Diagnostic Network Optimization
Where Diagnostics Meets Strategy and Innovation
What is DNO
Diagnostic Network Optimization (DNO) is a strategic, data-driven approach to designing efficient diagnostic systems. It identifies where diagnostic tools—such as laboratory instruments, laboratories, and sample transport —should be located and structured to maximize access, improve testing quality, and achieve efficiency goals within limited budgets, particularly in low-resource settings. The process includes assessing current gaps, modeling potential improvements, and developing sustainable sample referral pathways to strengthen patient care and optimize resource use.
Our team of Consultants have:
-
Led the creation of PEPFAR’s Diagnostic Network Optimization (DNO) approach and methodology, forming the basis of most national DNO frameworks.
-
Directed and led the first DNO - Nigeria’s major DNO effort (2018), reducing molecular labs from 27 to 16 and increasing viral load coverage from 58% to 98% within two years.
-
Delivered national DNOs in six countries to guide rational placement of conventional, POC, and near-POC technologies.
-
Supported privatization of Nigeria’s sample transport network and strengthened the National Integrated Sample Referral Network (NISRN) for multi-disease specimen transport, enabling rapid inclusion of COVID-19 and mpox samples.
-
Supported countries in developing and deploying integrated diagnostic strategies across multiple disease areas.
What DNO Does:
-
Analyzes & Models: Evaluates current diagnostic networks (labs, clinics, devices) and builds baseline models.
-
Recommends Placement: Suggests optimal locations for new labs, equipment, and sample collection points.
-
Optimizes Referrals: Creates efficient sample transport routes between facilities (e.g., from clinics to labs) to reduce delays and costs.
-
Increases Access: Ensures more people get timely, quality tests, improving disease control.
-
Guides Investment: Helps decide where to invest limited resources for maximum impact.
Concepts:​
-
Geospatial Analysis: Uses mapping (like ArcGIS, to visualize populations, facilities, and referral flows.
-
Scenario Modeling: Compares different network designs (e.g., adding a new lab, changing transport) to see their impact on access and cost.
Why It's Important:
-
Addresses inequities: Basic diagnostic access, especially in low/middle-income countries.
-
Improves efficiency: Prevents wasted resources and delays in critical diagnoses (like for TB, HIV).
-
Systemic approach: Moves beyond single tools to build resilient, interconnected health systems.
