Themes

Our Themes

Netiv’s research portfolio spans four interconnected themes that collectively advance a novel way of understanding health systems.

Complex Adaptive Systems

People crossing a city intersection from above, illustrating collective movement and interconnected activity.

At Netiv, we understand health systems as complex adaptive systems, composed of networks of people, institutions, technologies, and norms whose behavior emerges from interaction rather than instruction.

Netiv uses complexity science to help health systems see themselves more clearly: how patterns of interaction take shape, how effects propagate, and where learning accumulates or breaks down. This perspective allows systems to move beyond control and compliance toward coherence, adaptation, and sustained performance under uncertainty.


How a Reimagined Command Centre Helps Patient Flow (2025)

Cook, E., Gutberg, J., Rosenberg, L. (2025). How a Reimagined Command Centre Helps Patient Flow. NEJM Catalyst, 6(9), CAT-24. DOI: 10.1056/CAT.24.0437

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Antifragility

A solitary tree growing from cracked rocky ground, illustrating growth through stress and harsh conditions.

For Netiv, antifragility is not about resilience or recovery. It is about designing systems that improve through exposure to stress, variation, and uncertainty.

Health systems continuously face shocks such as workforce strain, demographic change, policy shifts, and technological disruption. Antifragile systems do not simply absorb these pressures; they use them as signals for learning and redesign.

Netiv applies antifragility as a design principle, focusing on structures, governance, and learning mechanisms that enable health systems to gain capability over time, rather than degrade through repeated strain.

Value-Based Healthcare

Healthcare professional holding a patient’s hands during a clinical interaction, reflecting care focused on human outcomes.

Netiv approaches value-based healthcare as a system property, not a reporting framework.

Value is created or destroyed through interactions across the full care ecosystem, not within isolated pathways or performance metrics. Measuring outcomes and costs without understanding system dynamics risks optimizing one part of the system at the expense of another, and collective coherence.

Netiv integrates value-based healthcare with complexity science to anchor learning in outcomes that matter to people and communities, while recognizing the trade-offs, constraints, and interdependencies that shape real-world care delivery.


Implementing the Pillars of Value-Based Care: Leadership Lessons from the CIUSSS Centre Ouest de l’Ile de Montreal (2025)

Gutberg, J., Cook, E., Rosenberg, L. (2025). Implementing the Pillars of Value-Based Care: Leadership Lessons from the CIUSSS Centre Ouest de l’Ile de Montreal. Healthcare Management Forum, 38(3), 206-10. DOI: 10.1177/08404704251317872

Related manuscript

Artificial Intelligence

Zen garden with raked sand, stones, and a small bridge, illustrating balance, structure, and human-guided intelligence.

At Netiv, artificial intelligence is integrated as a foundational capability within health system design, extending system awareness, sense-making, and foresight rather than replacing human responsibility.

AI is used to integrate evidence, data, and lived experience at a scale and pace no individual or committee can achieve alone. Its role is to surface patterns, reveal interactions, and illuminate upstream opportunities, supporting a shift from episodic healthcare toward health, prevention, and early action.

Netiv designs and applies AI in ways that preserve human stewardship, legitimacy, and trust, ensuring that intelligence strengthens understanding and foresight without becoming an authority or an end in itself.

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Knowledge Products

Netiv’s Knowledge Products distill complexity-informed research and real-world system learning into concise, usable formats. Designed to support collective sense-making, they integrate evidence, context, and experience to surface patterns, anticipate implications, and strengthen learning over time.

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“We can’t solve problems by using the same kind of thinking we used when we created them.”

— Albert Einstein