How Generics Companies Can Improve Hospital Rx Access

The US hospital generics market continues to face a difficult contradiction: manufacturers, distributors, and health systems have access to more data than ever, yet drug shortages persist and access remains uneven, particularly for smaller and lower tier hospitals.

Companies may detect early signals such as demand shifts, inventory drift, access friction, contract gaps, or changes in account behavior, but still struggle to convert those signals into coordinated action across supply, access, commercial, and field teams. The result can be delayed response, missed opportunities, avoidable revenue leakage, and uneven access for hospitals that may already have fewer resources to manage volatility.

In this Q&A, Rahul Mittal, head of strategy and innovations at Dr. Reddy’s Laboratories North America, discusses an execution infrastructure approach for bridging that gap. The model organizes cross functional signals, applies explicit decision logic, assigns ownership, and tracks actions through closure. The examples discussed are anonymized, and the focus is on transferable principles that other manufacturers can adapt without relying on proprietary tooling or large IT investments.

PC: You’ve Said that the Biggest Gap in Hospital Generics is Execution, not Data. What do you Mean?

Mittal: Data availability and execution reliability are not the same thing. Most organizations can see signals. Orders are moving. Inventory is tightening. Bids are stalling. Access friction is rising. The breakdown often happens in the translation from signal to coordinated action.

In one anonymized situation, demand began drifting downward across a group of mid tier hospital accounts while broader inventory signals did not immediately indicate a supply issue. When the signal was examined across contract structures, GPO coverage, and field engagement, the root cause turned out to be an access visibility issue rather than a supply constraint.

Once identified, the response required coordinated action. Contract and access teams clarified eligibility. Field teams were given a prioritized set of accounts and guidance. Follow through was tracked until ordering normalized. The signal itself appeared early. The difference came from having an execution structure that ensured it was acted on consistently.

In another case, an account cluster showed unstable ordering patterns across a limited number of institutional customers. Rather than treating it as isolated variability, the signal was evaluated across contract hierarchy and ordering pathways. A mismatch in account mapping was identified, and once corrected, ordering stabilized within a defined period.

These kinds of situations are not uncommon. What varies is whether organizations have a system that ensures signals are acted upon in a timely and coordinated way. Execution infrastructure is intended to provide that system.

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