Multi-Perspective Process Mining Interfaces for HL7 AuditEvent Repositories: XES and OCEL

Andreas Pointner; Oliver Krauss; Andreas Erhard; Andreas Schuler; Emmanuel Helm

doi:10.3233/SHTI230034

Multi-Perspective Process Mining Interfaces for HL7 AuditEvent Repositories: XES and OCEL

Andreas Pointner, Oliver Krauss, Andreas Erhard, Andreas Schuler, Emmanuel Helm

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

BACKGROUND: Medical information systems frequently use event logging, but these logs are not suitable for process mining as they are not logged in a standardized format. OBJECTIVES: Our goal is to enrich medical event logs for use in process mining. METHOD: We present an approach to convert events from standards- based repositories into the XES and OCEL formats commonly used in process mining. RESULTS: We tested this approach using simulated data from the Austrian breast cancer screening program. CONCLUSION: We aim to apply it to analyze care guidelines and improve hospital processes in the future.

Original language	English
Pages (from-to)	168-173
Number of pages	6
Journal	Studies in Health Technology and Informatics
Volume	301
DOIs	https://doi.org/10.3233/SHTI230034
Publication status	Published - 2 May 2023

Keywords

Data Mining
Electronic Health Records
Health Care
Process Assessment
Standard of Care
Austria
Hospitals
Hospital Information Systems
Process Assessment, Health Care

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3233/SHTI230034

Cite this

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title = "Multi-Perspective Process Mining Interfaces for HL7 AuditEvent Repositories: XES and OCEL",

abstract = "BACKGROUND: Medical information systems frequently use event logging, but these logs are not suitable for process mining as they are not logged in a standardized format. OBJECTIVES: Our goal is to enrich medical event logs for use in process mining. METHOD: We present an approach to convert events from standards- based repositories into the XES and OCEL formats commonly used in process mining. RESULTS: We tested this approach using simulated data from the Austrian breast cancer screening program. CONCLUSION: We aim to apply it to analyze care guidelines and improve hospital processes in the future.",

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author = "Andreas Pointner and Oliver Krauss and Andreas Erhard and Andreas Schuler and Emmanuel Helm",

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doi = "10.3233/SHTI230034",

language = "English",

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T1 - Multi-Perspective Process Mining Interfaces for HL7 AuditEvent Repositories

T2 - XES and OCEL

AU - Pointner, Andreas

AU - Krauss, Oliver

AU - Erhard, Andreas

AU - Schuler, Andreas

AU - Helm, Emmanuel

N1 - Funding Information: This project is financed by research subsidies granted by the government of Upper Austria. Publisher Copyright: © 2023 The authors, AIT Austrian Institute of Technology and IOS Press.

PY - 2023/5/2

Y1 - 2023/5/2

N2 - BACKGROUND: Medical information systems frequently use event logging, but these logs are not suitable for process mining as they are not logged in a standardized format. OBJECTIVES: Our goal is to enrich medical event logs for use in process mining. METHOD: We present an approach to convert events from standards- based repositories into the XES and OCEL formats commonly used in process mining. RESULTS: We tested this approach using simulated data from the Austrian breast cancer screening program. CONCLUSION: We aim to apply it to analyze care guidelines and improve hospital processes in the future.

AB - BACKGROUND: Medical information systems frequently use event logging, but these logs are not suitable for process mining as they are not logged in a standardized format. OBJECTIVES: Our goal is to enrich medical event logs for use in process mining. METHOD: We present an approach to convert events from standards- based repositories into the XES and OCEL formats commonly used in process mining. RESULTS: We tested this approach using simulated data from the Austrian breast cancer screening program. CONCLUSION: We aim to apply it to analyze care guidelines and improve hospital processes in the future.

KW - Data Mining

KW - Electronic Health Records

KW - Health Care

KW - Process Assessment

KW - Standard of Care

KW - Austria

KW - Hospitals

KW - Hospital Information Systems

KW - Process Assessment, Health Care

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SN - 0926-9630

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JO - Studies in Health Technology and Informatics

JF - Studies in Health Technology and Informatics

ER -

Multi-Perspective Process Mining Interfaces for HL7 AuditEvent Repositories: XES and OCEL

Abstract

Keywords

UN SDGs

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