From Integration to AI: The Data-Driven Future of Market Access

November 21

By Kala Bala and Dinesh Kabaleeswaran

In a competitive market, pharma companies are increasingly relying on various datasets to drive their decision-making. With so many disparate sources, however, data standardization presents a challenge, especially for companies eager to use predictive analytics tools. In a recent survey of 125 pharma executives, nearly half cited data integration and cleanliness as the primary roadblocks to adopting technologies like AI.

Harmonized data is a prerequisite for generating actionable insights, with or without sophisticated data science engines. For pharma companies, integrating internal and external datasets to create a single source of clean, unified data is an imperative. Without visibility across the product lifecycle, manufacturers are climbing a mountain without a guide—as those with more efficient data strategies forge ahead.

Making the Case for Data Integration

An integrated data model is especially important for market access teams, as they study the impact of payer and provider behavior on utilization. Integrating real-world datasets with payer policy, restriction, and formulary data reveals the full scope of the patient journey, helping pharma identify and mitigate the specific barriers impeding access to their therapies.

By bridging medical and pharmacy claims to policy and restriction data, pharma can explore the difference in how payers say they’ll manage a drug versus the reality. Every day, thousands of claims are processed for drugs that are technically not covered on published formularies. Integrated claims and coverage data quantifies how medical exceptions, new-to-market policies, and unpublished policies affect patient access. By tracking the impact of payer restrictions on time to treatment, manufacturers can advocate for adjustments to speed access.

Read the full article in Drug Channels.

Learn more about NorstellaLinQ, pharma’s first fully integrated data asset combining claims, labs, and EMR data with forecasting, clinical, payer and commercial intelligence.

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Kala Bala

Kala Bala is the senior vice president of Enterprise Access & Data Expertise at MMIT. Her team manages high-quality datasets to help clients solve market access barriers and smooth access to therapies. Kala has almost a decade of experience in data operations and payer research, and has served in numerous leadership positions. She holds a master’s degree in business administration from Baruch College.

Dinesh Kabaleeswaran

Dinesh Kabaleeswaran is the senior vice president of Advisory Services at MMIT. His team provides market access context and a market research narrative for the company's data and technology products. Dinesh has more than a decade of managed care experience, advising large biopharmaceutical clients on pre- and post-launch strategies across oncology, non-oncology and immunology therapeutic areas. Dinesh holds a master’s degree in bioengineering from the University of Pennsylvania.