Evidence map›Paper›PMID 36098956›Full record

ArticleGlobal health action2022

Building coherent monitoring and evaluation plans with the Evaluation Planning Tool for global health.

Timothy Roberton, Talata Sawadogo-Lewis

Abstract 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
–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

5 citing papers in PubMed.

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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.

Timothy RobertonDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-6413-2289
Talata Sawadogo-LewisDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-0541-1859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Practitioners in global health are called to monitor and evaluate their projects. This keeps projects on track, it meets donor and public demand, and it is a key mechanism by which global health organizations hold themselves accountable and improve their community of practice. However, monitoring and evaluation (M&E) is time- and resource-consuming, bringing into question whether the effort expended on M&E is worth it. While there has been a shift towards emphasizing the learning aspect of M&E, non-governmental organizations (NGOs) and other actors still struggle to get value from their efforts. One reason for this is that M&E plans are often not coherent or employed to their full potential. Theories of change, indicator lists, and data collection become a series of disjointed efforts that do not tie together. They become tick-the-box exercises to satisfy donors rather than a logical approach to draw meaningful findings for stakeholders, governments, and local communities. In this paper, we propose a step-by-step approach to utilizing M&E tools to their fullest potential, including: (1) a clearly defined theory of change that captures all program pathways and shows all intermediate objectives needed to achieve impact, (2) indicators which directly reflect the intermediate and ultimate objectives in the theory of change, and (3) a data collection plan which includes appropriate methods to measure indicators and address the questions stakeholders want answered. We make the case for a simpler, more coherent approach to M&E and propose a new tool to help practitioners more easily develop evaluation plans that are rigorous, practical, and worth the effort.

Indexed as

Global HealthOrganizationsData CollectionHumansdonorsEvaluationM&Emonitoring and evaluationNGOsnon-governmental organizationsplanning

Identifiers

PMID36098956
PMCPMC9481137

What OpenQuestion holds

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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.