September 14, 2025 Journal article Open Access

Bayou Tilahun Assaye; Bekalu Endalew; Maru Meseret Tadele; Gizaw hailiye Teferie; Abraham Teym; Yidersal hune Melese; Andualem fentahun senishaw; Sisay Maru Wubante; Habtamu Setegn Ngusie; Aysheshim Belaineh Haimanot

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  <identifier identifierType="DOI">10.20372/nadre:18409</identifier>
  <creators>
    <creator>
      <creatorName>Bayou Tilahun Assaye</creatorName>
      <affiliation>Department of Health Informatics, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Bekalu Endalew</creatorName>
      <affiliation>Department of Public Health, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Maru Meseret Tadele</creatorName>
      <affiliation>Department of Health Informatics, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Gizaw hailiye Teferie</creatorName>
      <affiliation>Department of Health Informatics, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Abraham Teym</creatorName>
      <affiliation>Department of Environmental Health, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Yidersal hune Melese</creatorName>
      <affiliation>Department of Human Nutrition, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Andualem fentahun senishaw</creatorName>
      <affiliation>Department of Public Health, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Sisay Maru Wubante</creatorName>
      <affiliation>Department of Health Informatics, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Habtamu Setegn Ngusie</creatorName>
      <affiliation>Department of Health Informatics, College of Medicine and Health Science, Woldia University, Woldia, Ethiopia</affiliation>
    </creator>
    <creator>
      <creatorName>Aysheshim Belaineh Haimanot</creatorName>
      <affiliation>Department of Public Health, College of Medicine and Health Science, Debre Markos University, Debre Markos, Ethiopia</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Readiness of big health data analytics by  technology-organization-environment (TOE) framework in  Ethiopian health sectors</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2025</publicationYear>
  <subjects>
    <subject>Big health data  Data analytics  Data management  Health information revolution  Health sectors  Readiness</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2025-09-14</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://nadre.ethernet.edu.et/record/18409</alternateIdentifier>
  </alternateIdentifiers>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.20372/nadre:18408</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/nadre</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/wu</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://nadre.ethernet.edu.et/communities/zenodo</relatedIdentifier>
  </relatedIdentifiers>
  <version>Version 1</version>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Background: Big health data is a large and complex dataset that the health sector has collected and stored continuously to generate healthcare evidence for intervening the future healthcare un certainty. However, data use for decision-making practices has been significantly low in devel oping countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influence the health sector&amp;rsquo;s decision to adopt big health data analytics in health sectors. The aim of this study was to identify the level of readiness for big health data analytics and its associated factors in healthcare sectors. Methods: A cross-sectional study design was conducted among 845 target employees using the structural equation modeling approach by using technological, organizational, and environ mental (TOE) frameworks. The target population of the study was health sector managers, di rectors, team leaders, healthcare planning officers, ICT/IT managers, and health professionals. For data analysis, exploratory factor analysis using SPSS 20.0 and structural equation modeling using AMOS software were used. Result: 58.85 % of the study participants had big health data analytics readiness. Complexity (CX), Top management support (TMS), training (TR) and government law policies and legislation (GLAL) and government IT policies (GITP) had positive direct effect, compatibility (CT), and optimism (OP) had negative direct effect on BD readiness (BDR) Conclusion: The technological, organizational, and environmental factors significantly contributed to big health data readiness in the healthcare sector. The Complexity, compatibility, optimism, Top management support, training (TR) and government law and IT policies (GITP) had effect on big health data analytics readiness. Formulating efficient reform in healthcare sectors, especially&amp;nbsp;for evidence-based decision-making and jointly working with stakeholders will be more relevant for effective implementation of big health data analytics in healthcare sectors.&lt;/p&gt;</description>
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