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Extending a Data Management Maturity Model for Process Mining in Healthcare
Andreas Erhard, Klaus Arthofer, Emmanuel Helm
192 - 197
10.3233/SHTI230038
Research Article
Studies in Health Technology and Informatics
Volume 301: dHealth 2023
Abstract

Background:

Many components must work together to continuously improve processes in healthcare organizations. Process mining has recently developed into a discipline that can make a significant contribution here.

Objectives:

We want to extend an existing management tool to assess and improve the capability of organizations in this area.

Method:

We add a dimension to the adoption readiness assessment and maturity model for sharable clinical pathways to assess and improve event data quality.

Results:

We present different approaches for formal and checkpoint assessments and an embedding of the improvement strategy with examples.

Conclusion:

The additional dimension from the process mining domain integrates with the existing model. At all levels, links can be established between the various aspects of event data quality with existing dimensions. The model has yet to be tested in a real-world use case.

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Creative Commons License