Adding New Dimensions to HEOR Research With Linked RWE Datasets

2024 ISPOR Posters Show the Power of Linked Data in Action

Health economics and outcomes research (HEOR) is a world of what-ifs. What if patients experiencing certain combinations of side effects were more or less likely to discontinue use? What if patient demographics or social determinants were creating barriers to care? What if treatment protocols changed and not all providers were aware of that change? These are the types of questions that keep HEOR teams up at night. It’s what pushes them to spend millions on real-world evidence (RWE) datasets that can give them a window into the myriad of behavioral, clinical, and socioeconomic variables influencing adherence.

Along the way, reconciling this data has become one of the biggest challenges. According to our recent benchmarking study tracking the state of data mining in Life Sciences, the biggest single hurdle — cited by 59% of HEOR professionals as a “significant” or “very significant” challenge — is linking claims data to specialty datasets. In their quest to understand the detailed nuances of the patient experience — not just a one-dimensional snapshot of diagnosis and treatment, but the complete constellation of intertwined variables — HEOR teams cobble together disparate specialty datasets. These can often include a mix of claims, lab, diagnostics, genomics, and census data. They then need to spend months cleaning and integrating before they can even start an analysis.

Not only are we deepening the visibility of our Healthcare Map™ with MapEnhance™ , but we achieve a high overlap with these specialty datasets resulting in the highest patient counts of the desired patient population. By bringing all these data assets together on a single platform, we’ve made it possible to add more depth, dimension, and visibility into clinical encounters and patient populations from a single, fully integrated solution. 

Now, we’re starting to see the results of that thesis in action. Researchers from Komodo Health have 12 poster presentations at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2024 conference that showcase the power of linked RWE datasets to add entirely new dimensions to HEOR. Komodo data is also powering an additional 20+ studies by our partners. The studies, which address a variety of HEOR use cases, including detailed cohort analyses for therapeutic areas without corresponding ICD-10 codes, the effects of changes to clinical safety standards, and the influence of racial disparities. These studies demonstrate the value of linking datasets through Komodo’s MapEnhance solution to uncover previously unseen insights. 

Here's a closer look at the research:

• Mapping Cohorts Without a Code: In this study, Validation of an Algorithm to Identify HR+/HER2- Metastatic Breast Cancer in Claims Data, genomics data from NeoGenomics linked to Komodo’s Healthcare Map was used to identify the key diagnostic and genetic variables consistent with HR+/HER2- metastatic breast cancer (mBC), the most common breast cancer subtype. Because there is no specific ICD-10 code for this condition, researchers have developed algorithmic models to identify patient cohorts. This study validated those existing algorithms by demonstrating a high degree of accuracy in identifying HR+/HER2- mBC patients.
• Assessing Outcomes Following Changes to the Standard of Care: This study, Changes in Neutropenia Outcomes Following Implementation of the Clozapine Risk Evaluation, evaluated the effects of a 2019 update by the U.S. Food and Drug Administration (FDA) to Clozapine Risk Evaluation and Mitigation Strategy (REMS), a safety program focused on managing the risk of severe neutropenia associated with clozapine treatment. Drawing on data from the Komodo Research Dataset linked to Komodo Lab Results data, the research found an increase in mild neutropenia among clozapine users following the FDA update, which may reflect the program’s intention of earlier detection of neutropenia.
• Race-Based Disparities in Breast Cancer Care Following the Pandemic: While it is well-documented that the COVID-19 pandemic highlighted race-based disparities in care, very little research has been done to assess whether or not that phenomenon has extended to breast cancer care. The study, Breast Cancer–Related Healthcare Resource Utilization and Staging Before and After the COVID-19 Pandemic Among White and Black Patients With Newly Diagnosed Breast Cancer, tackled that issue by using the Komodo Research Dataset and our Healthcare Map to identify potential gaps in breast cancer care. It found significant differences in care by race both pre- and post-pandemic.

Together, these are part of the 32 posters being presented at ISPOR 2024 that leveraged Komodo Health’s industry-leading insights and data products. These analyses addressed a wide range of HEOR use cases and shed new light on important population health trends. Perhaps more importantly, however, they demonstrate how, by seamlessly linking diverse datasets on a single research platform, HEOR teams can unlock truly multidimensional, highly nuanced views of patient journeys — without the huge time investment in wrestling with disconnected, incomplete, or inaccurate datasets.

To read more peer-reviewed studies powered by Komodo Health, visit our bibliography.