ArticlePLOS digital health2025
Utilizing process mining in quality management: A case study in radiation oncology.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Enhancing labour efficiency in coffee harvesting using process mining and statistical analysis.BMC plant biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiation oncology is known for its complexity, inherent risks, and sheer volume of data. Adopting a process-oriented management approach and systemic thinking is essential for ensuring safety, efficiency, and the highest quality of care. Process mining offers a data-centric method for analyzing and improving clinical workflows to ensure optimal patient outcomes. This study utilizes process mining techniques along with a quality management system to analyze event logs obtained from an electronic medical record system. Conformance checking and process improvement methodologies were utilized to detect inefficiencies and bottlenecks. Examining the treatment planning process through process mining revealed two principal bottlenecks-OAR contouring and physics chart checks. This led to specific interventions that markedly decreased the time to complete treatment planning processes. Additionally, applying organizational mining methods provided valuable information on how resources are utilized and how teams collaborate within the organization. Process mining is a useful tool for improving efficiency, quality, and decision-making in radiation oncology. By transitioning from traditional management to a data-driven leadership approach, radiation oncology departments can optimize workflows, enhance patient care, and adapt to the evolving demands of modern healthcare.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.