Value of Information Analysis in the Pharmacoeconomic Evaluation of Diagnostic Technologies for Respiratory Viral Infections

Background. Respiratory infections remain a major global health burden with significant economic impact. The di-versity of viral pathogens and variability in diagnostic approaches complicate etiological verification in laboratory practice. As diagnostic technologies evolve, there is a growing need for economically justified approaches that integrate analytical performance, operational characteristics, and costs. Value of Information (VOI) analysis provides a formal framework for evaluating the impact of uncertainty on decision-making.


Objective. To develop and apply a methodology for assessing the cost-utility and value of information of diagnostic technologies for viral respiratory infections from a laboratory perspective.


Methods. The study compared immunochromatographic rapid tests and PCR-based diagnostics for viral infections. Diagnostic utility was quantified using expert elicitation based on four operational criteria: automation, turnaround time, reproducibility, and accessibility. A multi-criteria decision-tree model was constructed, incorporating sensitivity, specificity, diagnostic spectrum, and cost parameters. Uncertainty was modeled using beta and gamma distributions. The framework enabled estimation of expected utility, Net Monetary Benefit (NMB), Expected Value of Perfect Infor-mation (EVPI), and Expected Value of Sample Information (EVSI).


Results. A multi-criteria cost-utility methodology for evaluating etiological diagnostic technologies was developed and applied. Within the defined model, PCR-based diagnostics demonstrated higher expected utility, primarily due to their broader diagnostic spectrum and higher analytical sensitivity. In probabilistic simulations (10,000 iterations), PCR showed an average positive Net Monetary Benefit of approximately $854 per clinical sample compared to rapid tests. VOI analysis indicated low decision uncertainty, with EVPI estimated at $0.25 per patient. EVPPI for the diagnostic spectrum of PCR was negligible, and EVSI reached a maximum of $2.69 at a sample size of 40, suggesting limited addi-tional value of further data collection under current assumptions.


Conclusions. The integration of multi-criteria cost-utility modelling with VOI analysis provides a consistent frame-work for evaluating diagnostic technologies in laboratory medicine. Within the assumptions of the model, PCR-based diagnostics demonstrated higher economic utility compared to rapid tests. However, the results should be interpreted within the defined laboratory perspective and modeling assumptions, including limitations related to the diagnostic spectrum of rapid tests and the absence of downstream clinical outcomes. The proposed approach supports evidence-based and economically justified selection of diagnostic technologies under uncertainty.