Abstract
In the realm of healthcare, effective communication and data management are increasingly reliant on Health Information Systems (HIS) and electronic health records (EHR).To ensure interoperability, adherence to standards such as the Integrating the Healthcare
Enterprise (IHE) profiles is essential [1]. Given the profound societal value of healthcare,
optimizing these processes is crucial for ensuring high-quality patient care, improving
the work-life balance of healthcare professionals, and reducing costs to sustain healthcare systems [2]. This thesis explores the application of Process Mining (PM) techniques
to analyse audit logs from the Austrian electronic health record (ELGA), specifically
within the Bereich Wien based on the local Audit Record Repository (L-ARR). By leveraging process mining, the work aims to identify vulnerabilities, efficiency potentials, and
optimization possibilities in healthcare data management processes.
This work demonstrates the suitability of L-ARR data for process mining, revealing
key patterns, potential security threats, and performance bottlenecks that could impact
the information exchange within the Austrian healthcare system. Through various filtering techniques and PM analysis, the research successfully identifies critical patterns
and frequent process behaviours. By this, the foundation for future applications in the
productive environment of ELGA Bereich Wien is established. Although the analysis
was conducted in a testing environment and limited to selected PM techniques, the
findings highlight the significant potential of process mining in improving the quality,
accuracy, and efficiency of healthcare services.
| Date of Award | 2024 |
|---|---|
| Original language | English (American) |
| Supervisor | Emmanuel Helm (Supervisor) |