Evidence map›Paper›PMID 37616207›Full record

ArticlePLOS global public health2023

"I tell you, getting data for this is hell"-Exploring the use of evidence for noncommunicable disease policies in Ghana.

Mark Fordjour Owusu, Joseph Adu, Benjamin Ansah Dortey

Abstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Mark Fordjour OwusuSchool of Health Sciences, University of Canterbury, Christchurch, New Zealand.
Joseph AduDepartment of Health and Rehabilitation, Western University, London, Ontario, Canada.
Benjamin Ansah DorteyTrauma and Specialist Hospital, Winneba, Ghana.ORCID https://orcid.org/0009-0001-5824-4740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After several years of over concentration on communicable diseases, Ghana has finally made notable strides in the prevention of NCDs by introducing key policies and programmes. Evident shows that there is limited NCD-related data on mortality and risk factors to inform NCD policy, planning, and implementation in Ghana. We explored the evidence base for noncommunicable disease policies in Ghana. A qualitative approach was adopted using key informant interviews and documents as data sources. An adaptation of the framework method for analysing qualitative data by Gale and colleagues' (2013) was used to analyse data. Our findings show that effort has been made in terms of institutions and systems to provide evidence for the policy process with the creation of the Centre for Health Information Management and the District Health Information Management System. Although there is overreliance on routine facility data, policies have also been framed using surveys, burden of disease estimates, monitoring reports, and systematic reviews. There is little emphasis on content analysis, key informant interviews, case studies, and implementation science techniques in the policy process of Ghana. Inadequate and poor data quality are key challenges that confront policymakers. Ghana has improved its information infrastructure but access to quality noncommunicable disease data remains a daunting challenge. A broader framework for the integration of different sources of data such as verbal autopsies and natural experiments is needed while strengthening existing systems. This, however, requires greater investments in personnel and logistics at national and district levels.

Identifiers

PMID37616207
PMCPMC10449463

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Registered trials

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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.