Specialised toolkit: Laboratory services

Documented review of current laboratory practices and operating models that inform outsourcing

Diagnostic network optimisation for laboratory services6

A diagnostic network optimisation approach focuses on developing a baseline understanding of the testing network, including capacity and equipment utilisation, and exploring more efficient options. A diagnostic network optimisation approach is the entry point to inform outsourcing decision-making and implementation

A diagnostic network optimisation approach achieves:

  1. Laboratory network optimisation: fully engaged stakeholders and proactive data collection and visualisation allow countries to optimise the network.
  2. Forecasting and supply planning: institutionalising collaboration among stakeholders and data best practices for future planning.
  3. Procurement and strategic sourcing: reduce procurement risks and increase pricing transparency, leading to cost savings and improved quality of services.
  4. Performance management: establishing performance indicators promotes standardisation, improved information sharing among stakeholders and better functioning equipment.


The Diagnostic Network Optimisation provides the foundation for an equipment rental model and a functional sample referral network. Importantly, the ministry of health choice of model is informed by the outcomes of the Diagnostic Network Optimisation approach.

Laboratory equipment rental model (all-inclusive)

The laboratory equipment rental model is also known as the reagent rental model. The laboratory equipment rental model of procurement means the ministry of health rents equipment with an all-inclusive per test cost structure. This means a single price per test is paid that includes reagents, controls, equipment, and servicing, usually linked to planned volumes over a defined period. The laboratory equipment rental model offers an all-inclusive per test cost structure spread across all instruments of the same brand within the laboratory network and made available to all stakeholders in the network. Thus, the model permits the leasing of specialised laboratory equipment by ministries of health through longer-term rental agreements or ‘placement contracts’. Equipment is placed at a central laboratory/s for use. It was piloted in the early 2000s as an alternative to purchasing equipment outright for highly specialised testing, such as viral load testing, and remains popular.

The benefits include:

  • All necessary supplies, tests, machinery, training, and maintenance are accessed through one source (manufacturer).
  • A lower predictable price per test.
  • Incentivises maximum equipment use.
  • Reduces the risk of equipment maintenance and servicing being de-prioritised.
  • Greater coordination and sharing of risk between buyers and suppliers.
  • Inclusive of consumables, service, maintenance, and (in some cases) vendor managed inventory.
  • Placement of equipment in testing laboratories.
  • Data solutions for patient result transmission, instrument, or user performance – informing the Viral Load Dashboard.
  • Network staff training and consistency.
  • More accurate budgeting and procurement monitoring.

The challenges and risks are:

  • Rental agreements may include high volume conditionalities.
  • Local distributors must adhere to pricing arrangements.
  • Equipment must be returned in good condition at the termination of the agreement.
  • May create a dependence on a single source of supply.

There are notable differences in price, performance, and risk between traditional and rental models, as outlined below. The equipment rental model offers more predictable cost forecasting for ministries of health’s and diverts procurement risk to suppliers.

Hub and spoke model for the specimen referral network9

Non-standardised, parallel specimen transportation systems with long turnaround times remain a challenge to achieving optimised laboratory networks. Through Diagnostic Network Optimisation, the hub and spoke model forms a more reliable and optimised specimen referral network. Specimens are collected from peripheral laboratories (‘spokes’) and transported to a central coordination and processing facility (the ‘hub’). Hubs are strategically located with geographic catchment areas and perform a variety of functions. Within the Diagnostic Network Optimisation lens, the hub and spoke model seeks to consolidate specimen referral networks into more optimised, reliable, and functional centralised ‘hub’ designs for improved transportation and diagnostic outcomes.

Hubs act as the coordination centre of a sub-district network: tracking, receiving, storing, and performing analysis of referred specimens from peripheral laboratories within catchment areas of a 40- to 50-kilometre radius. They make specimen referrals to higher-level facilities if required. Hubs must meet minimum requirements, including sufficient laboratory equipment, functional logistics and supply chain management systems, enhanced laboratory personnel, improved biosafety, biosecurity, and quality assurance systems. Often, these requirements are sourced from third-party logistics vendors providing requisite experience, equipment, and human resources to collect and deliver samples. Through the Diagnostic Network Optimisation approach, Nigeria and Uganda have designed and implemented hub and spoke models: the National Integrated Specimen Referral Network (NISRN) and the National Sample and Results Transport Network (NSRTN), respectively. Both have slightly different applications to outsourcing.

The benefits include:

  • A functional network approach to vast geographies.
  • Cuts across all sample types – not disease programme-specific.
  • Optimises use of available personnel and installed equipment capacity.
  • Reduces turnaround times which improves the quality of diagnostic services.
  • Reduces long-term costs associated with specimen transportation.

The challenges and risks are:

  • Challenges in scale-up of pilot projects.
  • Some hubs operate at optimal levels versus others running sub-optimally.
  • The network requires efficient systems for communication, coordination, and data or information management.

6Source: USAID Global Health Supply Chain Program-Procurement and Supply Management (GHSC-PSM); Williams J, Edgil D, Wattleworth M, Ndongmo C, Kuritsky J. The network approach to laboratory procurement and supply chain management: Addressing the system issues to enhance HIV viral load scale-up. Afr J Lab Med. 2020;9(1), a1022. https://doi. org/10.4102/ajlm.v9i1.1022.

7Sources: USAID PSM-GHSC. Laboratory Network Optimisation and All-Inclusive Reagent Rental Strategies https://slmta.org/uploads/category_file/69/5.6%20Expert%20Panel%20%233%20-%20The%20Solution%20by%20Clement%20Ndongmo.pptx.pdf Kiyaga C, Sendagire H, Joseph E, McConnell I, Grosz J, et al. 2013. Uganda’s New National Laboratory Sample Transport System: A Successful Model for Improving Access to Diagnostic Services for Early Infant HIV Diagnosis and Other Programs.

8Source: USAID Global Health Supply Chain Program-Procurement and Supply Management (GHSC-PSM)

9Source: Interviews for the Toolkit for Outsourcing Laboratories Services, November 2020; Kiyaga C, Sendagire H, Joseph E, McConnell I, Grosz J, et al. 2013. Uganda’s New National Laboratory Sample Transport System: A Successful Model for Improving Access to Diagnostic Services for Early Infant HIV Diagnosis and Other Programs.