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Introduction: Many hospitals are increasing their efforts to improve processes because processes play an important role in enhancing work efficiency and reducing costs. However, to date, a quantitative tool has not been available to examine the before and after effects of processes and environmental changes, other than the use of indirect indicators, such as mortality rate and readmission rate.
Methods: This study used process mining technology to analyze process changes based on changes in the hospital environment, such as the construction of a new building, and to measure the effects of environmental changes in terms of consultation wait time, time spent per task, and outpatient care processes. Using process mining technology, electronic health record (EHR) log data of outpatient care before and after constructing a new building were analyzed, and the effectiveness of the technology in terms of the process was evaluated.
Results: Using the process mining technique, we found that the total time spent in outpatient care did not increase significantly compared to that before the construction of a new building, considering that the number of outpatients increased, and the consultation wait time decreased. These results suggest that the operation of the outpatient clinic was effective after changes were implemented in the hospital environment. We further identified improvements in processes using the process mining technique, thereby demonstrating the usefulness of this technique for analyzing complex hospital processes at a low cost.
Conclusion: This study confirmed the effectiveness of process mining technology at an actual hospital site. In future studies, the use of process mining technology will be expanded by applying this approach to a larger variety of process change situations.
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http://dx.doi.org/10.1016/j.ijmedinf.2015.12.018 | DOI Listing |
PLoS One
September 2025
Department of Smart Manufacturing, Industrial Perception and Intelligent Manufacturing Equipment Engineering Research Center of Jiangsu Province, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu, China.
In the field of quality control, metal surface defect detection is an important yet challenging task. Although YOLO models perform well in most object detection scenarios, metal surface images under operational conditions often exhibit coexisting high-frequency noise components and spectral aliasing background textures, and defect targets typically exhibit characteristics such as small scale, weak contrast, and multi-class coexistence, posing challenges for automatic defect detection systems. To address this, we introduce concepts including wavelet decomposition, cross-attention, and U-shaped dilated convolution into the YOLO framework, proposing the YOLOv11-WBD model to enhance feature representation capability and semantic mining effectiveness.
View Article and Find Full Text PDFRSC Adv
September 2025
School of Chemical Engineering, Minhaj University Lahore Lahore 54000 Punjab Pakistan.
Naomaohu lignite (NL) from Hami, Xinjiang, was ultrasonically extracted with a mixed solvent of CS and acetone (in equal volumes) to obtain the extract residue (ER). The ER was then separated based on density differences with CCl to yield the corresponding light residue (NL-L). The composition and structural characteristics of the light residue were characterized by proximate, ultimate, infrared, and thermogravimetric analyses (TG-DTG).
View Article and Find Full Text PDFEnviron Res
September 2025
National Key Laboratory of Deep Coal Mining Safety and Environmental Protection, Anhui University of Science and Technology, Huainan, 232001, Anhui, China.
Zeolite synthesis from fly ash offers recycling and environmental benefits for carbon dioxide capture, but varying fly ash composition from different sources has different compositions, leading to inconsistent adsorption results. To achieve high CO adsorption performance and stability in zeolite synthesis from fly ash systems, this study established an element-controlled simulated fly ash system with Ca/Fe gradient differences. Hydrothermal synthesis yielded zeolites with optimized oxide ratios for CO adsorption.
View Article and Find Full Text PDFUltrasonics
September 2025
Faculty of Land Resource Engineering, Kunming University of Science and Technology, Yunnan 650093, China; Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area, Ministry of Natural Resources of the People's Republic of China, Yunnan Province, Kunming, Yunnan
Identifying and predicting the catastrophic failure of brittle rock remains a challenging task, yet it is crucial for developing early warning systems and preventing dynamic rock hazards. In this study, we employed the propagative parameters of ultrasonic waves and information from acoustic emission (AE) events to characterize the brittle failure of a flawed sandstone sample under uniaxial compression. A sliding event window method was developed to obtain the temporal b-value, effectively revealing microcrack growth based on the frequency-magnitude distribution of AE events.
View Article and Find Full Text PDFCereb Cortex
August 2025
Faculty of Psychology and Education Science, Department of Psychology, University of Geneva, Chemin des Mines 9, Geneva, 1202, Switzerland.
Language learning and use relies on domain-specific, domain-general cognitive and sensory-motor functions. Using fMRI during story listening and behavioral tests, we investigated brain-behavior associations between linguistic and non-linguistic measures in individuals with varied multilingual experience and reading skills, including typical reading participants (TRs) and dyslexic readers (DRs). Partial Least Square Correlation revealed a main component linking cognitive, linguistic, and phonological measures to amodal/associative brain areas.
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