Using Big Data to Anticipate Where the Market Is Going
In last month’s column, I described some of the things that big data can’t do, in short, that’s it’s not a “silver bullet.” This month, I’ll talk about some of the things it can do.
Big data has the potential to provide critical insights into patient behavior and to allow pharmaceutical companies to anticipate where the market is going. It can allow companies to identify gaps and opportunities across the continuum of care, but only if they build the right decision tools to make the most of their data.
Adopting a Market-Driven Approach
Historically, pharmaceutical companies have taken a product-driven approach to their business. This approach usually starts with a company looking at a particular space and deciding to pursue a product idea based on the number of sick people or treatments given per year. In the context of big data, these potential products can be identified through a simple scan.
The problem is, though, that in recent years, a number of critical demands have appeared from payers that this simple scan can’t address. As payers try to get healthcare cost inflation under control and demand more evidence of value for new and even existing products to justify their prices, having outcomes data demonstrating economic and clinical value in terms capable of persuading payers will be increasingly critical.
In this environment, companies must rigorously examine broader customer needs. If they build a model focused on a specific disease state, and take a comprehensive look at the continuum of care that allows them to identify unmet needs -- going beyond the traditional approach of examining the number of potential patients for a given treatment -- they will be able to guide the development of sustainable growth platforms. This approach will allow pharmaceutical companies to better anticipate where the market is going and differentiate themselves accordingly. In this case, it’s not so much a matter of acquiring as much data as possible, but in making efficient use of the data you have.
Beyond product decision-making, by thinking about pharmaceutical products in the context of the continuum of care, companies have an opportunity to more clearly define the economic and clinical value (ECV) their products bring, and to communicate that value -- supported by evidence -- to payers, patients, and physicians. It allows these companies to take into account the expected downstream impacts of an intervention, and quantify these benefits in a comprehensive fashion.
“Recently, payers and provider organizations have shown increasing interest in treatment guidelines as a way to ensure greater consistency and use of evidence-based medicine”
This approach to big data can help pharmaceutical manufacturers respond to one other pressure as well. Recently, payers and provider organizations have shown increasing interest in treatment guidelines as a way to ensure greater consistency and use of evidence-based medicine. It’s expected that this trend will grow as physicians are increasingly employed by hospitals and healthcare systems and payers apply downward pressure on reimbursement. As clinical protocols become more common, data that’s examined in the context of the continuum of care can help manufacturers demonstrate that their products have a place in the treatment guidelines, and where they fit. Companies that can demonstrate that they’ve identified the right treatment for the right patient at the right time will have a strategic advantage in an environment where evidence-based care guidelines are more widely used.
Creating the Decision Tools to Make the Most of Your Data
So how can companies operationalize a system for using their data effectively? First of all, it’s important that the market-based approach and focus on ECV be embedded across an organization. But the market-driven model requires new capabilities and organizational infrastructure to support those capabilities. Data will only be optimally utilized if the organizational structure is aligned to support its use.
This means having processes in place that allow companies to make consistent use of data across the product lifecycle in order to support the product’s ECV story. It also means building the discipline to take into account the perspectives of payers, regulators, patients and physicians on the value that the product brings. Pharmaceutical companies need to engage with these groups to understand their needs, deliver solutions that address those needs, and frame the health economics discussion more advantageously. Then they can use their data in a way that’s structured to demonstrate compelling clinical and economic value in comparison with available alternatives.
Changing behavior to align with this approach isn’t business as usual. It will also require redefining the roles of various parties to ensure accountability for the steps in the processes defined to make consistent use of the right data. This may require new or expanded competencies as well.
A continuous theme in the last few installments of this column is that it isn’t nearly as important how much data you have as it is to ensure that you are using it correctly. Manufacturers will need to embed rigorous analysis in their data strategies, creating processes and defining roles with accountability for ensuring that processes are followed, in order to make the most of the right data. Without this infrastructure, companies may end up squandering the data they do have.
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