Event Log Generation in a Health System: A Case Study

Remy, Simon; Pufahl, Luise; Sachs, Jan Philipp; Böttinger, Erwin P.; Weske, Mathias

doi:10.1007/978-3-030-58666-9_29

Cited by 10 publications

(13 citation statements)

References 21 publications

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“…The authors classify different source systems based on the abstraction level and the data accuracy. Those findings are confirmed in a case study [16] on event log generation in healthcare in which event abstraction challenges and the need for suitable techniques, like abstraction tables, are discussed. In order to investigate treatment processes, the authors of [5] use, similarly to [11], sub-processes to encapsulate low-level events of treatment processes in sub-processes.…”

Section: Related Workmentioning

confidence: 59%

“…To demonstrate the usefulness of the proposed method, we created and analyzed two event logs using a prototypical implementation 4 . A detailed description of the event log generation pipeline can be found in [16]. Each log comprises 2,000 patients diagnosed with low back pain from the Mount Sinai Health System with a focus on the treatment processes.…”

Section: Discussionmentioning

confidence: 99%

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Domain-Specific Event Abstraction

et al. 2021

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Process mining aims at deriving process knowledge from event logs, which contain data recorded during process executions. Typically, event logs need to be generated from process execution data, stored in different kinds of information systems. In complex domains like healthcare, data is available only at different levels of granularity. Event abstraction techniques allow the transformation of events to a common level of granularity, which enables effective process mining. Existing event abstraction techniques do not sufficiently take into account domain knowledge and, as a result, fail to deliver suitable event logs in complex application domains.This paper presents an event abstraction method based on domain ontologies. We show that the method introduced generates semantically meaningful high-level events, suitable for process mining; it is evaluated on real-world patient treatment data of a large U.S. health system.

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Section: Related Workmentioning

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Domain-Specific Event Abstraction

et al. 2021

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“…When business processes are supported in their execution by an information system or a Business Process Management System (BPMS), then process execution data is stored, from which event logs can be generated [44]. Event logs are useful for an evidence-based process analysis with the help of process mining techniques, such as the automated discovery of process models or the enhancement of process models by resource information [55].…”

Section: Hospital Information Systemmentioning

confidence: 99%

Automatic Resource Allocation in Business Processes: A Systematic Literature Survey

Pufahl,

Ihde,

Stiehle

et al. 2021

Preprint

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For delivering products or services to their clients, organizations execute manifold business processes. During such execution, upcoming process tasks need to be allocated to internal resources. Resource allocation is a complex decision-making problem with high impact on the effectiveness and efficiency of processes. A wide range of approaches was developed to support research allocation automatically. This systematic literature survey provides an overview of approaches and categorizes them regarding their resource allocation goals and capabilities, their use of models and data, their algorithmic solutions, and their maturity. Rule-based approaches were identified as dominant, but heuristics and learning approaches also play a relevant role.

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“…One can make use of a plethora of event log extraction approaches to construct an event log around a specific case notion from a database of a given organization [2], [6]. Therefore, it is possible to extract several event logs, each pertaining to a different case notion, from the same source of information.…”

Section: Preliminariesmentioning

confidence: 99%

“…In traditional process mining, event logs are extracted from the databases of a given organization. Typical event log extraction approaches require extensive access to the database tables and detailed knowledge about the database schema [2]. If this information is not available, other sources of information have to be tapped to extract event logs, primarily redo logs.…”

Section: Introductionmentioning

confidence: 99%

Database-Less Extraction of Event Logs from Redo Logs

et al. 2021

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Process mining is widely adopted in organizations to gain deep insights about running business processes. This can be achieved by applying different process mining techniques like discovery, conformance checking, and performance analysis. These techniques are applied on event logs, which need to be extracted from the organization’s databases beforehand. This not only implies access to databases, but also detailed knowledge about the database schema, which is often not available. In many real-world scenarios, however, process execution data is available as redo logs. Such logs are used to bring a database into a consistent state in case of a system failure. This paper proposes a semi-automatic approach to extract an event log from redo logs alone. It does not require access to the database or knowledge of the databaseschema. The feasibility of the proposed approach is evaluated on two synthetic redo logs.

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Event Log Generation in a Health System: A Case Study

Cited by 10 publications

References 21 publications

Domain-Specific Event Abstraction

Domain-Specific Event Abstraction

Automatic Resource Allocation in Business Processes: A Systematic Literature Survey

Database-Less Extraction of Event Logs from Redo Logs

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