A brand can have performance issues—like local access due to plan coverage and patient compliance—at virtually any phase of its lifecycle. Metrics from anonymous patient level data (APLD) can be developed to provide a rapid assessment that examines regional areas where uptake of market share is not meeting expectations.
The gastro-esophageal reflux disorder (GERD) market has been served for many years by two distinct classes of medications. The first class of drugs used to treat the condition was termed H2 Antagonists and included brand names such as Zantac, Pepcid, and Axid. In 1989, AstraZeneca launched the first of a new class of medications called Proton Pump Inhibitors (PPI). The release of Prilosec was quickly followed by other PPIs including Takeda’s Prevacid, Eisai’s Aciphex, and Pfizer’s Protonix.
The GERD market was one of the early darlings of the move to using direct-to-consumer advertising among pharmaceuticals. AstraZeneca’s Prilosec, long known as the “Purple Pill,” went off patent in 2001 and was replaced by a follow-on drug, Nexium. By the mid-2000s, virtually all H2 Antagonists were available generically, while the PPIs battled for competitive market share across the country. In 2004, AstraZeneca received approval for Prilosec to be distributed as an OTC medication.
Meanwhile, in the late 2000s, Prevacid and Protonix lost patent protection. With the loss of Prevacid’s patent protection in 2009, Takeda launched a new PPI, Dexilant, into the market in February 2011. Dexilant is different than most medications of its kind because, like an extended-release type of medication, one pill releases two separate doses of the medication.
By June 2012, Dexilant achieved a 3.3 percent share of new-to-brand patients and a 3.6 percent share of total prescriptions across the market. How consistent was the national performance with sub-national territory performance? Alternatively, could issues be identified via a diagnostic that incorporated APLD in order to improve Dexilant’s performance?
The Assessment: New-To-Brand Prescriptions And Compliance
Monitoring compliance and new-to-brand activity on a regional level is especially important for a newly launched drug like Dexilant. Inputs to performance tracking should include projected APLD that can easily classify new-to-brand starts, an overall projected prescribing estimate for the geography, and an efficient means to capture compliance activity—all at a sub-national level.
New-to-brand prescription percentage (NTB%) is an indicator of access—how well new patients flow into taking the brand. NTB% represents the share of prescriptions among patients who are taking a drug for the first time within a defined competitive market set. For Dexilant, NTB% is defined as the number of new-to-brand patient prescriptions divided by the total Dexilant prescriptions across a given geography. To determine a profile for a “new-to-brand” prescription, marketers should apply a six-month look-back period per patient to determine whether it is the first time Dexilant was taken in the clinically relevant market.
Compliance is often a ratio expressed as a percentage that measures the time (in days) for patients to refill medications divided by the number of days’ supply they receive. A patient given a 30-day supply of a medication on January 1, 2012 would be 100 percent compliant if he refilled his prescription 30 days later on January 31, 2012. Similarly, that patient would be only 50 percent compliant if he refilled the prescription 60 days later. Substandard compliance may be an indicator of potential cost or education issues that the brand may have.
Plotting NTB% against compliance-percentage in a scatter-plot graph can create a diagnostic. The national values for both NTB% and compliance (16.7 percent and 80.3 percent, respectively) are used as lines of central tendency to complete the quadrant. By adding these mean as central lines on to the graph, the chart provides a quick and easy assessment of high performing territories as well as potential issues. Furthermore, this approach could be used for the ongoing assessment of relative territory performance over time.
A view of this grid by Core Based Statistical Area (CBSA), used as a proxy for a potential territory, is shown in the accompanying chart.
The resulting analysis reveals notable performance characteristics for Dexilant in several geographies. For example, 22.8 percent of New York’s Dexilant prescribing was for new-to-brand prescriptions, suggesting strong access in the region. However, patients maintained one of the lowest geographic compliance rates at 75.8 percent, suggesting that tactics in the territory should be weighted to improve patient and physician education as a means of encouraging better patient compliance.
Conversely, the Providence area demonstrates the opposite issue. At 84.3 percent, Dexilant patients in Providence are highly compliant relative to the national expectation, but the drug demonstrates a relatively low new-to-brand prescribing percentage of 8.8 percent. This could suggest a significant payer or patient access issue, which inhibits initial brand prescribing. Brand teams may adopt a strategy to improve access through targeted patient co-pay vouchers, more optimized sampling, or even changing managed care contracting over the longer term to drive new patient starts.
The analysis also can be used to determine “star” and “dog” performing territories as key performance indicators (KPI). For example, based on the expected values, the performance of Dexilant in Miami (19.5 percent NTB%, 81.6 percent compliance) is high compared to a territory such as Greenville, SC (14.6 percent NTB%, 77.9 percent compliance).
Deploying APLD to enable more insightful brand analysis does not always require a lengthy or complicated process to assess potential problem areas. A brand assessment may be used to identify and address not only relative performance issues in an area but also the nature of specific issues in the territory.
Measuring Results And Taking Action
Ideally, a brand team will want to see both high new-to-brand start rates and acceptable compliance as a performance indicator in each of the territories in which the medication is launched. Realistically—given a competitive marketplace and managed care access/formulary positioning—it is unlikely that each and every territory will meet those expectations. By creating a scatter plot graph comparing NTB% against compliance rates for the same territory, brand teams can get a quick understanding of both the location and nature of any issues that may be occurring.
Using the nationally generated new-to-brand market share and compliance rates as “zero points” on a graph, a simple four quadrant graph may be constructed to represent how territories are performing relative to one another—and the resulting actions brand teams can take:
- HIGH NTB%/HIGH COMPLIANCE = Star territories; model behaviors in other territories
- HIGH NTB%/LOW COMPLIANCE = Potential compliance issues; initiate physician/patient education programs locally; deploy samples and/or compliance programs
- LOW NTB%/HIGH COMPLIANCE = Potential access issues; initiate voucher programs or other cost modification programs and examine managed care influence over territory
- LOW NTB%/LOW COMPLIANCE = Dog territories; examine potential sales issues along with other initiatives identified in territories with compliance and access issues
Given the information available to marketers, this type of assessment tool may be easily—and quickly—established for launch and mature brands. Analysts can examine changes from time period to time period and determine the longer effects of regional programs and whether corrective actions are improving overall performance.
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