Evidence map›Paper›PMID 36098950›Full record

ArticleGlobal health action2022

The role of modeling in evaluation of maternal and child health programs: using the lives saved tool to help answer core evaluation questions.

Neff Walker, Yvonne Tam

Open access · goldAbstract read
In one paragraph

Article in Global health action, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Neff WalkerDepartment of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-3526-2978
Yvonne TamDepartment of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-4849-5084
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper explains how The Lives Saved Tool (LiST), a computer-based model that estimates the impact of scaling up interventions on stillbirths, maternal, neonatal and child health, can contribute to evaluations of programs being delivered at scale to improve maternal and child health. LiST can be used to estimate the impact of a program in advance, allowing planners to refine, streamline and set appropriate program targets. LiST can also be used to estimate the impact of a program, which is particularly useful given the high costs of measuring changes in population health. Finally, LiST can be used to estimate the relative contributions of different interventions or sets of interventions within programs that are found to have a positive impact. The latest version of LiST allows users to manipulate both utilization and quality of service to generate estimates of effective coverage. In addition, a new, web-based version of LiST is now available, with a simpler and more streamlined interface designed to increase accessibility to beginning users. LiST modeling can help program planners, evaluators and funders respond to core evaluation questions related to program design and impact, providing evidence to support decisions about how best to use available resources to save the lives of women and children.

Indexed as

Child HealthChild MortalityChildFemaleHumansInfant MortalityInfant, NewbornMaternal MortalityPregnancyStillbirthchild healthimpact evaluationmaternal healthmodelingnewborn healthProgram evaluation

Identifiers

PMID36098950
PMCPMC9481079
OpenAlexW4295421526

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.