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Identifying Indicators to Assess and Monitor Data Integration Engines Systems.

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This study identified 90 indicators for healthcare integration engines. While some are challenging to compute, they offer potential for enhancing data quality and healthcare processes.

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Area of Science:

  • Health Informatics
  • Healthcare Systems Engineering

Background:

  • Integration engines are crucial for healthcare system interoperability.
  • Identifying relevant performance indicators is essential for optimizing these systems.

Purpose of the Study:

  • To identify key performance indicators (KPIs) for end-users of healthcare integration engines.
  • To assess the potential of these indicators in improving healthcare data quality and operational processes.

Main Methods:

  • A two-step approach was employed, combining qualitative interviews with a comprehensive literature review.
  • Ten semi-structured interviews were conducted with relevant stakeholders.

Main Results:

  • A total of 90 distinct indicators were identified through the combined methodologies.
  • Preliminary analysis suggests that many identified indicators, despite calculation challenges, hold significant promise.

Conclusions:

  • The identified indicators, though some are complex to derive, have the potential to significantly enhance data quality and streamline processes within healthcare institutions.
  • Further research and development are recommended to explore and implement these indicators effectively.