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Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model

BACKGROUND: No distinctive clinical signs of Ebola virus disease (EVD) have prompted the development of rapid screening tools or called for a new approach to screening suspected Ebola cases. New screening approaches require evidence of clinical benefit and economic efficiency. As of now, no evidence...

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Autores principales: Tshomba, Antoine Oloma, Mukadi-Bamuleka, Daniel, De Weggheleire, Anja, Tshiani, Olivier M., Kayembe, Charles T., Mbala-Kingebeni, Placide, Muyembe-Tamfum, Jean-Jacques, Ahuka-Mundeke, Steve, Chenge, Faustin M., Jacobs, Bart Karl M., Mumba, Dieudonné N., Tshala-Katumbay, Désiré D., Mulangu, Sabue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581462/
https://www.ncbi.nlm.nih.gov/pubmed/37847703
http://dx.doi.org/10.1371/journal.pone.0293077
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author Tshomba, Antoine Oloma
Mukadi-Bamuleka, Daniel
De Weggheleire, Anja
Tshiani, Olivier M.
Kayembe, Charles T.
Mbala-Kingebeni, Placide
Muyembe-Tamfum, Jean-Jacques
Ahuka-Mundeke, Steve
Chenge, Faustin M.
Jacobs, Bart Karl M.
Mumba, Dieudonné N.
Tshala-Katumbay, Désiré D.
Mulangu, Sabue
author_facet Tshomba, Antoine Oloma
Mukadi-Bamuleka, Daniel
De Weggheleire, Anja
Tshiani, Olivier M.
Kayembe, Charles T.
Mbala-Kingebeni, Placide
Muyembe-Tamfum, Jean-Jacques
Ahuka-Mundeke, Steve
Chenge, Faustin M.
Jacobs, Bart Karl M.
Mumba, Dieudonné N.
Tshala-Katumbay, Désiré D.
Mulangu, Sabue
author_sort Tshomba, Antoine Oloma
collection PubMed
description BACKGROUND: No distinctive clinical signs of Ebola virus disease (EVD) have prompted the development of rapid screening tools or called for a new approach to screening suspected Ebola cases. New screening approaches require evidence of clinical benefit and economic efficiency. As of now, no evidence or defined algorithm exists. OBJECTIVE: To evaluate, from a healthcare perspective, the efficiency of incorporating Ebola prediction scores and rapid diagnostic tests into the EVD screening algorithm during an outbreak. METHODS: We collected data on rapid diagnostic tests (RDTs) and prediction scores’ accuracy measurements, e.g., sensitivity and specificity, and the cost of case management and RDT screening in EVD suspect cases. The overall cost of healthcare services (PPE, procedure time, and standard-of-care (SOC) costs) per suspected patient and diagnostic confirmation of EVD were calculated. We also collected the EVD prevalence among suspects from the literature. We created an analytical decision model to assess the efficiency of eight screening strategies: 1) Screening suspect cases with the WHO case definition for Ebola suspects, 2) Screening suspect cases with the ECPS at -3 points of cut-off, 3) Screening suspect cases with the ECPS as a joint test, 4) Screening suspect cases with the ECPS as a conditional test, 5) Screening suspect cases with the WHO case definition, then QuickNavi™-Ebola RDT, 6) Screening suspect cases with the ECPS at -3 points of cut-off and QuickNavi™-Ebola RDT, 7) Screening suspect cases with the ECPS as a conditional test and QuickNavi™-Ebola RDT, and 8) Screening suspect cases with the ECPS as a joint test and QuickNavi™-Ebola RDT. We performed a cost-effectiveness analysis to identify an algorithm that minimizes the cost per patient correctly classified. We performed a one-way and probabilistic sensitivity analysis to test the robustness of our findings. RESULTS: Our analysis found dual ECPS as a conditional test with the QuickNavi™-Ebola RDT algorithm to be the most cost-effective screening algorithm for EVD, with an effectiveness of 0.86. The cost-effectiveness ratio was 106.7 USD per patient correctly classified. The following algorithms, the ECPS as a conditional test with an effectiveness of 0.80 and an efficiency of 111.5 USD per patient correctly classified and the ECPS as a joint test with the QuickNavi™-Ebola RDT algorithm with an effectiveness of 0.81 and a cost-effectiveness ratio of 131.5 USD per patient correctly classified. These findings were sensitive to variations in the prevalence of EVD in suspected population and the sensitivity of the QuickNavi™-Ebola RDT. CONCLUSIONS: Findings from this study showed that prediction scores and RDT could improve Ebola screening. The use of the ECPS as a conditional test algorithm and the dual ECPS as a conditional test and then the QuickNavi™-Ebola RDT algorithm are the best screening choices because they are more efficient and lower the number of confirmation tests and overall care costs during an EBOV epidemic.
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spelling pubmed-105814622023-10-18 Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model Tshomba, Antoine Oloma Mukadi-Bamuleka, Daniel De Weggheleire, Anja Tshiani, Olivier M. Kayembe, Charles T. Mbala-Kingebeni, Placide Muyembe-Tamfum, Jean-Jacques Ahuka-Mundeke, Steve Chenge, Faustin M. Jacobs, Bart Karl M. Mumba, Dieudonné N. Tshala-Katumbay, Désiré D. Mulangu, Sabue PLoS One Research Article BACKGROUND: No distinctive clinical signs of Ebola virus disease (EVD) have prompted the development of rapid screening tools or called for a new approach to screening suspected Ebola cases. New screening approaches require evidence of clinical benefit and economic efficiency. As of now, no evidence or defined algorithm exists. OBJECTIVE: To evaluate, from a healthcare perspective, the efficiency of incorporating Ebola prediction scores and rapid diagnostic tests into the EVD screening algorithm during an outbreak. METHODS: We collected data on rapid diagnostic tests (RDTs) and prediction scores’ accuracy measurements, e.g., sensitivity and specificity, and the cost of case management and RDT screening in EVD suspect cases. The overall cost of healthcare services (PPE, procedure time, and standard-of-care (SOC) costs) per suspected patient and diagnostic confirmation of EVD were calculated. We also collected the EVD prevalence among suspects from the literature. We created an analytical decision model to assess the efficiency of eight screening strategies: 1) Screening suspect cases with the WHO case definition for Ebola suspects, 2) Screening suspect cases with the ECPS at -3 points of cut-off, 3) Screening suspect cases with the ECPS as a joint test, 4) Screening suspect cases with the ECPS as a conditional test, 5) Screening suspect cases with the WHO case definition, then QuickNavi™-Ebola RDT, 6) Screening suspect cases with the ECPS at -3 points of cut-off and QuickNavi™-Ebola RDT, 7) Screening suspect cases with the ECPS as a conditional test and QuickNavi™-Ebola RDT, and 8) Screening suspect cases with the ECPS as a joint test and QuickNavi™-Ebola RDT. We performed a cost-effectiveness analysis to identify an algorithm that minimizes the cost per patient correctly classified. We performed a one-way and probabilistic sensitivity analysis to test the robustness of our findings. RESULTS: Our analysis found dual ECPS as a conditional test with the QuickNavi™-Ebola RDT algorithm to be the most cost-effective screening algorithm for EVD, with an effectiveness of 0.86. The cost-effectiveness ratio was 106.7 USD per patient correctly classified. The following algorithms, the ECPS as a conditional test with an effectiveness of 0.80 and an efficiency of 111.5 USD per patient correctly classified and the ECPS as a joint test with the QuickNavi™-Ebola RDT algorithm with an effectiveness of 0.81 and a cost-effectiveness ratio of 131.5 USD per patient correctly classified. These findings were sensitive to variations in the prevalence of EVD in suspected population and the sensitivity of the QuickNavi™-Ebola RDT. CONCLUSIONS: Findings from this study showed that prediction scores and RDT could improve Ebola screening. The use of the ECPS as a conditional test algorithm and the dual ECPS as a conditional test and then the QuickNavi™-Ebola RDT algorithm are the best screening choices because they are more efficient and lower the number of confirmation tests and overall care costs during an EBOV epidemic. Public Library of Science 2023-10-17 /pmc/articles/PMC10581462/ /pubmed/37847703 http://dx.doi.org/10.1371/journal.pone.0293077 Text en © 2023 Tshomba et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tshomba, Antoine Oloma
Mukadi-Bamuleka, Daniel
De Weggheleire, Anja
Tshiani, Olivier M.
Kayembe, Charles T.
Mbala-Kingebeni, Placide
Muyembe-Tamfum, Jean-Jacques
Ahuka-Mundeke, Steve
Chenge, Faustin M.
Jacobs, Bart Karl M.
Mumba, Dieudonné N.
Tshala-Katumbay, Désiré D.
Mulangu, Sabue
Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title_full Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title_fullStr Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title_full_unstemmed Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title_short Cost-effectiveness of incorporating Ebola prediction score tools and rapid diagnostic tests into a screening algorithm: A decision analytic model
title_sort cost-effectiveness of incorporating ebola prediction score tools and rapid diagnostic tests into a screening algorithm: a decision analytic model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581462/
https://www.ncbi.nlm.nih.gov/pubmed/37847703
http://dx.doi.org/10.1371/journal.pone.0293077
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