ArticleInternational journal of environmental research and public health2020
Process Mining-Supported Emergency Room Process Performance Indicators.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Overcrowding Indicators in Emergency Departments Across Countries: Scoping Review.Interactive journal of medical research · 2026Review
- Data-driven queueing modelling: a simulation case study of emergency department crowding.BMJ health & care informatics · 2026Article
- Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway.BMC medical research methodology · 2024Article
- Investigating the service utilization and pathways of patients with alcohol use disorders.Alcohol and alcoholism (Oxford, Oxfordshire) · 2024Article
- Article
- Observational
- Signal from the noise: A mixed graphical and quantitative process mining approach to evaluate care pathways applied to emergency stroke care.Journal of biomedical informatics · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Emergency room processes are often exposed to the risk of unexpected factors, and process management based on performance measurements is required due to its connectivity to the quality of care. Regarding this, there have been several attempts to propose a method to analyze the emergency room processes. This paper proposes a framework for process performance indicators utilized in emergency rooms. Based on the devil's quadrangle, i.e., time, cost, quality, and flexibility, the paper suggests multiple process performance indicators that can be analyzed using clinical event logs and verify them with a thorough discussion with clinical experts in the emergency department. A case study is conducted with the real-life clinical data collected from a tertiary hospital in Korea tovalidate the proposed method. The case study demonstrated that the proposed indicators are well applied using the clinical data, and the framework is capable of understanding emergency room processes' performance.
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Registered trials
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