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|Title:||Cost-benefit analysis of introducing next-generation sequencing (metagenomic) pathogen testing in the setting of pyrexia of unknown origin||Authors:||Chai J.H.
cost benefit analysis
health care system
next generation sequencing
high throughput sequencing
High-Throughput Nucleotide Sequencing
|Issue Date:||2018||Citation:||Chai J.H., Lee C.K., Lee H.K., Wong N., Teo K., Tan C.S., Thokala P., Tang J.W.-T., Tambyah P.A., Oh V.M.S., Loh T.P., Yoong J. (2018). Cost-benefit analysis of introducing next-generation sequencing (metagenomic) pathogen testing in the setting of pyrexia of unknown origin. PLoS ONE 13 (4) : e0194648. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0194648||Abstract:||Pyrexia of unknown origin (PUO) is defined as a temperature of >38.3C that lasts for >3 weeks, where no cause can be found despite appropriate investigation. Existing protocols for the work-up of PUO can be extensive and costly, motivating the application of recent advances in molecular diagnostics to pathogen testing. There have been many reports describing various analytical methods and performance of metagenomic pathogen testing in clinical samples but the economics of it has been less well studied. This study pragmatically evaluates the feasibility of introducing metagenomic testing in this setting by assessing the relative cost of clinically-relevant strategies employing this investigative tool under various cost and performance scenarios using Singapore as a demonstration case, and assessing the price and performance benchmarks, which would need to be achieved for metagenomic testing to be potentially considered financially viable relative to the current diagnostic standard. This study has some important limitations: we examined only impact of introducing the metagenomic test to the overall diagnostic cost and excluded costs associated with hospitalization and makes assumptions about the performance of the routine diagnostic tests, limiting the cost of metagenomic test, and the lack of further work-up after positive pathogen detection by the metagenomic test. However, these assumptions were necessary to keep the model within reasonable limits. In spite of these, the simplified presentation lends itself to the illustration of the key insights of our paper. In general, we find the use of metagenomic testing as second-line investigation is effectively dominated, and that use of metagenomic testing at first-line would typically require higher rates of detection or lower cost than currently available in order to be justifiable purely as a cost-saving measure. We conclude that current conditions do not warrant a widespread rush to deploy metagenomic testing to resolve any and all uncertainty, but rather as a front-line technology that should be used in specific contexts, as a supplement to rather than a replacement for careful clinical judgement. © 2018 Chai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.||Source Title:||PLoS ONE||URI:||https://scholarbank.nus.edu.sg/handle/10635/161234||ISSN:||19326203||DOI:||10.1371/journal.pone.0194648|
|Appears in Collections:||Staff Publications|
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