Browsing by Author "Rojas, Eric"

Now showing 1 - 15 of 15
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    A Framework for Recommending Resource Allocation based on Process Mining
    (2016) Arias, Michael; Rojas, Eric; Muñoz Gama, Jorge; Sepúlveda Fernández, Marcos Ernesto
    Dynamically allocating the most appropriate resource to execute the different activities of a business process is an important challenge in business process management. An ineffective allocation may lead to an inadequate resources usage, higher costs, or a poor process performance. Different approaches have been used to solve this challenge: data mining techniques, probabilistic allocation, or even manual allocation. However, there is a need for methods that support resource allocation based on multi-factor criteria. We propose a framework for recommending resource allocation based on Process Mining that does the recommendation at sub-process level, instead of activity-level. We introduce a resource process cube that provides a flexible, extensible and fine-grained mechanism to abstract historical information about past process executions. Then, several metrics are computed considering different criteria to obtain a final recommendation ranking based on the BPA algorithm. The approach is applied to a help desk scenario to demonstrate its usefulness.
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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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    BPIC 2013: Volvo incident and problem management behavior analysis
    (2013) Arias, Michael; Rojas, Eric
    This essay has the purpose of presenting the results of a work performed as part of Third International Business Process Intelligence Challenge. This challenge presents an event log from Volvo IT Belgium Company related with incident and problem management, focusing on a couple process owner´s questions. The authors of this document present the analysis realized applying different kind of tools and process mining techniques in order to solve the challenge presented. We provide an analysis, which discovered behavior characteristics, associated with products, resources and organizational lines. The results obtained provide useful information that Volvo can use to have more knowledge about the process that they are executing and have more information to make decisions and improve the actual process.
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    Characterization of Drug Use Patterns Using Process Mining and Temporal Abstraction Digital Phenotyping
    (2019) Rojas, Eric; Capurro Nario, Daniel Alejandro
    Understanding and identifying executed patterns, activitiesand processes for patients of different characteristics provides medicalexperts a deep understanding of which tasks are critical in the providedcare, and may help identify ways to improve them. However, extractingthese events and data for patients with complex clinical phenotypes isnot a trivial task. This paper provides an approach to identifying specificpatient cohorts based on complex digital phenotypes as a starting pointto apply process mining tools and techniques and identify patterns orprocess models. Using temporal abstraction-based digital phenotypingand pattern matching, we identified a cohort of patients with sepsis fromthe MIMIC II database, and then apply process mining techniques todiscover medication use patterns. In the case study we present, the useof temporal abstraction digital phenotyping helped us discover a relevantpatient cohort, aiding in the extraction of the data required to generatedrug use patterns for medications of different types such as vasopressors,vasodilators and systemic antibacterial antibiotics. For sepsis patients,combining the use of temporal abstraction digital phenotyping and process mining tools and techniques, was proven to help extract accuratecohorts of patients for health care process mining.
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    Clinical processes and its data, what can we do with them?
    (2015) Rojas, Eric; Arias, Michael; Sepúlveda Fernández, Marcos Ernesto
    Global healthcare services have evolved over time, and nowadays they are expected to follow high-quality optimized standards. Analyzing healthcare processes has become a relevant field of study, and different techniques and tools have been developed to promote improvements in the efficiency and effectiveness of these processes. There is a research field called process mining that can be used to extract knowledge from the event data stored in the hospital information systems. With the help of this, it is possible to discover the real executed process, examine its performance and analyze the resource interaction during its execution. The goal of this article is to provide a bibliographic survey about the use of process mining algorithms, techniques, and tools in the analysis of healthcare processes, providing a general overview about the main approaches previously used and the information required to apply them in the medical field. We provide important insights about data, algorithms, techniques and methodologies that are required to help answer medical expert questions about their processes, motivating and inspiring a broader usage. So, if we have the information and it is possible to analyze and understand the healthcare processes, why are we not doing it?
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    Deciphering event logs in SharePoint Server: A methodology based on process mining
    (IEEE, 2014) Arias, Michael; Rojas, Eric
    Nowadays, the information systems are an indispensable resource for the organizations. The processes that are managed through these systems most of the time are hard to understand, maintain and improve. The data associated to the process becomes the main source and input to do all types of analysis. Process Mining allows the extraction of useful knowledge from the generated information of the corporate systems. This work suggests a methodology based on process mining to execute process support analysis of a corporate intranet implemented in SharePoint Server. With the extracted information it is possible to do analysis from several perspectives. The obtained results allow administrators of this type of technology platforms to evaluate the techniques used and generate benefits. The methodology was applied in a case study for a Retail client, besides doing an exploratory analysis of the data for two additional clients in the Industrial Safety industry in Chile.
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    Discovering role interaction models in the Emergency Room using Process Mining
    (2018) Alvarez, Camilo; Rojas, Eric; Arias, Michael; Munoz-Gama, Jorge; Sepulveda, Marcos; Herskovic, Valeria; Capurro, Daniel
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    Individual Behavior Modeling with Sensors Using Process Mining
    (2019) Dogan, Onur; Martinez-Millana, Antonio; Rojas, Eric; Sepúlveda Fernández, Marcos Ernesto; Muñoz Gama, Jorge; Traver, Vicente; Fernandez-Llatas, Carlos
    Understanding human behavior can assist in the adoption of satisfactory healthinterventions and improved care. One of the main problems relies on the definition of humanbehaviors, as human activities depend on multiple variables and are of dynamic nature. Althoughsmart homes have advanced in the latest years and contributed to unobtrusive human behaviortracking, artificial intelligence has not coped yet with the problem of variability and dynamismof these behaviors. Process mining is an emerging discipline capable of adapting to the nature ofhigh-variate data and extract knowledge to define behavior patterns. In this study, we analyze datafrom 25 in-house residents acquired with indoor location sensors by means of process miningclustering techniques, which allows obtaining workflows of the human behavior inside the house.Data are clustered by adjusting two variables: the similarity index and the Euclidean distancebetween workflows. Thereafter, two main models are created: (1) a workflow view to analyze thecharacteristics of the discovered clusters and the information they reveal about human behaviorand (2) a calendar view, in which common behaviors are rendered in the way of a calendarallowing to detect relevant patterns depending on the day of the week and the season of the year.Three representative patients who performed three different behaviors: stable, unstable, and complexbehaviors according to the proposed approach are investigated. This approach provides humanbehavior details in the manner of a workflow model, discovering user paths, frequent transitionsbetween rooms, and the time the user was in each room, in addition to showing the results into thecalendar view increases readability and visual attraction of human behaviors, allowing to us detectpatterns happening on special days.
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    Mapping the patient’s journey in healthcare through process mining
    (2020) Arias, M.; Rojas, Eric; Aguirre, S.; Cornejo, F.; Muñoz Gama, Jorge; Sepúlveda Fernández, Marcos Ernesto; Capurro, Daniel
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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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    Question-Driven Methodology for Analyzing Emergency Room Processes Using Process Mining
    (2017) Rojas, Eric; Sepúlveda Fernández, Marcos Ernesto; Muñoz Gama, Jorge; Capurro, Daniel; Traver, Vicente; Fernandez Llatas, Carlos
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    ResRec: A multi-criteria tool for resource recommendation
    (2016) Arias, Michael; Rojas, Eric; Lee, Wai Lam Jonathan; Muñoz Gama, Jorge; Sepúlveda Fernández, Marcos Ernesto
    Dynamic resource allocation is considered a key aspect withinbusiness process management. Selecting the most suitable resources is achallenge for those in charge of making the allocation, because the efficiency with which this task is executed, can contribute to the quality ofthe results, and improve the process performance. Different mechanismshave been proposed to improve resource allocation. However, there is aneed for more flexible allocation methods that integrate a set of conditions and requirements defined at run-time, and also, allow the combination of different criteria to evaluate resources. In this paper, we presentResRec, a novel Multi-factor Criteria tool that can be used to recommend and allocate resources dynamically. The tool provides the featureof solving individual requests (On-demand), or requests made in blocks(Batch) through a recommender system developed in ProM.
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    The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database
    (2018) Kurniati, Angelina Prima; Rojas, Eric; Hogg, David; Hall, Geoff; Johnson, Owen A.
    There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models.
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    The ClearPath Method for Care Pathway Process Mining and Simulation
    (2019) Johnson, Owen A.; Ba Dhafari, Thamer; Kurniati, Angelina; Fox, Frank; Rojas, Eric
    Process mining of routine electronic healthcare records can help inform the management of care pathways. Combining process mining with simulation creates a rich set of tools for care pathway improvement. Healthcare process mining creates insight into the reality of patients’ journeys through care pathways while healthcare process simulation can help communicate those insights and explore “what if” options for improvement. In this paper, we outline the ClearPath method, which extends the PM2 process mining method with a process simulation approach that address issues of poor quality and missing data and supports rich stakeholder engagement. We review the literature that informed the development of ClearPath and illustrate the method with case studies of pathways for alcohol-related illness, giant-cell arteritis and functional neurological symptoms. We designed an evidence template that we use to underpin the fidelity of our simulation models by tracing each model element back to literature sources, data and process mining outputs and insights from qualitative research. Our approach may be of benefit to others using process-oriented data science to improve healthcare.