@inproceedings{2280363229d846f6ac4403f4bb994ad3,
title = "Extending a Data Management Maturity Model for Process Mining in Healthcare",
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.",
keywords = "BPM+ Health, Data Management Maturity Model, Event Data, OMG, Process Mining, RAMM, Health Facilities, Delivery of Health Care, Data Mining/methods, Data Management, Organizations",
author = "Andreas Erhard and Klaus Arthofer and Emmanuel Helm",
note = "Publisher Copyright: {\textcopyright} 2023 The authors, AIT Austrian Institute of Technology and IOS Press.; 17th Annual Sonference on Health Informatics Meets Digital Health, dHealth 2023 ; Conference date: 16-05-2023 Through 17-05-2023",
year = "2023",
month = may,
day = "2",
doi = "10.3233/SHTI230038",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "192--197",
editor = "Bernhard Pfeifer and Gunter Schreier and Martin Baumgartner and Dieter Hayn",
booktitle = "dHealth 2023 - Proceedings of the 17th Health Informatics Meets Digital Health Conference",
address = "Netherlands",
}