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The path from big data analytics capabilities to value in hospitals: a scoping review
BACKGROUND: As the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing number of hospitals are investing in the development of big data analytics (BDA) capabilities. If the promises associated with these capabilities are hig...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805378/ https://www.ncbi.nlm.nih.gov/pubmed/35101026 http://dx.doi.org/10.1186/s12913-021-07332-0 |
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author | Brossard, Pierre-Yves Minvielle, Etienne Sicotte, Claude |
author_facet | Brossard, Pierre-Yves Minvielle, Etienne Sicotte, Claude |
author_sort | Brossard, Pierre-Yves |
collection | PubMed |
description | BACKGROUND: As the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing number of hospitals are investing in the development of big data analytics (BDA) capabilities. If the promises associated with these capabilities are high, how hospitals create value from it remains unclear. The present study undertakes a scoping review of existing research on BDA use in hospitals to describe the path from BDA capabilities (BDAC) to value and its associated challenges. METHODS: This scoping review was conducted following Arksey and O’Malley’s 5 stages framework. A systematic search strategy was adopted to identify relevant articles in Scopus and Web of Science. Data charting and extraction were performed following an analytical framework that builds on the resource-based view of the firm to describe the path from BDA capabilities to value in hospitals. RESULTS: Of 1,478 articles identified, 94 were included. Most of them are experimental research (n=69) published in medical (n=66) or computer science journals (n=28). The main value targets associated with the use of BDA are improving the quality of decision-making (n=56) and driving innovation (n=52) which apply mainly to care (n=67) and administrative (n=48) activities. To reach these targets, hospitals need to adequately combine BDA capabilities and value creation mechanisms (VCM) to enable knowledge generation and drive its assimilation. Benefits are endpoints of the value creation process. They are expected in all articles but realized in a few instances only (n=19). CONCLUSIONS: This review confirms the value creation potential of BDA solutions in hospitals. It also shows the organizational challenges that prevent hospitals from generating actual benefits from BDAC-building efforts. The configuring of strategies, technologies and organizational capabilities underlying the development of value-creating BDA solutions should become a priority area for research, with focus on the mechanisms that can drive the alignment of BDA and organizational strategies, and the development of organizational capabilities to support knowledge generation and assimilation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07332-0. |
format | Online Article Text |
id | pubmed-8805378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88053782022-02-03 The path from big data analytics capabilities to value in hospitals: a scoping review Brossard, Pierre-Yves Minvielle, Etienne Sicotte, Claude BMC Health Serv Res Research BACKGROUND: As the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing number of hospitals are investing in the development of big data analytics (BDA) capabilities. If the promises associated with these capabilities are high, how hospitals create value from it remains unclear. The present study undertakes a scoping review of existing research on BDA use in hospitals to describe the path from BDA capabilities (BDAC) to value and its associated challenges. METHODS: This scoping review was conducted following Arksey and O’Malley’s 5 stages framework. A systematic search strategy was adopted to identify relevant articles in Scopus and Web of Science. Data charting and extraction were performed following an analytical framework that builds on the resource-based view of the firm to describe the path from BDA capabilities to value in hospitals. RESULTS: Of 1,478 articles identified, 94 were included. Most of them are experimental research (n=69) published in medical (n=66) or computer science journals (n=28). The main value targets associated with the use of BDA are improving the quality of decision-making (n=56) and driving innovation (n=52) which apply mainly to care (n=67) and administrative (n=48) activities. To reach these targets, hospitals need to adequately combine BDA capabilities and value creation mechanisms (VCM) to enable knowledge generation and drive its assimilation. Benefits are endpoints of the value creation process. They are expected in all articles but realized in a few instances only (n=19). CONCLUSIONS: This review confirms the value creation potential of BDA solutions in hospitals. It also shows the organizational challenges that prevent hospitals from generating actual benefits from BDAC-building efforts. The configuring of strategies, technologies and organizational capabilities underlying the development of value-creating BDA solutions should become a priority area for research, with focus on the mechanisms that can drive the alignment of BDA and organizational strategies, and the development of organizational capabilities to support knowledge generation and assimilation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-07332-0. BioMed Central 2022-01-31 /pmc/articles/PMC8805378/ /pubmed/35101026 http://dx.doi.org/10.1186/s12913-021-07332-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Brossard, Pierre-Yves Minvielle, Etienne Sicotte, Claude The path from big data analytics capabilities to value in hospitals: a scoping review |
title | The path from big data analytics capabilities to value in hospitals: a scoping review |
title_full | The path from big data analytics capabilities to value in hospitals: a scoping review |
title_fullStr | The path from big data analytics capabilities to value in hospitals: a scoping review |
title_full_unstemmed | The path from big data analytics capabilities to value in hospitals: a scoping review |
title_short | The path from big data analytics capabilities to value in hospitals: a scoping review |
title_sort | path from big data analytics capabilities to value in hospitals: a scoping review |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805378/ https://www.ncbi.nlm.nih.gov/pubmed/35101026 http://dx.doi.org/10.1186/s12913-021-07332-0 |
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