Defining and conceptualising data harmonisation: a scoping review protocol.

Journal: Systematic reviews

Volume: 7

Issue: 1

Year of Publication: 2019

Affiliated Institutions:  School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Falmouth Rd, Observatory, Cape Town, , South Africa. schbey@myuct.ac.za. Division of Social and Behavioural Sciences, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa. Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa. Department of Epidemiology, School of Public Health, Brown University, Providence, USA.

Abstract summary 

Data 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.This 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.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.

Authors & Co-authors:  Schmidt Bey-Marrié BM Colvin Christopher J CJ Hohlfeld Ameer A Leon Natalie N

Study Outcome 

Source Link: Visit source

Statistics
Citations :  World Health Organization . Everybody’s business-strengthening health systems to improve health outcomes: WHO’s framework for action. Geneva: WHO; 2007.
Authors :  4
Identifiers
Doi : 226
SSN : 2046-4053
Study Population
Male,Female
Mesh Terms
Decision Making
Other Terms
Data harmonisation;Data linkage;Health information exchange;Health management decision-making;Routine health information system;Scoping review
Study Design
Narrative Study,Cross Sectional Study
Study Approach
Country of Study
Publication Country
England