Considerations for Group Testing: A Practical Approach for the Clinical Laboratory.

Clinical laboratories typically avoid pooled sample testing due to concerns about diagnostic accuracy. However, the need for efficient testing during the SARS-CoV-2 pandemic has revived interest in this approach. Prior research has shown that pooled testing can reduce reagent use but may compromise sensitivity. No prior work had resolved how to systematically assess which analytes are suitable for pooling. This gap motivated the development of a framework to guide clinical labs in implementing pooled testing. The challenge lies in balancing resource constraints with diagnostic reliability. Traditional methods focus on individual testing, but pooled testing introduces new variables. The pandemic highlighted the urgency of expanding testing capacity without compromising quality. This paper addresses the need for a structured approach to pooled testing in clinical settings.

The study aims to provide clinical laboratories with a practical framework for implementing pooled sample testing. It addresses the challenge of determining which analytes are suitable for pooling and how to execute the process effectively. The motivation stems from the need to conserve reagents during the SARS-CoV-2 pandemic. The authors propose a five-criteria model to evaluate analyte suitability. They also outline five implementation steps for successful pooled testing. The goal is to maximize public health outcomes while minimizing diagnostic risks. This approach allows labs to expand testing capacity without sacrificing essential quality controls. The study focuses on SARS-CoV-2 PCR testing as a case example.

The authors outline a five-criteria model to assess analyte suitability for pooling. These criteria include analyte concentration differences, dilution effects on sensitivity, disease prevalence, turnaround time requirements, and resource rationing needs. They also propose a five-step implementation plan for clinical labs. The steps include determining when pooling occurs, validating protocols, ensuring infrastructure, configuring information systems, and staff training. The methods rely on a combination of theoretical analysis and practical guidelines. No new experimental data is generated; instead, the authors synthesize existing knowledge. The approach is based on prior research in blood banking and diagnostic testing. The authors emphasize the importance of validation and infrastructure readiness.

The five criteria suggest that analytes with a 10-fold concentration difference between diseased and healthy individuals are suitable for pooling. Sample dilution must not significantly reduce sensitivity. Low disease prevalence is essential for effective pooling. Fast turnaround time is not a requirement for pooled testing. Resource rationing is a key driver for implementing pooled testing. The five implementation steps include determining pooling timing, protocol validation, infrastructure readiness, information system configuration, and staff training. The results indicate that pooled testing may broaden access to testing but at the cost of reduced sensitivity. The findings suggest that pooled testing is not a universal solution but can be effective under specific conditions.

The authors conclude that pooled testing may be a viable option for clinical laboratories under specific conditions. The five criteria provide a framework to assess analyte suitability for pooling. The five implementation steps offer a practical guide for labs to adopt pooled testing. The authors emphasize the importance of validation and infrastructure readiness. They suggest that pooled testing is not a panacea but can help conserve resources. The findings indicate that pooled testing may reduce sensitivity and increase turnaround time. The authors propose that pooled testing should be considered when resource rationing is necessary. The conclusions are based on the analysis of prior research and practical guidelines.