IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0264912.html
   My bibliography  Save this article

Cost and affordability of scaling up tuberculosis diagnosis using Xpert MTB/RIF testing in West Java, Indonesia

Author

Listed:
  • Mardiati Nadjib
  • Retno Kusuma Dewi
  • Ery Setiawan
  • Tri Yunis Miko
  • Septiara Putri
  • Panji Fortuna Hadisoemarto
  • Euis Ratna Sari
  • Pujiyanto
  • Rani Martina
  • Lusi Nursilawati Syamsi

Abstract

In Indonesia, a significant number of tuberculosis (TB) cases may be missed, due to the low sensitivity and specificity of the currently used diagnostic algorithm. In this regard, the rapid molecular test using Xpert MTB/RIF, which has recently been introduced in Indonesia, can improve case detection. Thus, this study determined the cost and affordability of incorporating Xpert MTB/RIF testing for TB diagnosis. For this purpose, we estimated the costs (from the health system and societal perspectives) of reaching the TB detection target in Depok municipality, and applied the findings to the West Java province of Indonesia. The resources available for the health and TB program were also analyzed to support the decision to scale up the TB diagnosis using Xpert MTB/RIF testing. According to the results, the unit cost for TB diagnosis per person was USD 27.22 and USD 70.16 from the health system and societal perspectives, respectively. To reach the target of 109,843 TB cases for the 2020–2024 time period, Depok municipality would need USD 2,989,927 and USD 2,549,455 from the health system viewpoint, assuming the machine’s lifespan of five and 10 years, respectively. Extrapolating these results to the West Java province, USD 56,353,833 would be necessary to test 2,076,413 cases from 2019 to 2024. However, in order to accelerate the case detection target up to 2024, West Java requires additional funds. The implication of the findings is that the central government must consider local capacity to accelerate TB case detection and ensure that the installation of Xpert MTB/RIF machines is included in the overall costs.

Suggested Citation

  • Mardiati Nadjib & Retno Kusuma Dewi & Ery Setiawan & Tri Yunis Miko & Septiara Putri & Panji Fortuna Hadisoemarto & Euis Ratna Sari & Pujiyanto & Rani Martina & Lusi Nursilawati Syamsi, 2022. "Cost and affordability of scaling up tuberculosis diagnosis using Xpert MTB/RIF testing in West Java, Indonesia," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-16, March.
    • Handle: RePEc:plo:pone00:0264912
    DOI: 10.1371/journal.pone.0264912
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0264912
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0264912&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0264912?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Monde Muyoyeta & Maureen Moyo & Nkatya Kasese & Mapopa Ndhlovu & Deborah Milimo & Winfridah Mwanza & Nathan Kapata & Albertus Schaap & Peter Godfrey Faussett & Helen Ayles, 2015. "Implementation Research to Inform the Use of Xpert MTB/RIF in Primary Health Care Facilities in High TB and HIV Settings in Resource Constrained Settings," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-18, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miriam Harris & Amy Qi & Luke Jeagal & Nazi Torabi & Dick Menzies & Alexei Korobitsyn & Madhukar Pai & Ruvandhi R Nathavitharana & Faiz Ahmad Khan, 2019. "A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-19, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0264912. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.