For many, the path through health, diagnosis, and treatment is complex. An individual patient’s journey can see them seeking care at many different places, undergoing multiple rounds of testing or treatment, and experiencing a wide range of health outcomes — the positive and the not-so-positive. Through each step in this journey, patients generate data that, when analyzed at a population level, reveal patterns that help us better understand trends in disease, treatment, and coverage. This real-world evidence (RWE) powers the insights that transform patient care.

At Komodo Health, we’re guided by our mission to reduce the burden of disease and our vision to accelerate insights through high quality data and technology. During The One Day Summit, we spent time with Life Sciences leaders to explore what the future of healthcare could look like if we were to harness the power of data and technology to its full potential — with a foundation of patient-centered insights at its core.

Shifting to a patient foundation of insights
Komodo CEO and Co-Founder Arif Nathoo, MD, opened The One Day Summit with an overview of the legacy model for Life Sciences data and analytics. For the last 40 years, analysts have counted prescriptions and measured fills, with a particular focus on high-prescribing providers. They’ve viewed reach and frequency of engagement with pharmaceutical product ads as mainstay metrics for tracking drug utilization, which they have used to inform marketing strategies and clinician engagement plans. Today, this model is changing. 

“We’re in the middle of a transformation, where the patient is at the center of the analytic model,” Arif said. In rare diseases, for example, we now use patient-level data to understand the experiences that patients go through to reach their diagnoses. In oncology, patient-journey insights help us learn about lines of therapy and responsiveness to treatment. And in general medicine, we’re using payer and patient demographics data to identify areas of unmet need. 

Following this transformation, Life Sciences teams have experienced challenges in scaling robust data and technology tools across their companies. Due to siloed workstreams, teams across an enterprise may invest in datasets that another team had already purchased or licensed. Then, the fit-for-purpose insights from that data is difficult to share and often goes underutilized. Add to this the fact that insights are rarely timely, because in the old model, Life Sciences teams had to undertake a time-intensive and costly process to combine, clean, and analyze disconnected data, with outputs reported in PowerPoint slides that would immediately be stale upon delivery. This broken insights workflow ultimately leads to missed opportunities to engage the right doctors at the right times. All of this leads to subpar outcomes for both patients and Life Sciences companies.  

Enabling deeper insights with better-quality data and full-stack analytics
Komodo set out nine years ago to up-end the legacy approaches in Life Sciences and create a new way to organize and leverage patient journeys to speed time to insights. At the foundation of this is Komodo’s Healthcare Map™. The Map provides the industry’s most comprehensive view of healthcare costs and outcomes in the U.S., bringing together a wide range of data types and sources and is truly representative of the U.S. population. With such breadth and depth of information, the Healthcare Map enables speed and value by acting as a single source of truth for all data-driven decisions and integrates enterprise-wide to consolidate data into a unified asset that all teams can use. When layered with artificial intelligence (AI) models and other analytics capabilities, the Healthcare Map serves as the foundation of insights for Komodo’s full stack of analytics and software solutions.

Arif also shared new and future updates to the Healthcare Map that will enhance Life Sciences’ ability to drive even more accurate and powerful insights:

• Our commitment to high-fidelity data in our Healthcare Map means integrating new, diverse data sources and continuously refining our methodologies to deliver the most comprehensive view into real-time, real-world patient journeys nationwide.
• As part of our MapEnhance offering, the Healthcare Map now seamlessly integrates a network of specialty data partners that provides customers with access to a multidimensional, real-world view of clinical events and patient populations at a level of resolution not previously available.
• Our detailed quality approach delivers unparalleled accuracy of data, resolving the many errors inherent in tokenization to ensure the accuracy of the patient’s interactions reflected in the data. 

With these and other innovations, Arif said, the Healthcare Map is expanding the foundation from which Life Sciences partners can advance patient data within their own organizations. Rather than contracting with various legacy aggregators, Life Sciences teams can leverage a uniform method for RWE generation across an enterprise, driving insights that will change the game for patient access to medication. 

One Day: Transforming healthcare with real-time insights
Arif sees the industry at an inflection point for patient centricity. By harnessing the vast amount of data generated from routine healthcare interactions every day and integrating new AI and machine learning technologies, we can improve outcomes and move from a one-size-fits-all care approach to one that is personalized and tailored to each patient. 

Arif closed with his One Day vision: “With the Healthcare Map as a foundation, we have an opportunity to transform healthcare. To put the patient at the center of their care with granular, real-time insights and personal engagement. To change the paradigm from the way we used to do things and focus on just-in-time engagement. To elevate the care we provide to patients and the options we’re able to give them.”

about the in-depth discussions at Komodo's The One Day Summit, where we explored how technology is shaping the future of healthcare — one day.

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