Unlocking longitudinality: How hybrid claims data transforms RWE/HEOR studies

Insurance claims data have long been a trusted source for generating robust real-world evidence (RWE). Yet in RWE and health economics and outcomes research (HEOR), tracking patients consistently over time remains a major challenge. Closed claims provide rich payer-specific detail but lose visibility once patients change jobs, insurers, or plans, leaving gaps in their healthcare record. Open claims, sourced from clearinghouses and providers, can help bridge these gaps.

In this Guest Column in partnership with Forian, Wouter van der Pluijm and Mike Sicilia explore how hybrid claims data that integrates both open and closed sources can extend patient journeys, strengthen longitudinal analyses, and improve the quality of RWE and HEOR.

For researchers in RWE and HEOR, the ability to track comprehensive patient journeys over time is paramount. Yet a persistent challenge has been the limited patient longitudinality of closed claims datasets. Once patients change jobs, switch insurance payers, or transition between plans, they often drop out of the dataset. This creates data gaps that limit the validity of the study. 

Hybrid claims data, which integrates open and closed claims, offers a powerful solution.

“By extending the continuity of patient histories across payers and over time, hybrid datasets enhance study robustness and expand the scope of longitudinal analyses.”

The challenge of longitudinality in closed claims

Closed claims datasets have traditionally served as a cornerstone of RWE and HEOR studies. However, their reliance on enrollment with a single payer creates substantial limitations. Once a patient was no longer enrolled with the same payer, subsequent healthcare encounters were no longer captured, and pre-enrollment history became unavailable. This "data black hole" can significantly impact the robustness and generalizability of RWE/HEOR studies.

Two key trends underscore the impact of this limitation:

1. Job mobility and insurance changes: According to a 2024 Bureau of Labor Statistics report, the average American worker stays at their job for 3.9 years, a 15% decrease over the past decade. Each transition often involves a change in health coverage, leading to discontinuities in claims data. We must also account for annual intra-company payer and plan switching.
2. Patient turnover in commercial insurance: A University of Pennsylvania study published in JAMA (2022) found that 2.2% of commercial enrollees transitioned externally each month, amounting to a staggering 21.5% annually.

As a result, more than one-fifth of patients are lost to follow-up in commercial closed claims datasets each year. For studies assessing treatment effectiveness, disease progression, and healthcare utilization, such attrition significantly weakens the ability to generate long-term, statistically significant insights.

Expanding patient history with hybrid claims data 

Hybrid claims data addresses key limitations of traditional closed claims by combining them with open claims sourced from clearinghouses and provider submissions. This approach provides a more comprehensive view of patient healthcare encounters, maintaining continuity even when patients transition between insurance plans or payers. By capturing both pre- and post-enrollment activity, hybrid data extends the patient journey beyond the confines of closed claims alone.

This longitudinal depth not only bridges data gaps in patient histories, but also strengthens research quality. Longer observational periods and larger, more complete patient cohorts increase the statistical power of studies, enabling more reliable insights. Together, these advantages position hybrid claims data as a critical resource for understanding patient care trajectories and outcomes.

The overlap between open and closed claims datasets is substantial. Often, more than 80% of patients in closed datasets can also be found in large open claims sources. The same patients who have claims paid by specific commercial insurers (closed claims) also have those same claims routed by the provider to that payer and back for provider reimbursement (open claims). This claim-level overlap enables encounter validation, data granularity, and longitudinal extension.

Forian’s hybrid claims data ecosystem, CHRONOS™, demonstrates the impact of hybrid claims integration. Between 2021 and 2023, CHRONOS™ achieved a 95% overall linkage rate between open and closed sources (95% of patients in the closed claims data also existed in the open). 

Between 2021 and 2023, open claims consistently added extra months of patient capture, with around one in five patients having pre-enrollment history, a similar proportion with post-enrollment history, and nearly one in ten with both.

Additional patient capture from linked open medical claims, by year.

Pre-enrollment: The period before the patient’s continuous enrollment in closed claims; Post-enrollment: The period after the patient’s continuous enrollment in closed claims.

A similar analysis of pharmacy claims showed slightly less overlap (in the mid-70% range), with higher pre- and post-enrollment capture rates.

Additional patient capture from linked open pharmacy claims, by year.

These findings highlight the extent to which open claims extend patient histories beyond closed enrollment, yielding a more complete and clinically relevant view. The magnitude of this benefit, however, is not uniform. Different therapeutic areas present unique challenges and utilization patterns. Exploring these differences is a vital next step in demonstrating the full value of hybrid claims integration. The degree of added visibility varies by therapeutic area, underscoring the importance of disease-specific analyses. 

To evaluate these types of trends at the therapeutic level, we ran the same analyses for three distinctly unique diseases, metabolic dysfunction-associated steatohepatitis (MASH, formally known as NASH), ALS, and cholangiocarcinoma (bile duct cancer), for the same timeframe. Breakouts by therapeutic area for medical and pharmacy longitudinal data revealed higher percentages than in the overall CHRONOS™ dataset, particularly for conditions such as MASH and ALS, where patients tended to have more frequent healthcare encounters.

Additional patient capture from open claims, by therapeutic area (medical).

Additional patient capture from open claims, by therapeutic area (pharmacy).

During this analysis, it was noted that the disease-specific tables showed higher percentages compared to the full CHRONOS™ dataset. This likely reflects the fact that patients in these disease groups tend to be more severely ill and therefore have more frequent healthcare encounters, both within and outside the closed network. These findings underscore the importance of utilizing hybrid data ecosystems to capture a fuller picture of patient activity and to enable more accurate longitudinal analyses, especially at the indication-specific level.

Further analysis by therapeutic area revealed differences in average and median pre- and post-enrollment capture. On average, patients gained more months of pre-enrollment history than post-enrollment follow-up – a pattern consistent with earlier disease-specific findings.

Average and median months of pre- and post-enrollment data capture, by disease.

When applying this more stringent criteria, requiring evidence from both medical and pharmacy claims, the results still demonstrated meaningful gains. This clearly demonstrates how integrating open and closed claims can yield substantial additional months of data for the same patients, enabling a richer longitudinal view.

Implications for RWE and HEOR research

For researchers, hybrid claims data represents more than an incremental improvement. It is a structural shift that directly addresses the limitations of traditional closed claims. 

Benefits include: 

• Richer, more complete datasets: Access to a more comprehensive view of patient care, regardless of insurance changes.
• Enhanced outcomes measurement: The ability to track long-term effects, adherence, and healthcare resource utilization over extended periods.
• Stronger evidence generation: Extended longitudinality improves confidence in study conclusions that can truly influence healthcare decisions and policies.

Embracing hybrid claims data is not just an incremental improvement; it's a transformative approach that addresses a fundamental challenge in real-world data analysis. As demonstrated in Forian’s CHRONOS™, this approach significantly extends patient histories, strengthens study power, and paves the way for more impactful evidence generation. 

“The integrated approach of combining open and closed claims not only improves the accuracy and robustness of analyses, but also supports more equitable, patient-centered insights. As hybrid data ecosystems progress, they will become an essential foundation for next-generation RWE and HEOR studies.”

Authors

Michael Sicilia
RWD Data Scientist, Forian, Inc.

Michael Sicilia is a RWE Data Scientist at Forian, Inc., where he designs and conducts real-world evidence studies. Prior to joining Forian in 2024, Michael was at EVERSANA where he implemented complex outcome, economic, burden-of-illness, and machine learning analyses on rare disease patient populations. In total, he has over 5 years of experience in the real-world data/evidence space and holds a bachelor’s degree in Computer Science.

Wouter van der Pluijm
Vice President of Market Insights & Solutions, Forian, Inc.

As the Vice President of Market Insights & Solutions, Wouter works extensively with Forian’s real-world data ecosystem. His responsibilities range from identifying and integrating new data sources to scoping and delivering analytic and evidentiary solutions to Forian clients.

Wouter has worked in the real-world data space for over a decade, having roles in sales enablement, integrated solution design, as well as forecasting and evidence generation. Combined with his experience as an epidemiologist, Wouter brings a balance of both clinical and commercial experience in supporting Forian’s clients across the Life Science and Healthcare landscape. Prior to joining Forian, Wouter spent 7 years at DRG/Clarivate and worked at the local public health level as an Epidemiologist. He holds an MPH in Epidemiology from the University of Michigan.