Putnam helps clients drive brand performance across the product lifecycle, thanks to groundbreaking patient- and physician-level insights – all based on strategic analysis of market research and real-world data.
As the healthcare market evolves away from mass-market solutions towards more niche, personalized products, pharmaceutical companies face the complex challenge of finding specific patient populations to enhance brand performance.
Traditionally, pharma has relied on quantitative and qualitative primary market research such as demand assessments and ATUs (awareness, trial, and usage studies) to understand utilization, drivers, and barriers to use. But while these are important, the data they produce can be limited by sample size, stakeholder recall, and bias when it comes to honing in on the incredibly complex prescribing decisions made for individual patients. Brands, therefore, often find themselves making decisions on clinical development and marketing strategies with incomplete information of niche-opportunity patients or physicians.
Alternatively, many pharma companies are recognizing the value of ‘big data’ such as claims, electronic health records/lab, sales, and hospital data, in order to have broader and unbiased coverage of the market. However, these data sources are plagued by their own limitations in coverage, with each source varying in completeness, information capture, longitudinality, and update timing. More importantly, real-world data by their nature are not set up to directly answer many of the most important questions pharma clients are facing. Therefore, these data sets must be mined using carefully designed business rules developed by individuals with a deep understanding of the therapeutic area and market dynamics, as well as how situations are coded in the data set. With data alone, we have none of the stakeholders involved in the claim to provide explanation, context, or rationale.
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