was also calculated. It was set to 1 for patients with medication in the class of interest during the quarter and to 0 for patients with no medications in the class. As a dichotomous variable, the user rate can serve as a measure of initiation or discontinuation of a medication class.
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