Economic Analyses of Respiratory Tract Infection Diagnostics: A Systematic Review

Abstract

Background Diagnostic testing for respiratory tract infections is a tool to manage the current COVID-19 pandemic, as well as the rising incidence of antimicrobial resistance. At the same time, new European regulations for market entry of in vitro diagnostics, in the form of the in vitro diagnostic regulation, may lead to more clinical evidence supporting health-economic analyses. Objective The objective of this systematic review was to review the methods used in economic evaluations of applied diagnostic techniques, for all patients seeking care for infectious diseases of the respiratory tract (such as pneumonia, pulmonary tuberculosis, influenza, sinusitis, pharyngitis, sore throats and general respiratory tract infections). Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, articles from three large databases of scientific literature were included (Scopus, Web of Science and PubMed) for the period January 2000 to May 2020. Results A total of 70 economic analyses are included, most of which use decision tree modelling for diagnostic testing for respiratory tract infections in the community-care setting. Many studies do not incorporate a generally comparable clinical outcome in their cost-effectiveness analysis: fewer than half the studies (33/70) used generalisable outcomes such as qualityadjusted life-years. Other papers consider outcomes related to the accuracy of the test or outcomes related to the prescribed treatment. The time horizons of the studies generally are limited. Conclusions The methods to economically assess diagnostic tests for respiratory tract infections vary and would benefit from clear recommendations from policy makers on the assessed time horizon and outcomes used.Simon van der Pol and Paula Rojas Garcia contributed equally to the article.

Health-Economic Analyses of Diagnostics: Guidance on Design and Reporting

“…We recently systematically reviewed many CEAs of diagnostic strategies of infectious disease, focusing on the modelling techniques used [13,14]. In the process, we identified several gaps in the reporting of diagnostic interventions, but also common structural problems related to the design of health-economic models.…”

“…• Screening: Finding diseases in a defined population, in people without, or unaware of, symptoms [18]. • Diagnosing: Identifying the most likely cause of, and, optionally, optimal treatment for, a previously undetected disease in a clinically suspect patient who is seeking care [13,19]. A diagnostic specifically aimed at determining the optimal treatment option for a patient with a previ-ously diagnosed disease is considered a companion diagnostic [5].…”

“…The decision problem must be fully and accurately described in identifying the most suitable treatment. These types of algorithms are already very common in economic analyses, where they translate into decision-tree models [13,14,26]. For diagnostic algorithms that include many different outcomes, i.e., a decision tree branching out to hundreds of outcomes, simplifications may be warranted or more flexible modelling approaches can be considered [27].…”

“…Generally, a lifetime horizon should be used [16], however there could be reasons to have a shorter time horizon but they should cover all relevant costs and outcomes. Economic analyses only assessing a time horizon as long as the diagnostic process, as seen rather frequently in literature [13], will in most cases not cover all relevant costs and outcomes. The time horizon should be similar to the time horizon over which costs and consequences of treatment following the diagnostic process are typically evaluated.…”

“…It is common to compare various diagnostic algorithms simultaneously within a CEA [13], as explained above. The different algorithms may not only contain different diagnostic techniques but may also be performed in different sequences or at different locations (e.g., at the POC or in a laboratory).…”