Azcárate Camio, Cristina

Loading...
Profile Picture

Email Address

Birth Date

Job Title

Last Name

Azcárate Camio

First Name

Cristina

person.page.departamento

Estadística, Informática y Matemáticas

person.page.instituteName

ISC. Institute of Smart Cities

person.page.observainves

person.page.upna

Name

Search Results

Now showing 1 - 2 of 2
  • PublicationOpen 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.
  • PublicationOpen Access
    Modelado de la atención en consulta externa en un hospital público: una herramienta de gestión
    (Pontificia Universidad Javeriana (Colombia), 2014) Gáfaro Rojas, Aurora Inés; Mallor Giménez, Fermín; Azcárate Camio, Cristina; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
    Problema: aunque se dispone de herramientas que pueden apoyar la planificación de las actividades asistenciales, hasta el momento no existe una distribución de los servicios de atención en salud cuya estructura orgánica obtenga resultados óptimos, es decir, que garantice un flujo normal de pacientes sin generar colas excesiva, con tiempos de espera adecuados, disponibilidad apropiada de personal y directrices estratégicas de programas concretos, centrados en la concepción y organización de actividades de acuerdo con la demanda de la población atendida. Objetivo: describir y aplicar una herramienta para modelar el proceso de llegadas de pacientes en un hospital colombiano, encaminado al mejoramiento de la gestión organizacional. Método: este estudio corresponde a una investigación operativa que aplica un modelo de simulación. Resultado: se generó un modelo matemático útil en otros contextos similares para la generación de llegadas o análisis de la afluencia de pacientes.