Scaling for Good

by Jon Scaccia December 16, 2024

Bottom line up front: There are 100s of using public health intervention out there, but these often reach on a fraction of the people they could.

What if there was a way to ensure such solutions could scale up, delivering their life-saving potential to entire populations while minimizing harm? This is the challenge and promise of scaling science—a field dedicated to expanding innovations without compromising their impact. But how do we do it right?

What Is Scaling Science, and Why Does It Matter?

Scaling science aims to ensure that impactful health and social care innovations are systematically expanded to improve outcomes for diverse populations. Unlike traditional approaches that often equate scaling with mere growth or replication, scaling science emphasizes adaptability, equity, and sustainability. It bridges the gap between implementation (how to get innovations adopted) and broad-scale application (how to maximize their impact).

This distinction is critical. While implementation science has laid the groundwork for improving health systems, scaling science takes a step further, addressing questions like:

• How can we ensure that scaled innovations benefit underserved communities?
• What are the unintended consequences of scaling?
• How can ethical considerations guide scaling efforts?

By tackling these questions, scaling science aims to optimize the reach and impact of innovations in the real world.

The Frameworks Guiding Scaling Efforts

To navigate the complexities of scaling, researchers and practitioners have developed frameworks—structured approaches that outline activities, mechanisms, and considerations for successful scaling. A recent scoping review identified 13 such frameworks designed to support health and social care innovations. These frameworks vary in their origins, development processes, and focus areas, but they share a common goal: to make scaling more effective, ethical, and inclusive.

Key Features of the Frameworks:

1. Planning-Centric Design: Most frameworks focus on guiding the planning stages of scaling, emphasizing steps like assessing readiness, mobilizing resources, and ensuring sustainability.
2. Diverse Stakeholder Involvement: Many frameworks include input from funders, policymakers, researchers, and, in some cases, program recipients. This inclusivity helps ensure the frameworks are practical and contextually relevant.
3. Ethical Considerations: A majority use a consequentialist-utilitarian ethical lens, prioritizing outcomes like equity, impact, and sustainability. Grey literature frameworks (those developed outside academic publishing) often incorporate multiple ethical perspectives, making them more adaptable to complex contexts.

How Frameworks Differ: Academic vs. Grey Literature

The scoping review highlighted notable differences between academic and grey literature frameworks:

• Academic Frameworks: Typically rooted in systematic reviews and theoretical models, these frameworks often emphasize rigor and are cautious about generalizability. They are valuable for understanding what has worked in specific contexts but may require adaptation for broader use.
• Grey Literature Frameworks: Created by NGOs and funders, these frameworks prioritize usability and practice. They often include tools like checklists or guidelines, making them immediately applicable to real-world scaling efforts.

For instance, an academic framework might analyze scaling as a theoretical concept, while a grey literature framework might provide a step-by-step guide for scaling a vaccination program in low-resource settings.

Challenges in Scaling Science

Despite their promise, scaling frameworks face several challenges:

• Limited Global Representation: Most frameworks are developed by researchers in high-income countries despite extensive scaling experience in the Global South. This imbalance risks overlooking critical insights from low- and middle-income contexts.
• Insufficient Testing: Many frameworks are still in the development stage, with limited application to real-world cases. This raises questions about their reliability and effectiveness.
• Balancing Rigor and Flexibility: Striking the right balance between evidence-based rigor and adaptability to diverse contexts remains a key challenge.

Practical Applications: How Frameworks Can Transform Public Health

Scaling frameworks have the potential to revolutionize public health by:

1. Enhancing Equity: By prioritizing the needs of marginalized communities, frameworks can guide innovations to where they are needed most. For example, a framework might help ensure a maternal health intervention reaches rural areas with high mortality rates.
2. Improving Sustainability: Frameworks that incorporate long-term planning and stakeholder engagement can help ensure innovations remain effective over time, even in resource-constrained settings.
3. Minimizing Harm: Frameworks that consider ethical implications can prevent unintended consequences, such as inequitable access or cultural insensitivity.

A Hypothetical Scenario: Scaling a Digital Health Tool

Imagine a digital tool designed to help diabetes patients manage their condition. Using a robust scaling framework, health practitioners could:

• Assess the tool’s readiness for different settings (e.g., urban vs. rural communities).
• Adapt the tool’s features to align with local cultural and linguistic needs.
• Plan for ongoing monitoring to ensure the tool improves health outcomes without exacerbating inequities.

What’s Next for Scaling Science?

The future of scaling science lies in addressing its current gaps:

• Decolonizing Scaling: Researchers must actively involve Global South voices, not just as participants but as leaders in framework development.
• Testing and Refining Frameworks: More real-world applications are needed to validate existing frameworks and identify best practices.
• Expanding Ethical Perspectives: Incorporating diverse ethical lenses can help ensure scaling efforts align with both global and local values.

Additionally, scaling science must adapt to new challenges, such as the rise of artificial intelligence (AI). As AI becomes integral to public health, frameworks must ensure its use aligns with principles of equity, transparency, and accountability.

Join the Conversation

Scaling science offers a powerful way to amplify the impact of public health innovations, but it’s a field that thrives on collaboration and dialogue. What are your thoughts on the frameworks guiding scaling efforts? Have you encountered challenges in scaling innovations in your work? How can we ensure scaling efforts prioritize equity and sustainability?

Let’s discuss! Share your insights in the comments or on social media. Together, we can advance the science of scaling for the public good.

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