The Use of Data Analysis Technologies in Primary Health Care Management: Scoping Review

Objective: To map the use of data analysis technologies in the management of Primary Health Care (PHC). Method: A scoping review conducted according to the stages proposed by the Joanna Briggs Institute. The literature search was performed in PubMed, Embase, Web of Science, Scopus, and the Virtual Health Library (VHL), while gray literature was retrieved from Google Scholar, the Brazilian Digital Library of Theses and Dissertations, and the Theses and Dissertations Catalog of the Coordination for the Improvement of Higher Education Personnel (CAPES). Articles were independently assessed by two reviewers using Rayyan. Results and Discussion: The search strategy identified 737 studies, with additional records included from other sources. A total of 47 duplicate documents were excluded, along with 662 that did not meet the inclusion criteria based on title and abstract screening. In 12 cases, there was a conflict, which was resolved by a third reviewer, leading to the exclusion of nine studies. As a result, 19 studies were selected for full-text reading, of which five were ultimately included in the review. Research Implications: The findings of this review demonstrate how dashboards can support the analysis of large datasets, which are common but not limited to the healthcare sector. Additionally, these tools enable the creation of analytical models that predict outcomes of interest, facilitating data-driven decision-making and allowing for the adoption of more effective measures to monitor disease spread and healthcare service capacity. Originality/Value: This study contributes by mapping the use of data analysis technologies in PHC management, a topic that remains underexplored. Despite the increasing adoption of these tools and the benefits reported in the literature, there is a scarcity of publications addressing their application in PHC. Thus, the findings reinforce the need for further research on the impact and cost-effectiveness of these technologies in healthcare management.

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Publication Details

Journal
Revista de Gestão Social e Ambiental
Published
2025-04-16
DOI
https://doi.org/10.24857/rgsa.v19n4-086
Primary Topic
Big Data and Business Intelligence
Type
article
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article

The Use of Data Analysis Technologies in Primary Health Care Management: Scoping Review

Thereza Maria Magalhães Moreira, Ana Kézia Cunha de Queiroz Araújo, Virna Ribeiro Feitosa Cestari, Fabiana Sales Vitoriano Uchoa et al.
Revista de Gestão Social e Ambiental
Big Data and Business Intelligence
article

The Use of Data Analysis Technologies in Primary Health Care Management: Scoping Review

Thereza Maria Magalhães Moreira, Ana Kézia Cunha de Queiroz Araújo, Virna Ribeiro Feitosa Cestari, Fabiana Sales Vitoriano Uchoa, Vanessa Guimarães Romão
article en

Abstract

Objective: To map the use of data analysis technologies in the management of Primary Health Care (PHC). Method: A scoping review conducted according to the stages proposed by the Joanna Briggs Institute. The literature search was performed in PubMed, Embase, Web of Science, Scopus, and the Virtual Health Library (VHL), while gray literature was retrieved from Google Scholar, the Brazilian Digital Library of Theses and Dissertations, and the Theses and Dissertations Catalog of the Coordination for the Improvement of Higher Education Personnel (CAPES). Articles were independently assessed by two reviewers using Rayyan. Results and Discussion: The search strategy identified 737 studies, with additional records included from other sources. A total of 47 duplicate documents were excluded, along with 662 that did not meet the inclusion criteria based on title and abstract screening. In 12 cases, there was a conflict, which was resolved by a third reviewer, leading to the exclusion of nine studies. As a result, 19 studies were selected for full-text reading, of which five were ultimately included in the review. Research Implications: The findings of this review demonstrate how dashboards can support the analysis of large datasets, which are common but not limited to the healthcare sector. Additionally, these tools enable the creation of analytical models that predict outcomes of interest, facilitating data-driven decision-making and allowing for the adoption of more effective measures to monitor disease spread and healthcare service capacity. Originality/Value: This study contributes by mapping the use of data analysis technologies in PHC management, a topic that remains underexplored. Despite the increasing adoption of these tools and the benefits reported in the literature, there is a scarcity of publications addressing their application in PHC. Thus, the findings reinforce the need for further research on the impact and cost-effectiveness of these technologies in healthcare management.

Revista de Gestão Social e AmbientalVol. 19(4)
Openalex Percentile: Top 89%
Big Data and Business Intelligence
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