Evidence map›Paper›PMID 32074142›Full record

ArticlePloS one2020

Situating trade-offs: Stakeholder perspectives on overtreatment versus missed diagnosis in transition to Xpert MTB/RIF Ultra in Kenya and Swaziland.

Muthoni Mwaura, Kekeletso Kao, Jesse Wambugu, Andre Trollip, Welile Sikhondze, Eunice Omesa, Sindi Dlamini, Nompumelelo Mzizi, Muyalo Dlamini, Busizwe Sibandze and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 3 pooled it
0.1field-weighted citation impact, top 55% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 4 countries.

Muthoni MwauraDepartment of Health, Ethics & Society; Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands.
Kekeletso KaoFoundation for Innovative New Diagnostics (FIIND), Geneva, Switzerland.
Jesse WambuguFoundation for Innovative New Diagnostics (FIIND), Geneva, Switzerland.
Andre TrollipFoundation for Innovative New Diagnostics (FIIND), Geneva, Switzerland.
Welile SikhondzeNational TB Control Program, Ministry of Health, Mbabane, Swaziland.
Eunice OmesaNational Tuberculosis, Leprosy, and Lung Disease Program, Ministry of Health, Nairobi, Kenya.
Sindi DlaminiSwaziland Health Laboratory Service, Ministry of Health, Mbabane, Swaziland.
Nompumelelo MziziNational TB Control Program, Ministry of Health, Mbabane, Swaziland.
Muyalo DlaminiNational TB Control Program, Ministry of Health, Mbabane, Swaziland.
Busizwe SibandzeNational TB Control Program, Ministry of Health, Mbabane, Swaziland.
Brian DlaminiNational TB Control Program, Ministry of Health, Mbabane, Swaziland.ORCID 0000-0002-6421-2438
Heidi AlbertFoundation for Innovative New Diagnostics (FIIND), Geneva, Switzerland.ORCID 0000-0002-8595-4123
Wybo DondorpDepartment of Health, Ethics & Society; Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands.
Nora EngelDepartment of Health, Ethics & Society; Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-1823-3908
Ministry of Health · SZFIND · CHMaastricht University · NLMinistry of Health · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Implementing new diagnostics in public health programs can involve difficult trade-off decisions between individual patient benefits and public health considerations. Such decision-making processes are often not documented and may not include engagement of affected communities. This paper examines the perspectives of stakeholders on the trade-off between over-treatment and missed diagnosis captured during decision-making workshops on the transition from use of Xpert MTB/RIF to diagnose tuberculosis to Xpert MTB/RIF Ultra in Kenya and Swaziland. Xpert MTB/RIF Ultra has an overall increase in sensitivity but a decrease in specificity when compared to its predecessor. We conducted a qualitative study using four focus group discussions with a total of 47 participants and non-participant observation. The analysis reveals how participants deemed Xpert MTB/RIF Ultra's reduced specificity vis-à-vis its increased sensitivity to be an acceptable trade-off. The way participants assessed this trade-off was shaped by their experiences with the general uncertainty of all diagnostic tests, alternative testing options, historical evolution of diagnostic practices, epidemiological factors and resource constraints. In assessing the trade-off community and individual benefit and harm was frequently discussed together. Qualitative research on stakeholder engagement activities for diagnostic development and implementation can identify everyday experiences and situate assessments and perspectives of key stakeholders and as such aid in decision-making, improving implementation as well as patient outcomes. Further research is needed on the intended and unintended consequences of such engagement activities, how findings are being incorporated by decision-makers, and the impact on programmatic implementation.

Indexed as

AttitudeMedical OveruseEswatiniFocus GroupsHumansKenyaMissed DiagnosisMolecular Diagnostic TechniquesReagent Kits, DiagnosticSensitivity and SpecificityStakeholder ParticipationTuberculosisReagent Kits, Diagnostic

Identifiers

PMID32074142
PMCPMC7029953
OpenAlexW3006976811

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.