Diagnostic network design & optimization
GOAL: Use local data to design context-specific testing strategies and implementation models
Designing optimal diagnostic systems is complex and highly context-dependent, relying on multiple data inputs and assumptions. Important variations in epidemiology, geography and health systems – often within the same country – must also be accounted for, as well as budgetary considerations. Diagnostic network optimization takes a geospatial network analytics approach, used in many manufacturing industries, to improve patient access to services in the most cost-efficient way. Using data to inform instrument placement, sample transportation, referral mechanisms, staffing, and geographical prioritization, diagnostic access can be increased for those most in need, while also ensuring cost efficiency and feasibility. Data can also inform integration of diagnostic tools and services (such as testing for COVID-19 using molecular diagnostics already in place for TB), to provide patient-centred services and resource allocation across heath sectors and programmes. Together with other approaches to support countries to identify gaps and develop tailored interventions, such as patient pathway analysis and structured assessments, diagnostic network optimization can help target the right mix of diagnostic solutions to where they are needed most, at costs sustainable for health systems, and is able to rapidly adapt to emerging
threats.
Our focus is on helping countries to build and maintain comprehensive, integrated digital network models that are coordinated and owned by Ministries of Health and used by all partners, with common standards for data collection, reporting and data management.
Workstreams:
- Optimize use of current diagnostics through diagnostic network optimization that can inform countries’ strategic plans, as a routine element of health systems and supported by sustainable funding mechanisms
- Inform introduction of new diagnostics by using diagnostic network optimization to compare cost-effectiveness of different implementation models and understand decision drivers for use of new tests in different settings
- Expedite testing strategies for new/emerging diseases by ensuring they are informed by rapid deployment of diagnostic network optimization analysis, using pre-existing network models
Indicative deliverables:
- Pilot in 4 countries and launch OptiDx, an open-access software for conducting diagnostic network optimization across diseases in LMICs
- Scale up use of OptiDx and establish diagnostic network optimization as a key element in country strategic planning and investment decisions for at least 2 donors in laboratory systems strengthening
- Enable at least 20 countries to optimize multi-disease molecular testing networks to improve access and deliver efficient and sustainable services
- Inform design and optimization of surveillance networks for at least 2 diseases in at least 1 region
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