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  1. Home
  2. Browse by Author

Browsing by Author "Sepúlveda, Marcos "

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    Analysis of Emergency Room Episodes Duration Through Process Mining
    (2019) Rojas, Eric; Cifuentes Soto, Andrés Alonso; Burattin, A.; Muñoz Gama, Jorge; Sepúlveda, Marcos; Capurro, Daniel
    This study presents the proposal of a performance analysis method for ER Processes through Process Mining. This method helps to determine which activities, sub-processes, interactions and characteristics of episodes explain why the process has long episode duration, besides providing decision makers with additional information that will help to decrease waiting times, reduce patient congestion and increment quality of provided care. By applying the exposed method to a case study, it was discovered that when a loop is formed between the Examination and Treatment sub-processes, the episode duration lengthens. Moreover, the relationship between case severity and the number of repetitions of the Examination-Treatment loop was also studied. As the case severity increases, the number of repetitions increases as well.
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    Analyzing medical emergency processes with process mining: the stroke case
    (2019) Fernandez-Llatas, Carlos; Ibanez-Sanchez, Gema; Celda, Angeles; Mandingorra, Jesus; Aparici-Tortajada, Lucia; Martinez-Millana, Antonio; Munoz-Gama, Jorge; Sepúlveda, Marcos; Rojas, Eric; Gálvez, Víctor; Capurro, Daniel; Traver, Vicente
    Medical emergencies are one of the most critical processes that occurs in a hospital. The creation of adequate and timely triage protocols, can make the difference between the life and death of the patient. One of the most critical emergency care protocols is the stroke case. This disease demands an accurate and quick diagnosis for ensuring an immediate treatment in order to limit or even, avoid, the undesired cognitive decline. The aim of this paper is perform an analysis of how Process Mining techniques can support health professionals in the interactive analysis of emergency processes considering critical timing of Stroke, using a Question Driven methodology. To demonstrate the possibilities of Process Mining in the characterization of the emergency process, we have used a real log with 9046 emergency episodes from 2145 stroke patients that occurred from January of 2010 to June of 2017. Our results demonstrate how Process Mining technology can highlight the differences of the stroke patient flow in emergency, supporting professionals in the better understanding and improvement of quality of care.
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    Backpack Process Model (BPPM): A Process Mining Approach for Curricular Analytics
    (MDPI, 2021) Salazar Fernandez, Juan Pablo; Muñoz Gama, Jorge; Maldonado Mahauad, Jorge; Bustamante, Diego; Sepúlveda, Marcos
    Curricular analytics is the area of learning analytics that looks for insights and evidence on the relationship between curricular elements and the degree of achievement of curricular outcomes. For higher education institutions, curricular analytics can be useful for identifying the strengths and weaknesses of the curricula and for justifying changes in learning pathways for students. This work presents the study of curricular trajectories as processes (i.e., sequence of events) using process mining techniques. Specifically, the Backpack Process Model (BPPM) is defined as a novel model to unveil student trajectories, not by the courses that they take, but according to the courses that they have failed and have yet to pass. The usefulness of the proposed model is validated through the analysis of the curricular trajectories of N = 4466 engineering students considering the first courses in their program. We found differences between backpack trajectories that resulted in retention or in dropout; specific courses in the backpack and a larger initial backpack sizes were associated with a higher proportion of dropout. BPPM can contribute to understanding how students handle failed courses they must retake, providing information that could contribute to designing and implementing timely interventions in higher education institutions.
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    Interactive Process Mining for Medical Training
    (2020) Muñoz, Gama Jorge; Victor, Galvez; Rene de la Fuente; Sepúlveda, Marcos; Fuentes, Ricardo
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    PALIA-ER: Bringing question-driven process mining closer to the emergency room
    (2017) Rojas, Eric; Fernández-Llatas, Carlos; Traver, Vicente; Muñoz-Gama, Vicente; Sepúlveda, Marcos; Herskovic, Valeria; Capurro, Daniel
    This paper presents PALIA-ER, a web-based tool for question-driven process mining in Emergency Room. PALIA-ER uses Palia discovery algorithm and includes model simplification and filtering features specially domain-specific for ER. Most PALIA-ER functionalities can be easily applied to other interdisciplinary contexts such as other healthcare units, education, or logistics.
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    Process mining in healthcare: A literature review
    (2016) Sepúlveda, Marcos
    Process Mining focuses on extracting knowledge from data generated and stored in corporate information systems in order to analyze executed processes. In the healthcare domain, process mining has been used in different case studies, with promising results. Accordingly, we have conducted a literature review of the usage of process mining in healthcare. The scope of this review covers 74 papers with associated case studies, all of which were analyzed according to eleven main aspects, including: process and data types; frequently posed questions; process mining techniques, perspectives and tools; methodologies; implementation and analysis strategies; geographical analysis; and medical fields. The most commonly used categories and emerging topics have been identified, as well as future trends, such as enhancing Hospital Information Systems to become process-aware. This review can: (i) provide a useful overview of the current work being undertaken in this field; (ii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches for their own applications; and (iii) highlight the use of process mining to improve healthcare processes.
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    Towards a Taxonomy of Human Resource Allocation Criteria
    (2018) Muñoz Gama, Jorge; Sepúlveda, Marcos ; Arias, Michael
    Allocating the most appropriate resource to execute the activities of a business process is a key aspect within the organizational perspective. An optimal selection of the resources that are in charge of executing the activities may contribute to improve the efficiency and the performance of the business processes. Despite the existence of resource metamodels that seek to provide a better representation of resources, a detailed classification of the allocation criteria that have been used to evaluate resources is missing. In this paper, we provide an initial proposal for a resource allocation criteria taxonomy. This taxonomy is based on an extensive literature review that yielded 2,370 articles regarding the existing resource allocation approaches within the business process management discipline, from which 95 articles were considered for the analysis. The proposed taxonomy points out the most frequently used criteria for assessing the resources from January 2005 to July 2016.

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