Improving community health centres with big data analytics: A systematic literature review on adoption
Introduction Implementing Big Data Analytics (BDA) could enhance the efficiency and effectiveness of Community Health Centres (CHCs). This study focuses on improving healthcare service delivery in CHCs located in the Nkangala District through the adoption of BDA. It identifies a specific research ga...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-05-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251314548 |
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| author | Pascal Ndikuyeze Phahlane Mampilo |
| author_facet | Pascal Ndikuyeze Phahlane Mampilo |
| author_sort | Pascal Ndikuyeze |
| collection | DOAJ |
| description | Introduction Implementing Big Data Analytics (BDA) could enhance the efficiency and effectiveness of Community Health Centres (CHCs). This study focuses on improving healthcare service delivery in CHCs located in the Nkangala District through the adoption of BDA. It identifies a specific research gap and seeks to consolidate existing knowledge while revealing challenges and opportunities in BDA implementation. Methods This literature review was conducted using a systematic method that adheres to PRISMA principles. The review process involved the identification and selection of peer-reviewed publications in English up to 2024. The search was carried out among several major academic databases, including PubMed, Taylor & Francis Online, Google Scholar, IEEE Xplore, SpringerLink, ScienceDirect, and JSTOR. Specific search terms related to data-driven approaches and healthcare service delivery were used. The inclusion criteria focused on studies addressing the adoption and implementation of BDA in CHCs, while exclusion criteria eliminated studies not relevant to this context. The selected studies were analysed to assess the research state, identify key themes, and highlight gaps and challenges in BDA adoption within CHCs. Results A total of 31 studies met the inclusion criteria, demonstrating variability in study design, geographic location, and focus areas related to BDA adoption and implementation. The synthesis of results unveiled common challenges, best practices, and outcomes associated with BDA implementation, including technological, organizational, and human factors influencing successful integration. Conclusion The development and implementation of data-driven methodologies in healthcare service delivery present several challenges, including evidence limitations such as heterogeneity in study designs, restricted generalizability, and variability in study quality. Additionally, the short duration of many studies complicates the evaluation of their long-term impacts. Despite these challenges, the transformative potential of data-driven approaches highlights the necessity for further research to enhance adoption strategies and address existing research gaps. |
| format | Article |
| id | doaj-art-a216e1dc9c6b4c8cb7292c96ccc178c6 |
| institution | DOAJ |
| issn | 2055-2076 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj-art-a216e1dc9c6b4c8cb7292c96ccc178c62025-08-20T02:57:12ZengSAGE PublishingDigital Health2055-20762025-05-011110.1177/20552076251314548Improving community health centres with big data analytics: A systematic literature review on adoptionPascal NdikuyezePhahlane MampiloIntroduction Implementing Big Data Analytics (BDA) could enhance the efficiency and effectiveness of Community Health Centres (CHCs). This study focuses on improving healthcare service delivery in CHCs located in the Nkangala District through the adoption of BDA. It identifies a specific research gap and seeks to consolidate existing knowledge while revealing challenges and opportunities in BDA implementation. Methods This literature review was conducted using a systematic method that adheres to PRISMA principles. The review process involved the identification and selection of peer-reviewed publications in English up to 2024. The search was carried out among several major academic databases, including PubMed, Taylor & Francis Online, Google Scholar, IEEE Xplore, SpringerLink, ScienceDirect, and JSTOR. Specific search terms related to data-driven approaches and healthcare service delivery were used. The inclusion criteria focused on studies addressing the adoption and implementation of BDA in CHCs, while exclusion criteria eliminated studies not relevant to this context. The selected studies were analysed to assess the research state, identify key themes, and highlight gaps and challenges in BDA adoption within CHCs. Results A total of 31 studies met the inclusion criteria, demonstrating variability in study design, geographic location, and focus areas related to BDA adoption and implementation. The synthesis of results unveiled common challenges, best practices, and outcomes associated with BDA implementation, including technological, organizational, and human factors influencing successful integration. Conclusion The development and implementation of data-driven methodologies in healthcare service delivery present several challenges, including evidence limitations such as heterogeneity in study designs, restricted generalizability, and variability in study quality. Additionally, the short duration of many studies complicates the evaluation of their long-term impacts. Despite these challenges, the transformative potential of data-driven approaches highlights the necessity for further research to enhance adoption strategies and address existing research gaps.https://doi.org/10.1177/20552076251314548 |
| spellingShingle | Pascal Ndikuyeze Phahlane Mampilo Improving community health centres with big data analytics: A systematic literature review on adoption Digital Health |
| title | Improving community health centres with big data analytics: A systematic literature review on adoption |
| title_full | Improving community health centres with big data analytics: A systematic literature review on adoption |
| title_fullStr | Improving community health centres with big data analytics: A systematic literature review on adoption |
| title_full_unstemmed | Improving community health centres with big data analytics: A systematic literature review on adoption |
| title_short | Improving community health centres with big data analytics: A systematic literature review on adoption |
| title_sort | improving community health centres with big data analytics a systematic literature review on adoption |
| url | https://doi.org/10.1177/20552076251314548 |
| work_keys_str_mv | AT pascalndikuyeze improvingcommunityhealthcentreswithbigdataanalyticsasystematicliteraturereviewonadoption AT phahlanemampilo improvingcommunityhealthcentreswithbigdataanalyticsasystematicliteraturereviewonadoption |