Optimizing Investments in Rare Disease Claims Data

A large life sciences manufacturer began to reassess its strategy for investing in rare disease claims datasets. The client had been purchasing datasets from multiple vendors, including a combination of commercially available open and closed data sources, augmented with several unique disease-specific data assets. The client uses these data assets to evaluate the size of patient-specific populations and to compare its product against therapeutic alternatives in terms of cost, outcomes, and other factors. To reassess its investment, the client enlisted us to conduct a thorough audit of the datasets and to compare them with alternative options to determine whether to change its investment strategy for rare disease claims data.

We analyzed the client’s current data portfolio for patterns that would enable us to determine the degree of overlap between original data sources. We then compared our findings to the data vendor’s marketing materials and identified several discrepancies, indicating gaps in the data being purchased. We also compared the claims in the data portfolio to the claims in datasets from other vendors to evaluate the degree of overlap so the client could determine how to maximize its data through a novel metric of number of unique claims obtained per dollar spent. We then developed strategic recommendations for optimizing the client’s investment strategy for rare disease claims data to support its indications of interest and overall strategic priorities.

Our analyses provided valuable business intelligence to the client and our recommendations led to a decision to conclude purchasing data from the original vendor and to switch to a different vendor whose data assets were validated thoroughly by our analyses and could better serve the client’s needs.