Evidence map›Paper›PMID 34671462›Full record

SynthesisJournal of global health2021

Research gaps in transforming tuberculosis data to action for better health outcomes: A systematic literature review.

Manish Kumar, Meredith Silver, Jeanne Chauffour, Colleen Boyle, David Boone

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. MDR Tuberculosis Treatment.Medicina (Kaunas, Lithuania) · 2022
    Review
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

5 authors.

Manish KumarCarolina Population Center, University of North Carolina at Chapel Hill, NC, USA.
Meredith SilverCarolina Population Center, University of North Carolina at Chapel Hill, NC, USA.
Jeanne ChauffourJohn Snow Inc., Washington, D.C., USA.
Colleen BoyleCarolina Population Center, University of North Carolina at Chapel Hill, NC, USA.
David BooneJohn Snow Inc., Washington, D.C., USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn their work to end the tuberculosis (TB) epidemic in lower- and middle-income countries, national TB programs need a tool to measure, monitor, and strengthen relevant capabilities to create a continuous transformation of data into action (D2A) to improve TB program results. However, there is a lack of scientific evidence to determine specific measurement dimensions of a D2A continuum that enables TB programs to identify the barriers and enablers of D2A and to guide the selection of interventions appropriate for the context and decision-making capabilities of various TB program actors.

methodsA systematic review of peer-reviewed and grey literature was conducted per Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 48 peer-reviewed publications were selected for data extraction and analysis.

resultsThe findings show that selected publications discussed the health system level, stakeholders involved in decision making, decision type, data system, data sources, data use enablers and barriers, decision-making framework and steps, decision outcome/impact, and how that outcome was measured. The findings highlight barriers and enablers to data use and explain the relationship among data sources, decision type, and stakeholders. Seventeen D2A measurement dimensions were identified.

conclusionsTransforming data to action is a continuous process that recognizes that data use indicators vary by type of decisions, decision makers, and the health system level at which decisions are made. As a logical next step, the project team plans to develop and validate a D2A continuum toolkit that will include a measurement scale, implementation guide, and data collection and analysis Microsoft Excel workbook.

Indexed as

TuberculosisHumans

Identifiers

PMID34671462
PMCPMC8501450

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.