View in EDS HTML Full Text PDF Full Text

Identification and prioritization of critical socio-technical factors influencing big data analytics adoption in healthcare using Delphi method.

Saved in:
Bibliographic Details
Title: Identification and prioritization of critical socio-technical factors influencing big data analytics adoption in healthcare using Delphi method.
Authors: Salahuddin, Lizawati (AUTHOR), Wolseley, Nik Nurdini (AUTHOR), Mohd Aboobaider, Burhanuddin (AUTHOR), Raja Ikram, Raja Rina (AUTHOR), Hashim, Ummi Rabaah (AUTHOR), Mohamed Said, Mohd Shahrir (AUTHOR), Hassan, Noor Hafizah (AUTHOR)
Source: Behaviour & Information Technology. Nov2025, Vol. 44 Issue 19, p4838-4852. 15p.
Subjects: Consensus (Social sciences), Medical informatics, Research funding, Data analytics, Decision making, Judgment sampling, Descriptive statistics, System analysis, Organizational change, Statistics, Delphi method, Data quality
Abstract: The healthcare sector faces significant challenges in adopting big data analytics, primarily due to the complex interplay of various socio-technical factors that influence successful implementation. While prior research has identified numerous factors affecting big data analytics adoption, there is limited understanding of their relative importance in the healthcare context. This study aims to identify and prioritise the critical socio-technical factors influencing big data analytics adoption in healthcare through expert consensus. A four-round Delphi study was conducted with ten experts representing diverse stakeholders including academics, data scientists, healthcare practitioners, and top management. The study employed a comprehensive framework encompassing person, technology, organisation, environment, and task dimensions. The results revealed that analytical skills, knowledge, and experience were the most critical person-related factors. In the technology dimension, system reliability, and data quality emerged as top priorities, while organisational support, funding, and infrastructure were identified as crucial organisational factors. The study also highlighted technological advancement and government regulations as key environmental factors, with task reliability emerging as the most significant task-related factor. The study offers a comprehensive understanding of the relative importance of various social-technical factors, thereby enabling more focused and effective big data analytics adoption strategies in healthcare settings. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 189411027
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Identification and prioritization of critical socio-technical factors influencing big data analytics adoption in healthcare using Delphi method.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Salahuddin%2C+Lizawati%22">Salahuddin, Lizawati</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wolseley%2C+Nik+Nurdini%22">Wolseley, Nik Nurdini</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mohd+Aboobaider%2C+Burhanuddin%22">Mohd Aboobaider, Burhanuddin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Raja+Ikram%2C+Raja+Rina%22">Raja Ikram, Raja Rina</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hashim%2C+Ummi+Rabaah%22">Hashim, Ummi Rabaah</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mohamed+Said%2C+Mohd+Shahrir%22">Mohamed Said, Mohd Shahrir</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hassan%2C+Noor+Hafizah%22">Hassan, Noor Hafizah</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Behaviour+%26+Information+Technology%22">Behaviour & Information Technology</searchLink>. Nov2025, Vol. 44 Issue 19, p4838-4852. 15p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Consensus+%28Social+sciences%29%22">Consensus (Social sciences)</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+informatics%22">Medical informatics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analytics%22">Data analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Judgment+sampling%22">Judgment sampling</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22System+analysis%22">System analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Organizational+change%22">Organizational change</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Delphi+method%22">Delphi method</searchLink><br /><searchLink fieldCode="DE" term="%22Data+quality%22">Data quality</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The healthcare sector faces significant challenges in adopting big data analytics, primarily due to the complex interplay of various socio-technical factors that influence successful implementation. While prior research has identified numerous factors affecting big data analytics adoption, there is limited understanding of their relative importance in the healthcare context. This study aims to identify and prioritise the critical socio-technical factors influencing big data analytics adoption in healthcare through expert consensus. A four-round Delphi study was conducted with ten experts representing diverse stakeholders including academics, data scientists, healthcare practitioners, and top management. The study employed a comprehensive framework encompassing person, technology, organisation, environment, and task dimensions. The results revealed that analytical skills, knowledge, and experience were the most critical person-related factors. In the technology dimension, system reliability, and data quality emerged as top priorities, while organisational support, funding, and infrastructure were identified as crucial organisational factors. The study also highlighted technological advancement and government regulations as key environmental factors, with task reliability emerging as the most significant task-related factor. The study offers a comprehensive understanding of the relative importance of various social-technical factors, thereby enabling more focused and effective big data analytics adoption strategies in healthcare settings. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=189411027
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/0144929X.2025.2494283
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 4838
    Subjects:
      – SubjectFull: Consensus (Social sciences)
        Type: general
      – SubjectFull: Medical informatics
        Type: general
      – SubjectFull: Research funding
        Type: general
      – SubjectFull: Data analytics
        Type: general
      – SubjectFull: Decision making
        Type: general
      – SubjectFull: Judgment sampling
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: System analysis
        Type: general
      – SubjectFull: Organizational change
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Delphi method
        Type: general
      – SubjectFull: Data quality
        Type: general
    Titles:
      – TitleFull: Identification and prioritization of critical socio-technical factors influencing big data analytics adoption in healthcare using Delphi method.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Salahuddin, Lizawati
      – PersonEntity:
          Name:
            NameFull: Wolseley, Nik Nurdini
      – PersonEntity:
          Name:
            NameFull: Mohd Aboobaider, Burhanuddin
      – PersonEntity:
          Name:
            NameFull: Raja Ikram, Raja Rina
      – PersonEntity:
          Name:
            NameFull: Hashim, Ummi Rabaah
      – PersonEntity:
          Name:
            NameFull: Mohamed Said, Mohd Shahrir
      – PersonEntity:
          Name:
            NameFull: Hassan, Noor Hafizah
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0144929X
          Numbering:
            – Type: volume
              Value: 44
            – Type: issue
              Value: 19
          Titles:
            – TitleFull: Behaviour & Information Technology
              Type: main
ResultId 1