Claims, Lab, and EHR Data Can Make or Break a Drug Launch


Real-world data can help resolve access barriers by providing a highly detailed view into the barriers that impact specific patient populations.

Amid a projected uptick in the prevalence of chronic diseases for an increasingly aging population, it’s more imperative than ever for patients to have access to the therapies they need to treat their health conditions.1,2 To improve patient access, stakeholders across the industry have turned to real-world data (RWD) to uncover critical insights into the patient journey—from social determinants of health to diagnoses, treatment, and outcomes.

With the Center for Drug Evaluation and Research approving nearly 43 novel drugs per year, pharmaceutical (pharma) companies are recognizing the value of claims, lab, and electronic health record (EHR) data to paint a holistic picture of the market environment before launching a new drug.3 RWD-generated insights help manufacturers identify areas of need, understand access barriers and the full patient journey, and plan a successful drug launch.

Analyzing the Pharmaceutical Landscape

Before a manufacturer can launch a new drug, they must first have a comprehensive understanding of the overall landscape. RWD plays a pivotal role in this process. By blending RWD sources like claims data, lab tests and results, and EHR data with payer coverage and clinical pathway data, manufacturers can gain full visibility into what’s happening in the market.

By blending RWD sources like claims data, lab tests and results, and EHR data with payer coverage and clinical pathway data, manufacturers can gain full visibility into what’s happening in the market. Image Credit: © Molnia -

By blending RWD sources like claims data, lab tests and results, and EHR data with payer coverage and clinical pathway data, manufacturers can gain full visibility into what’s happening in the market. Image Credit: © Molnia -

Claims data reveals how patients are interacting with health care systems, while lab and clinical pathway data provide insight into how a disease progresses and how treatments are administered. Payer coverage data completes the picture by showing who is covered and to what extent.

By unifying RWD and market access data sources, manufacturers can streamline the analysis process behind their commercialization strategies. They can assess regions with high potential patient populations and fine-tune their physician engagement strategy accordingly, targeting specific areas with the most need. The level of detail RWD provides allows pharma companies to make data-driven decisions that closely align with the needs of the market and their target patient population.

Understanding Access Barriers and Optimizing Treatment

Resolving access barriers to life-saving treatments is one of the most pressing challenges in health care. RWD provides a highly detailed view into the access barriers that impact specific patient populations. Brand-specific data pulled from providers and labs, combined with competitive intelligence, can help manufacturers better understand the hurdles patients encounter. By identifying issues such as how many patients have coverage for their therapy but aren’t receiving it, manufacturers can determine and address the access barriers impacting utilization.

Integrated RWD can also reveal which physicians are testing for a disease and which drugs are being used for treating patients; this can flag the use of an inappropriate therapy. It also identifies physicians who are failing to conduct pertinent tests for a specific patient population. Equipped with this information, manufacturers can proactively intervene to resolve these barriers.

Lab data is also an integral component of optimizing access to care. By precisely identifying the health care providers and institutions who are treating specific patient populations, manufacturers can determine which hospitals and organizations are primed for access improvement.

Ensuring a Successful Commercialization Strategy

Once pharma manufacturers understand the patient population, they are well-equipped to implement an effective market access strategy. Leveraging RWD becomes crucial for informed decision-making related to driving innovation, securing drug approvals, and optimizing reimbursement for drug manufacturers. RWD reveals nuances of disease progression, patients' response to drugs, and possible reasons for abandoning treatment, illuminating areas for improvement.

Integrated RWD and market access data can also shed light on competitors’ strategies, enabling manufacturers to validate which payers and institutions have contracted with a competitor for favorable access. This crucial information allows manufacturers to make informed decisions on partnerships and alliances. By referencing a consolidated RWD source, manufacturers can expedite the analysis process behind their market access strategy and gain critical insights into expanding patient access to their therapies.

In all of these cases, data provided by real-world sources work in concert to help drug manufacturers build a commercialization strategy. While RWD was once a nice-to-have option for pharma, it has become a strategic imperative with the ability to reshape a company’s approach not only to drug development, but also to pre- and post-launch market access planning.

The popularity of RWD has even prompted its use by the FDA to monitor and assess the post-market safety of approved drugs.4 By augmenting traditional market access data with RWD from claims, labs, and the EHR, pharma manufacturers will be better equipped to launch novel therapies, overcome patient access barriers, and improve outcomes for patients in need.

About the Author

Dinesh Kabaleeswaran is the senior vice president, consulting, and advisory services at MMIT and leads MMIT's market research, advisory, and data intelligence teams, which deliver insights for MMIT's real-world data and technology products. Kabaleeswaran has a decade of managed care experience advising biopharmaceutical clients on their launch strategies across a number of different therapeutic areas. Kabaleeswaran holds a master’s in bioengineering from the University of Pennsylvania.


  1. Ansah JP, Chiu CT. Projecting the chronic disease burden among the adult population in the United States using a multi-state population model. Front Public Health. 2023;10:1082183. doi:10.3389/fpubh.2022.1082183
  2. The US Population Is Aging. Urban Institute. 2023. Accessed January 2, 2024.
  3. New Drug Therapy Approvals 2022. FDA. January 10, 2023. Accessed January 2, 2024.,novel%20drug%20approvals%20per%20year.
  4. Real-World Evidence. FDA. February 5, 2023. Accessed January 2, 2024.
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