Patient-Level Data Provides a Competitive Edge to DTC Advertisers

Contributed by:

Heather Alba, Engagement Manager, IMS Health

NOTE: The content below contains the first few paragraphs of the printed article and the titles of the sidebars and boxes, if applicable.

These days, selling direct-to-consumer (DTC) advertising space/time to pharmaceutical brand teams can be a tough sell. Promotional budgets are tight, and without hard data on how a medium’s reach aligns with a brand’s target audience, marketers are less likely to take a risk than in the past. In fact, DTC spending has been trending downward for several years; U.S. pharmaceutical companies spent 20% less on reaching consumers in 2011 than they did in 2007. And without measurable proof that an advertising investment delivered a positive return, there’s no basis on which to earn repeat business. However, advances in patient-level market insights and analytics have finally brought new levels of precision to DTC targeting and ROI measurement that benefit agencies and media outlets on behalf of their pharmaceutical accounts. Anonymized patient-level data can be aligned to media markets — and even linked to de-identified lists of patients exposed to the message — making it possible to: » Target DTC campaigns with precision, knowing the therapy choice of the audience in a particular geographic area or for a ­specific media outlet. » Measure return on investment (ROI) ­without performing costly primary market research. Advertising agencies and media companies can help pharmaceutical brand teams spend their limited DTC advertising budgets wisely, demonstrating the value of placements in terms of the patients they reach and their impact on patients’ behavior. Such quantifiable feedback can inform media buying decisions and continuously improve the efficiency and effectiveness of a company’s DTC advertising spend. Advertising agencies and media companies that are able to help their clients allocate their DTC resources in this way will prove their value time and again. The Methodology Applications of this breakthrough are best appreciated with an understanding of the data and methodology involved. The foundational database consists of hundreds of millions of patient-level healthcare records that have been de-identified in full compliance with HIPAA regulations using a unique algorithm. Key metrics on individual, anonymized, patients tracked over time include treatment, demographic, and psychographic information. This information, being evidence-based, is without the bias of self-reported data collected from patients. Plus, it’s available on an ongoing basis, unlike the ad hoc results of primary research. The data can be cut to provide insights into the prevalence of treatment, patients’ therapy choices, and their demographics in specific geographies, including the geographic breakdowns by which advertising is purchased. Through a series of indices that compare the metrics from a given geographic area with the national marketplace, one can identify: » Which areas have the highest concentration of patients with a particular condition/ taking a particular drug (by brand), i.e., which markets hold the greatest ­opportunity for a therapy. » The profile of patients being treated for a particular condition in a given area. » How specific brands are performing. It is also possible to match the data to any list of media consumption, such as subscriber lists from magazines or registered users from an online site, to calculate the relevance and value of a particular audience to an advertiser, by brand. To accomplish this in a way that is HIPAA compliant, a third party deidentifies the subscriber list using the same encryption algorithm that is used to deidentify the prescription claim. The two deidentified sources are then integrated, providing a profile of the audience in terms of: » The number of audience members being treated for a particular condition. » The number of total prescriptions filled among the audience for a given brand. » The rate and number of new patients ­joining the audience. » Compliance and persistence rates among audience members. All of these factors are then compared with the same information for the marketplace as a whole, thereby indicating the audience’s relative value to the advertiser over other groups. Both the geographic indices and the audience-specific analyses provide a clear view of how and where an advertiser can reach the largest and most appropriate audience for a brand’s goals. Perhaps, for example, it is in metropolitan markets where there is the highest concentration of patients being treated for diabetes. (See Figure 1.) Or, perhaps it is the magazine with the highest concentration of patients who are new to therapy. The Proof Is in Patient Data Patient-level data, broken down by geographic area and/or matched to any media consumption data, can be used to measure the ROI of a campaign with great precision. Through the selection of a test and control group, changes in patient behavior can be reported post exposure to show the true impact of the campaign across key measures such as new patient starts, average number of days to convert, number of exposures prior to conversion, and patient persistence and compliance rates. Advertising agencies and media companies can use this insight to: » Provide actionable insight for optimizing and measuring the brand’s campaign. » Demonstrate to prospective advertisers the type of ROI others have been able to achieve. » Offer true accountability to customers with evidence-based ROI calculations. » Earn repeat business on the basis of value delivered. A Real-Life Example Based on the results of an analysis of the geographic areas with the highest concentration of patients taking a diabetes product, a pharmaceutical manufacturer ran a television campaign within select geographic areas. Five months after the start of the campaign, there was a .28% incremental lift in conversion rate for new-to-brand prescriptions among patients exposed to the promotion versus those in the control group. In all, the campaign resulted in nearly 13,000 new patients across the test geographies, with the highest conversion rates in New York, Miami, and Philadelphia. (See Figure 2.) In this case, anonymized, patient-level data effectively identified the geographies in which patients were more likely to fill a diabetes prescription compared with the overall U.S. diabetes population. Following exposure to the campaign, patients within these geographies were significantly more likely to convert to the brand compared to the control group. Conclusion For years, targeting patients for DTC advertising and measuring the return on such campaigns could only be done via primary market research — an expensive, time-consuming, and potentially biased exercise. Now, de-identified, patient-level data provide a rapid, cost-effective, and evidence-based alternative. Pharmaceutical brand teams can now reasonably expect to make their DTC advertising decisions with hard data on which markets and outlets afford the largest opportunity. And they can plan to continually improve their advertising effectiveness with precise measures for every campaign. Editor’s Note: IMS Health’s HealthRatings applies the largest repository of HIPAA-compliant patient data to any unique audience (viewership data, subscribers, panel members, or geographical footprint) to demonstrate the audience’s actual value to a pharmaceutical advertiser. Patient-Level Data Provides a Competitive Edge to DTC Advertisers Patient-level data, broken down by geographic area and/or matched to any media ­consumption data, can be used to measure the ROI of a ­campaign with great precision. Figure 1: Regions with the Highest Concentration of Diabetes Patients based on Brand Development Index Figure 2: % Cumulative Conversion Rate Top Geographies

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