Open Access
Motor unit action potential duration, II: a new automatic measurement method based on the wavelet transform
(Lippincott, Williams & Wilkins, 2007) Rodríguez Carreño, Ignacio; Gila Useros, Luis; Malanda Trigueros, Armando; García Gurtubay, Ignacio; Mallor Giménez, Fermín; Gómez Elvira, Sagrario; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Estadística e Investigación Operativa; Ingeniaritza Elektrikoa eta Elektronikoa; Estatistika eta Ikerketa Operatiboa
To present and evaluate a new algorithm, based on the wavelet transform, for the automatic measurement of motor unit action potential (MUAP) duration. A total of 240 MUAPs were studied. The waveform of each MUAP was wavelet-transformed, and the start and end points were estimated by regarding the maxima and minima points in a particular scale of the wavelet transform. The results of the new method were compared with the gold standard of duration marker positions obtained by manual measurement. The new method was also compared with a conventional algorithm, which we had found to be best in a previous comparative study. To evaluate the new method against manual measurements, the dispersion of automatic and manual duration markers were analyzed in a set of 19 repeatedly recorded MUAPs. The differences between the new algorithm’s marker positions and the gold standard of duration marker positions were smaller than those observed with the conventional method. The dispersion of the new algorithm’s marker positions was slightly less than that of the manual one. Our new method for automatic measurement of MUAP duration is more accurate than other available algorithms and more consistent than manual measurements.
Open Access
Coping with stress in emergency department physicians through improved patient-flow management
(Elsevier, 2020) Cildoz Esquíroz, Marta; Ibarra, Amaia; Mallor Giménez, Fermín; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas
This paper provides a method for the real-time monitoring of job stress in emergency department (ED) physicians. It is implemented in a Decision Support System (DSS) designed for patient-to-physician assignment after triage. Our concept of job stress includes not only the workload but also time pressure and uncertainty. A job stress function is estimated based on the consensus views of ED physicians obtained through a novel methodology involving stress factor analysis, questionnaire design, and the statistical analysis of expert opinions. The resulting stress score enables the assessment of job stress using workload data from the ED physicians’ whiteboard. These data can be used for the real-time measurement and monitoring of ED physician job stress in a stochastic and dynamic environment, which is the main novelty of this method as compared to previous workload and stress measurement proposals. A further advantage of this methodology is that it is general enough to be adapted to physician job stress monitoring in any ED. The use of the DSS for ED patient-flow management reduces job stress and spreads it more evenly among the whole team of physicians, while also improving other important ED performance measures such as arrival-to-provider time and the percentage of compliance with patient waiting time targets. A case study illustrates the application of the methodology for the construction of a stress-score, the monitoring of physician stress levels, and ED patient-flow management.
Open Access
Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast
(Elsevier, 2015-11-21) Frías Paredes, Laura; Mallor Giménez, Fermín; León, Teresa; Gastón Romeo, Martín; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa; Institute of Smart Cities - ISC
Wind has been the largest contributor to the growth of renewal energy during the early 21st century. However, the natural uncertainty that arises in assessing the wind resource implies the occurrence of wind power forecasting errors which perform a considerable role in the impacts and costs in the wind energy integration and its commercialization. The main goal of this paper is to provide a deeper insight in the analysis of timing errors which leads to the proposal of a new methodology for its control and measure. A new methodology, based on Dynamic TimeWarping, is proposed to be considered in the estimation of accuracy as attribute of forecast quality. A new dissimilarity measure, the Temporal Distortion Index, among time series is introduced to complement the traditional verication measures found in the literature. Furthermore we provide a bi-criteria perspective to the problem of comparing different forecasts. The methodology is illustrated with several examples including a real case.
Open Access
Accumulating priority queues versus pure priority queues for managing patients in emergency departments
(Elsevier, 2019) Cildoz Esquíroz, Marta; Ibarra, Amaia; Mallor Giménez, Fermín; Institute of Smart Cities - ISC
Improving the quality of healthcare in emergency departments (EDs) is at the forefront of many hospital managers’ efforts, as they strive to plan and implement better patient flow strategies. In this paper, a new approach to manage the patient flow in EDs after triage is proposed. The new queue discipline, named accumulative priority queue with finite horizon and denoted by APQ-h, is an extension of the accumulative priority queue (APQ) discipline that considers not only the acuity level of patients and their waiting time but also the stage of the healthcare treatment. APQ disciplines have been studied in the literature from a queueing theory point of view, which requires assumptions rarely found in real EDs, such as homogeneity in the patient arrival pattern and only one service stage. The APQ-h discipline accumulates priority from the point of waiting for the first physician consultation until the moment the waiting time exceeds the upper time limit set to access the physician after the patient's arrival. A recent study shows that a management strategy of this type is applied in practice in several Canadian EDs. The main aim of this paper is to explore the implementation of APQ-h managing policies in a real ED. For this purpose, a simulation model replicating a real ED is developed. This simulation model is also used to obtain the optimal APQ type polices through a simulation-based optimization method that solves a multi-objective and stochastic optimization problem. Arrival to provider time and total waiting time in the ED are considered to be the key ED performance indicators. An extensive computational analysis shows the flexibility of the APQ-h and APQ discipline and their superiority over other pure priority disciplines in a real setting and in a variety of ED scenarios. In addition, no superiority over the APQ discipline is demonstrated. © 2019 The Authors
Open Access
Un modelo para predecir cuántas camas UCI harán falta durante cada oleada
(Asociacion the Conversation España, 2021) Mallor Giménez, Fermín; García de Vicuña Bilbao, Daniel; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
La crisis financiera mundial de 2008 puso de moda en España el término económico “prima de riesgo”, hasta entonces desconocido. Del mismo modo, la pandemia ha popularizado expresiones y términos como “doblar la curva”, “incidencia acumulada” e incluso conceptos epidemiológicos más específicos como “el número efectivo de reproducción R₀”. Ocupan portadas de periódicos, así como espacios en noticiarios televisivos y radiofónicos. Constituyen una muestra del uso de las matemáticas para describir la evolución de la pandemia y para proporcionar indicadores con los que las autoridades políticas pueden fundamentar una toma de decisiones informada sobre medidas de distanciamiento social y restricciones a la movilidad. Sin embargo, los modelos matemáticos no solo sirven para describir qué ha pasado o el estado actual de la pandemia, sino que pueden facilitar predicciones muy útiles sobre cómo va a evolucionar. Estas son útiles para la planificación de los recursos sanitarios necesarios para atender a paciente covid-19, como las camas UCI. La planificación facilita la utilización eficiente de recursos y, en consecuencia, proporcionar una mejor atención a todos los pacientes, covid y no covid. Los modelos matemáticos más útiles para predecir variables relacionadas con la evolución de la pandemia son los de simulación. Estos modelos son capaces de representar características complejas de la realidad pandémica, como su aleatoriedad e incertidumbre, así como la variabilidad en el impacto que la enfermedad puede tener en distintas personas
Open Access
Simulation of household electricity consumption by using functional data analysis
(Taylor & Francis, 2018) Mallor Giménez, Fermín; Moler Cuiral, José Antonio; Urmeneta Martín-Calero, Henar; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
Open Access
Design exploration prior to blade multi-disciplinary optimisation
(IOP Publishing, 2018) Echeverría Durá, Fernando; Mallor Giménez, Fermín; San Miguel, Unai; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The approach of designing blades as a multi-disciplinary, holistic optimisation implies significant challenges owing to the high complexity of the involved factors such as aerodynamics, elasticity, controller and loads. Moreover, the large number of design variables complicates the intuitive analysis of the relationship between the design variables and responses. This paper presents the design variable exploration prior to blade optimisation, which reveals certain design variable combinations that lead to undesirable dynamic load amplification. Statistical tools, such as multiple logistic regression and fast and frugal decision trees, are applied to identify the conditions causing the phenomenon and predict the possible appearance under new design variable combinations.
Open Access
Assessing the impact of physicians' behavior variability on performance indicators in emergency departments: an agent-based model
(IEEE, 2025-01-20) Baigorri Iguzquiaguirre, Miguel; Cildoz Esquíroz, Marta; Mallor Giménez, Fermín; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
In emergency departments (EDs), traditional simulation models often overlook the variability in physician practice, assuming uniform service provision. Our study introduces a hybrid agent-based discrete-event simulation (AB-DES) model to capture this variability. Through simulation scenarios based on real ED data, we assess the impact of physician behavior on key performance indicators such as patient waiting times and physician stress levels. Results show significant variability in both individual physician performance and average metrics across scenarios. By integrating physician agent modeling, informed by literature from medical and workplace psychology, our approach offers a more nuanced representation of ED dynamics. This model serves as a foundation for future developments towards digital twins, facilitating real-time ED management. Our findings emphasize the importance of considering physician behavior for accurate performance assessment and optimization.
Open Access
A GRASP-based algorithm for solving the emergency room physician scheduling problem
(Elsevier, 2021) Cildoz Esquíroz, Marta; Mallor Giménez, Fermín; Mateo, Pedro; Institute of Smart Cities - ISC
This paper addresses a physician scheduling problem in an Emergency Room (ER) requiring a long-term work calendar to allocate work days and types of shift among all the doctors. The mathematical model is created without simplifications, using the real calendar, including holidays. This precludes the possibility of cyclic-type solutions, and involves numerous and varied constraints (demand, workload, ergonomics, fairness, etc.). An effective solution to this very difficult practical problem cannot be obtained, for large instances, with exact solution methods. We formulate a mathematical representation of a real-world ER physician scheduling problem featuring a hybrid algorithm combining continuous linear programming with a greedy randomized adaptive search procedure (GRASP). Linear programming is used to model a general physician-demand covering problem, where the solution is used to guide the construction phase of the GRASP, to obtain initial full schedules for subsequent improvement by iterative application of Variable Neighborhood Descent Search (VNDS) and Network Flow Optimization (NFO). A computational study shows the superiority of our approach over the Integer Linear Programming method in a set of instances of varying size and difficulty inspired by a real setting. The methodology is embedded in a software tool for generating one-year-ahead physician schedules for a local ER. These solutions, which are now in use, outperform the manually-created schedules used previously. © 2021 Elsevier B.V.
Open Access
The problem of the last bed: contextualization and a new simulation framework for analyzing physician decisions
(Elsevier, 2019) Azcárate Camio, Cristina; Esparza, Laida; Mallor Giménez, Fermín; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Faced with a full Intensive Care Unit (ICU), physicians need to decide between turning away a new patient in need of critical care and creating a vacancy by prematurely discharging a current occupant. This dilemma is widely discussed in the medical literature, where the influencing factors are identified, the patient discharge process described and the patient health consequences analyzed. Nevertheless, the existing mathematical models of ICU management practices overlook many of the factors considered by physicians in real-world triage decisions. This paper offers a review of the medical and mathematical literature on patient discharge decisions, and a proposal for a new simulation framework to enable more realistic mathematical modeling of the real-world patient discharge process. Our model includes a) the times at which discharge decisions are made and setup times for patient transfer from the ICU to a general ward and preparation of an ICU bed for an incoming patient, in order to capture the impossibility of an immediate switch of patients; b) advance notice of the number of patients due to arrive from elective surgery requiring intensive postoperative care and potentially triggering the need for early discharges to avoid surgery cancelations; and c) patient health status (to reflect the dependency of physicians’ discharge decisions on health indicators) by modeling length of stay with a phase-type distribution in which a medical meaning is assigned to each state. A simulation-based optimization method is also proposed as a means to obtain optimal discharge decisions as a function of the health status of current patients, the bed occupancy level and the number of planned arrivals from elective surgery over the following days. Optimal decisions should strike a balance between patient rejection and LoS reduction. This new simulation framework generates an optimal discharge policy, which closely resembles real decision-making under a cautious discharge policy, where the frequency of early discharge increases with the ICU occupancy level. This is a contrast with previous simulation models, which consider only the triage of the last bed, disregarding the pressures on physicians faced with high bed occupancy levels.