High-quality data is needed to power high-quality analytics and insights

Ben Comer Senior Manager, Health Research Institute, PwC US March 27, 2019

Drug and device companies that want to maximize the value of their data assets with analytics must have access to high-quality data, such as physician data that can be integrated seamlessly with tools (like chatbots) used by sales forces and marketing executives.

The first step toward building an advanced analytics capability is to integrate data assets already available in different corners of the commercial function. Combining syndicated market research with specialty pharmacy data in a single data environment helped lead one US-based biopharmaceutial company to new insights and improve the value of the data sets.

Companies also need to understand the end customer—the patient—on a deeper level. A digital solution used by a patient tells a much deeper story about patterns of medication use and lifestyle choices, which in turn can help to create new personalized solutions for that patient. However, access to high-quality, patient-level data is limited for most companies, due in part to privacy laws and indirect access to patients. Thirty-three percent of pharmaceutical executives surveyed by HRI said the use of electronic health records by providers has had a positive effect on their businesses.

Differing product portfolios, corporate cultures and experiences with data integration and governance have led to divergent capabilities across the pharmaceutical and life sciences industries.

Much like the differences in advanced analytics maturity, some organizations have gone further than others in creating a robust data environment capable of generating predictive insights and real-time reporting. While many pharmaceutical companies have access to market volume data (e.g., prescription claims data), specialty pharmacy data, market research, sales force data (e.g., customer details, product sampling), qualitative physician surveys and advertising data collected from media agencies, these data sets are often not fully integrated.

That lack of integration inhibits the use of advanced analytics to generate predictive, prescriptive or cognitive analytic insights.

At another global biopharmaceutical company, executives are focused on integrating internal data and other purchased, third-party data sets, and identifying the remaining customer data gaps.

Bridging those gaps in physician behavior and the patient journey is where the biggest opportunities exist. Enormous amounts of data are being generated throughout the healthcare ecosystem—in electronic health records, by insurers and PBMs, and by patients themselves—but no single stakeholder has the complete picture.

Data sharing between healthcare sectors also can improve the customer relationship between drugmakers and health systems. Pharmaceutical companies are investing in patient data collection and analytic services to improve interactions between physicians and patients, with the ultimate goal of improving outcomes. As data becomes more accessible across the healthcare ecosystem, commercial analytics will become a critical tool for generating business insights and predicting market change. But the insights will only be as good as the data feeding into the analytics system.