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Cost implications for the NHS of using the Alere™ i Influenza A & B near patient test with nasal swabs

Lookup NU author(s): Dr Joy Allen, Rachel O'Leary, Dr Sara Graziadio, Dr William Jones, Professor John Simpson, Dr David Price, Professor Luke Vale

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

BackgroundInfluenza is an acute viral infection of the respiratory tract. A rapid confirmatory diagnosis of influenza is important, since it is highly transmissible and outbreaks of influenza within the hospital setting increase morbidity and mortality. The objective of this study was to evaluate the cost implications, from the perspective of the UK NHS, of using on-label nasal swabs with the Alere™ i Influenza A & B test in a near patient setting.MethodsA cost consequence model was developed. The time horizon of the model was from hospital admission on suspicion of influenza until the end of treatment (following a diagnosis of influenza or discharge from hospital). Data on the prevalence of influenza and the sensitivity and specificity of the Alere™ i Influenza A & B test came from two prospective observational diagnostic accuracy studies. Costs were obtained from published resources. Uncertainties in the model data were investigated using deterministic, one-way sensitivity analyses.ResultsUsing the Alere™ i Influenza A & B point of care test with nasal swabs (on label) in NHS medical assessment units and emergency departments could save approximately £242,730 per 1000 adults presenting with influenza-like symptoms. The main cause for this was reduced times to availability of the result compared with the laboratory RT-PCR test. Other key drivers of savings were the cost of isolation, the prevalence of influenza, the specificity of the test, and the availability of isolation resources.ConclusionsThe Alere™ i Influenza A & B point of care test would have greatest impact in hospitals that have extensive delays in the time to receive a result. Sensitivity analyses identified the model parameters which would have greatest effect on the result and confirmed that assumptions were conservative, i.e. did not change key results.


Publication metadata

Author(s): Allen AJ, O'Leary RO, Davis S, Graziadio S, Jones WS, Simpson AJ, Price DA, Vale L, Power M

Publication type: Article

Publication status: Published

Journal: Diagnostic and Prognostic Research

Year: 2018

Volume: 2

Print publication date: 01/08/2018

Online publication date: 01/08/2018

Acceptance date: 18/05/2018

Date deposited: 10/09/2018

ISSN (electronic): 2397-7523

Publisher: BioMed Central Ltd.

URL: https://doi.org/10.1186/s41512-018-0031-8

DOI: 10.1186/s41512-018-0031-8


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