Komodo Health is a technology company that specializes in transforming the complex, fragmented landscape of U.S. healthcare data into actionable insights. The company leverages large-scale patient information, known as “real-world data” (RWD), to help reduce the global burden of disease. This approach analyzes how treatments and diseases manifest in everyday patient populations, moving beyond traditional scientific studies. By pairing this expansive data set with advanced software and artificial intelligence, Komodo Health provides evidence-based decision-making across the healthcare industry.
Defining Healthcare Claims Data
Healthcare claims data represents the records generated when a healthcare provider bills a payer, such as an insurance company or a government program, for services rendered to a patient. This data is a structured, codified artifact of a patient’s interaction with the medical system. Each claim contains specific diagnostic codes (like ICD-10), procedural codes (like CPT), and information about prescription drugs dispensed.
The claims record also captures details about the service location, the type of provider involved, and the date of the encounter. Because this data is generated as part of the financial transaction of care, it provides a consistent lens into patient journeys and disease prevalence across broad populations. This administrative data is foundational for understanding patterns in utilization, cost, and the sequence of care a patient receives over time.
The Komodo Healthcare Map
Komodo Health’s proprietary asset, the Healthcare Map, is a database that aggregates and links patient encounters from hundreds of disparate sources across the United States. It represents the patient journey for over 330 million individuals, covering nearly the entire U.S. population. The map is constructed by merging data from sources that include medical claims, pharmacy claims, lab results, and, in some cases, genomic information.
This comprehensive linkage allows researchers to follow a de-identified individual’s path through the healthcare system over many years. The map is a unified data set that connects various encounter points, eliminating the silos that traditionally separate information between different providers and payers. For instance, it can show a patient’s primary care visit, specialist referral, lab work, diagnosis, and prescription fulfillment, regardless of the insurance plan or provider they used. This integration provides a foundation for advanced health analytics and artificial intelligence applications.
How the Data Drives Medical Decisions
The insights derived from the Healthcare Map serve a diverse set of users, including pharmaceutical companies, payers, and government health agencies. Life sciences organizations utilize the data to optimize the design and placement of clinical trials. They identify specific patient cohorts and provider locations with a high concentration of relevant patients, which accelerates the development timeline for new therapies.
The data is also applied to understand the real-world effectiveness of treatments, a field known as Health Economics and Outcomes Research (HEOR). Researchers analyze treatment adherence patterns and measure patient outcomes following a new drug’s launch to demonstrate its value beyond controlled clinical settings.
Payers and providers use the map to identify unmet patient needs, helping them close gaps in care for chronic conditions or better understand disease progression in rare disorders. By tracking payer dynamics, such as coverage restrictions and policy criteria, the data also informs market access strategies, ensuring new therapies are accessible to patients.
Privacy and Security Standards
Komodo Health operates under a framework of privacy and compliance to protect patient identity. All data used to populate the Healthcare Map is de-identified and anonymized, meaning it cannot be traced back to an individual person. The company adheres to federal standards, including the Health Insurance Portability and Accountability Act (HIPAA), which governs the use and disclosure of protected health information.
The process of de-identification is technologically rigorous, ensuring patient privacy is maintained before the data enters the analysis platform. A third-party technology is often used to securely link these datasets, allowing for the creation of a longitudinal journey while preserving anonymity. This allows for the aggregation of thousands of patient records to generate large-scale, population-level insights.