Evidence map›Paper›PMID 30522527›Full record

ArticleSystematic reviews2018

Defining and conceptualising data harmonisation: a scoping review protocol.

Bey-Marrié Schmidt, Christopher J Colvin, Ameer Hohlfeld, Natalie Leon

Abstract read
In one paragraph

Article in Systematic reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

4 authors.

Bey-Marrié SchmidtSchool of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Falmouth Rd, Observatory, Cape Town, 7925, South Africa. schbey001@myuct.ac.za.ORCID 0000-0003-1363-171X
Christopher J ColvinDivision of Social and Behavioural Sciences, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.
Ameer HohlfeldCochrane South Africa, South African Medical Research Council, Cape Town, South Africa.
Natalie LeonDepartment of Epidemiology, School of Public Health, Brown University, Providence, USA.

Funding

Using Information to Align Services and Link and Retain Men in the HIV CascadeR01MH106600 · NIMH · UNIVERSITY OF CAPE TOWN · PI COLVIN, CHRISTOPHER JAMES, LURIE, MARK NATHAN · 2015 to 2019
$2.1M
NIMH NIH HHS R01 MH106600US National Institute of Mental Health 1R01MH106600
6 · The paper itself

Abstract

backgroundData harmonisation is an important intervention to strengthen health systems functioning. It has the potential to enhance the production, accessibility and utilisation of routine health information for clinical and service management decision-making. It is important to understand the range of definitions and concepts of data harmonisation, as well as how its various social and technical components and processes are thought to lead to better health management decision-making. However, there is lack of agreement in the literature, and in practice, on definitions and conceptualisations of data harmonisation, making it difficult for health system decision-makers and researchers to design, implement, evaluate and compare data harmonisation interventions. This scoping review aims to synthesise (1) definitions and conceptualisations of data harmonisation as well as (2) explanations in the literature of the causal relationships between data harmonisation and health management decision-making.

methodsThis review follows recommended methodological stages for scoping studies. We will identify relevant studies (peer-reviewed and grey literature) from 2000 onwards, in English only, and with no methodological restriction, in various electronic databases, such as CINAHL, MEDLINE via PubMed and Global Health. Two reviewers will independently screen records for potential inclusion for the abstract and full-text screening stages. One reviewer will do the data extraction, analysis and synthesis, with built-in reliability checks from the rest of the team. We will use a combination of sampling techniques, including two types of 'purposeful sampling', a methodological approach that is particularly suitable for a scoping review with our objectives. We will provide (a) a numerical synthesis of characteristics of the included studies and (b) a narrative synthesis of definitions and explanations in the literature of the relationship between data harmonisation and health management decision-making. DISCUSSION: We list potential limitations of this scoping review. To our knowledge, this scoping review will be the first to synthesise definitions and conceptualisations of data harmonisation in the literature as well as the underlying explanations in the literature of the causal links between data harmonisation and health management decision-making.

Indexed as

Decision MakingHealth Information ExchangeInformation Storage and RetrievalHumansResearch DesignScoping Reviews as TopicData harmonisationData linkageHealth information exchangeHealth management decision-makingRoutine health information systemScoping review

Identifiers

PMID30522527
PMCPMC6284298

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.