Riverside Health

Jason Kilgore

Organizational Intelligence Champion

Jason Kilgore is Senior VP of Strategy and Analytics at Riverside Health, where he oversees enterprise strategy, payer strategy, business development, data science and process improvement. He leads work that aligns long-term growth with market dynamics, strengthens payer relationships, supports value-based care and improves system-wide performance.

Previously, Jason served as VP of results management and analytics, building a cross-functional team across data science, process improvement and operational research. He began his career at Continental Automotive Systems, formerly Siemens AG, in engineering, operations and program management, earning more than 25 U.S. and international patents in automotive fuel systems. He holds a degree in mechanical engineering, an MBA in finance and is pursuing a doctorate in systems engineering.

Healthcare organizations have more data today than ever before. Every patient encounter, physician referral, insurance claim, quality measure and operational process generates vast amounts of data. At the same time, organizations are investing heavily in data storage, artificial intelligence and advanced analytics capabilities. Oftentimes, the assumption is that more data and better technology will naturally yield better decisions.

Unfortunately, it is not quite that simple. There are three components that power strategic decision-making: data science, industry research and subject matter expertise. While none of these creates a sustainable competitive edge on its own, an advantage emerges when these capabilities are intentionally leveraged to deliver a robust enterprise strategy. In my role, I have come to appreciate that the most important asset in healthcare analytics is not data itself but rather the ability to transform information into understanding and understanding into action. This capability is often referred to as organizational intelligence.

Organizational Intelligence Begins with Data Science

It is the responsibility of a robust data science function to identify patterns that would otherwise remain invisible. Healthcare leaders are frequently forced to make decisions in environments characterized by uncertainty, incomplete information and competing priorities. Waiting for perfect data is almost never an option because decisions are time-sensitive and data mining is often akin to the never-ending search for the holy grail.

Instead, successful organizations must learn how to triangulate multiple sources of information to develop a sufficient understanding of the current state. Data science enables organizations to identify patterns at a much more fundamental level than traditional reporting. It transforms fragmented, multifactorial data into meaningful insights, including service-line opportunities, predicted demand, payment probability and clinical outcomes.

Industry Research Provides Context for the Data

Identifying patterns is just the beginning. Patterns without context can be misleading, often misrepresenting correlation as causation. This is where extensive healthcare-specific industry research becomes essential. Research provides a broader perspective and a theoretical framework for properly interpreting sophisticated algorithmic outputs.

Market intelligence, competitive analysis, consumer research, demographic studies and environmental scanning help organizations clarify analytical findings with an added layer of precision that analytics alone cannot provide. For example, an analytical model might predict an increase in demand for a particular service. The research layer assesses the extent to which demand is driven by population growth, changing consumer preferences, physician shortages, competitive disruption, or some combination of these factors. Understanding what drives the trend is just as important as recognizing the trend itself.

“The most important asset in healthcare analytics is not data itself but rather the ability to transform information into understanding and understanding into action. This capability is often referred to as organizational intelligence.”

Just as data science reveals patterns and industry research provides context, expertise generates judgment.

This may be the most underappreciated component of organizational intelligence. Healthcare is a remarkably complex industry. Algorithms can identify relationships within data, but they cannot fully understand the practical realities of clinical care or community expectations. Those insights come from experienced clinicians, operators and strategists. The most valuable decisions are not guided solely by algorithms and qualitative analysis. They are made when all the available information is synthesized through the lens of practical expertise.

AI can process information faster than ever before. It can uncover relationships that humans might miss and dramatically reduce the time required to gather and summarize market research. Yet AI does not eliminate the need for lived experience. If anything, it increases the importance of critically evaluating what AI produces. Organizations must identify and employ experts who can ask the right questions, challenge the status quo and translate insights into action.

Strategic advantage exists at the intersection of data science, industry research and subject-matter expertise.

This intersection is becoming increasingly important as artificial intelligence gains traction across healthcare. While AI is attracting significant attention, its greatest value may not lie in automation alone. Its greatest value may be its ability to accelerate the development of organizational intelligence. Ultimately, the purpose of organizational intelligence is not to create better dashboards or more sophisticated models. It is to improve strategic decision-making and navigate constant change.

Health systems that successfully accelerate the development of their organizational intelligence capabilities gain a significant advantage. They identify opportunities sooner. They recognize risks earlier. They allocate capital more effectively. They adapt more quickly. Most importantly, they are well-positioned to fulfill their mission of serving their patients and communities.