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Provenance Data Management in Health Information Systems: A Systematic Literature Review.

Márcio José Sembay1, Douglas Dyllon Jeronimo de Macedo1, Laércio Pioli Júnior2

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|June 28, 2023
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Summary
This summary is machine-generated.

This systematic literature review explores methods for provenance data management in health information systems (HISs). It identifies common models like PROV and technologies such as blockchain, while highlighting challenges in HISs.

Keywords:
data provenancehealth datahealth data managementhealth information systemsprovenance dataprovenance data management

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Area of Science:

  • Health Informatics
  • Computer Science
  • Data Management

Background:

  • Provenance data management is crucial for health information systems (HISs).
  • Understanding existing methods, techniques, models, and technologies is essential for advancing HISs.
  • A systematic literature review (SLR) provides a comprehensive overview of the field.

Purpose of the Study:

  • To systematically review and understand methods, techniques, models, methodologies, and technologies for provenance data management in HISs.
  • To identify common approaches and emerging trends in HIS provenance.
  • To answer research questions that describe the current landscape of provenance data management in HISs.

Main Methods:

  • A systematic literature review (SLR) was conducted using six databases.
  • Backward and forward snowballing techniques were employed to identify additional relevant studies.
  • Eligible studies were assessed for quality and relevance to provenance data management in HISs.

Main Results:

  • Out of 239 retrieved studies, 17 were included in the final analysis.
  • Most studies were conference papers, reflecting the interdisciplinary nature of HIS research.
  • PROV-family data provenance models were frequently used with technologies like blockchain and middleware.
  • Key challenges include lack of technological infrastructure, data interoperability issues, and workforce preparedness.

Conclusions:

  • Various methods, techniques, models, and technologies for HIS provenance data management exist.
  • A proposed taxonomy offers researchers a new understanding of the field.
  • Addressing identified challenges is crucial for effective provenance data management in HISs.