In today’s data-driven healthcare environment, commercial teams in life science companies face increasing pressure to demonstrate the real-world value of their products. Claims data, once a resource mostly used for reimbursement and payer negotiations, now holds the key to unlocking powerful commercial strategies. As an independent consultant with extensive experience in market research, payor data, and pharmaceutical analytics, I’ve seen firsthand how integrating claims data into the commercial strategy can drive tangible business outcomes—from gaining formulary access to optimizing provider outreach efforts.
In recent years I’ve worked with Aetna, Blue Cross Blue Shield and IQVIA claims data and in this post, I’ll explore how life science companies can use this data to enhance their commercial success. We’ll discuss the desired outcomes of leveraging claims data, key use cases, and when to use specific types of data such as closed versus open claims, NPI data, and allowed amounts.
Desired Outcomes: Turning Data Into Impactful Commercial Strategies
The ultimate goal of using claims data is to enable commercial teams to drive decisions that result in measurable business outcomes. Here are some of the key objectives that can be achieved through the strategic use of claims data:
- Gaining Payor Formularies Access: Claims data is crucial for demonstrating the clinical and economic value of your product. It allows you to build a compelling case for inclusion in formularies, showing the effectiveness of your therapy in real-world settings. By linking treatment patterns and outcomes to your drug, you can present a data-driven narrative that resonates with payors.
- Provider Outreach Strategy: Claims data offers rich insights into provider behavior and treatment patterns. Commercial teams can use this information to identify high-value providers who are already prescribing similar therapies or who may benefit from adopting your product. Tailored outreach can be more effective when informed by claims data, ensuring that the right message is delivered to the right provider.
- Market Access Strategy: In a complex healthcare landscape, understanding the specific market dynamics—such as reimbursement trends, formulary coverage, and patient access hurdles—is crucial. Claims data can illuminate access gaps, pricing variances, and patient treatment flows, enabling your team to target regions or demographics that may need more focused efforts.
- Optimizing Targeting and Segmentation: Claims data enables hyper-targeted segmentation, whether by disease state, geography, treatment patterns, or patient outcomes. By utilizing claims data to identify the most relevant healthcare providers and patient populations, commercial teams can better allocate resources and tailor marketing efforts.
- Evidence Generation for Health Economics and Outcomes Research (HEOR): Claims data is a goldmine for HEOR teams looking to generate real-world evidence (RWE). By analyzing treatment patterns, outcomes, and costs, claims data can support health economic modeling, demonstrating cost-effectiveness, and strengthening reimbursement negotiations.
Key Use Cases for Claims Data in Life Science Commercial Strategy
Claims data provides a range of use cases that can help life science companies achieve their commercial goals. Here are several key applications:
- Health Economics and Outcomes Research (HEOR)
One of the most powerful uses of claims data is in HEOR analytics. Pharmaceutical companies often rely on HEOR studies to build economic models that demonstrate the cost-effectiveness and clinical benefits of their products. Claims data can support these models by providing real-world insights into:
- Treatment pathways: By analyzing how patients are treated in the real world, HEOR teams can better understand the clinical effectiveness and safety of a product in comparison to others.
- Cost-effectiveness: Claims data can track the total cost of care for patients on different therapies, including hospitalizations, physician visits, and other healthcare services, helping to demonstrate the economic value of a drug.
- Patient outcomes: Claims data can capture important metrics such as hospitalization rates, readmission rates, and disease progression, providing key evidence of a product’s impact on patient health over time.
- Comparative Effectiveness Research
Comparative effectiveness studies are critical for demonstrating how a drug performs in the real world compared to others. Claims data is ideal for this type of research, as it includes a broad range of patient demographics and treatment patterns. By linking patient characteristics with therapy use, you can assess:
- Real-world clinical outcomes: How well does your product perform compared to others in terms of patient health outcomes?
- Treatment adherence: Claims data can reveal whether patients are continuing with their prescribed therapies and any factors that influence adherence.
- Cost and utilization differences: Which treatments are associated with better cost efficiency, fewer side effects, and less resource utilization?
- Provider Outreach Strategy
Claims data enables commercial teams to gain deep insights into how healthcare providers are treating patients. Here’s how it can enhance provider outreach:
- Identifying high-potential providers: By analyzing which providers are already prescribing similar therapies, commercial teams can target their efforts to those who are more likely to adopt new products.
- Understanding provider behavior: Claims data helps identify patterns in prescribing behavior, allowing teams to understand which providers are early adopters, which may be more conservative, and which are willing to try new treatments.
- Optimizing messaging: With insights into the patient populations a provider serves, commercial teams can tailor their outreach to address specific needs—whether it’s through evidence of clinical efficacy or economic benefits.
- Payor Remittance Analysis: Unlocking Reimbursement Insights
Another critical use of claims data is payor remittance analysis. Payor remittance data provides valuable insights into how claims are processed, approved, or rejected by payors. Analyzing this data allows commercial teams to:
- Understand approval rates: By reviewing which claims are approved or denied, commercial teams can gain insights into the overall approval rate for specific drugs or treatments. This can help identify potential barriers in the reimbursement process that need to be addressed.
- Identify rejection reasons: One of the most important aspects of payor remittance analysis is understanding the primary reasons claims are rejected. Common reasons may include coding errors, lack of medical necessity, or issues with documentation. By identifying these trends, commercial teams can work with internal stakeholders (e.g., medical affairs, reimbursement specialists) to address these issues proactively.
- Improve claims submission accuracy: Insights into the rejection reasons can help guide training for healthcare providers or internal teams, ensuring more accurate claims submissions going forward. This can reduce delays in reimbursement and ensure better access to care for patients.
- Optimize payer negotiations: Analyzing remittance data helps commercial teams understand which payors are more likely to approve claims and under what conditions. This insight can be leveraged during payer negotiations to improve reimbursement rates or streamline the approval process for your product.
- Market Access and Reimbursement Strategies
Claims data is essential for developing strategies that improve market access. Here’s how it can help:
- Formulary positioning: By analyzing reimbursement levels and the treatment landscape, you can identify where your product may face challenges in gaining formulary access.
- Payer negotiations: Claims data helps to identify trends in reimbursement, allowing for more effective negotiations with payors.
- Targeted market access campaigns: Use claims data to focus on specific payors or regions where access is limited, and develop targeted strategies to overcome those barriers.
Understanding Different Types of Claims Data
When leveraging claims data for commercial strategies, it’s important to understand when to use different types of data. Claims data can be broadly categorized into closed and open claims, each serving different purposes.
- Closed Claims Data: This refers to claims that have already been processed and are fully adjudicated. Closed claims data provides a historical view of treatment patterns, outcomes, and utilization. It’s particularly valuable for retrospective analyses such as HEOR, comparative effectiveness, and cost-effectiveness studies. Closed claims data also allows you to track long-term patient outcomes and the total cost of care.
- Open Claims Data: These are claims that are still in the process of being adjudicated. While open claims data provides a more real-time view, it may be less reliable for certain types of analyses, as the claims are not yet finalized. However, open claims data is useful for tracking emerging trends, understanding the dynamics of newer treatments, and capturing data on ongoing patient journeys.
- NPI Data: National Provider Identifier (NPI) data is crucial for understanding provider behavior and linking claims to specific healthcare professionals. By incorporating NPI data into claims data analysis, commercial teams can gain a granular understanding of how individual providers are prescribing treatments and serving patients. This data can help in crafting more effective provider targeting strategies.
- Allowed Amounts: Claims data also contains information about the “allowed amount,” which refers to the maximum amount a payer will reimburse for a particular service or treatment. Analyzing allowed amounts can provide valuable insights into pricing dynamics, reimbursement trends, and the economic landscape surrounding specific therapies.
Note many closed claims suppliers have data governance rules that do not provide NPI data and Allowed Amounts information or have limitations on what they can share.
Conclusion: Maximizing Commercial Success with Claims Data
As life science companies navigate an increasingly complex healthcare ecosystem, claims data offers a critical opportunity to drive commercial success. By leveraging claims data for HEOR analytics, comparative effectiveness studies, provider outreach strategies, payor remittance analysis, and market access initiatives, commercial teams can enhance decision-making, optimize targeting, and ultimately achieve business outcomes.
The key to success lies in understanding when and how to use different types of claims data—whether open or closed, integrating NPI and allowed amounts, or targeting specific provider and market segments. With the right strategy and a data-driven approach, claims data can be a game changer for life science companies looking to drive growth and success in today’s competitive market.