Between prediction, education, and quality control: simulation models in critical care

被引:0
|
作者
Herwig Gerlach
Susanne Toussaint
机构
[1] Intensive Care Medicine,Department of Anaesthesia
[2] and Pain Management,undefined
[3] Vivantes – Klinikum Neukölln,undefined
来源
Critical Care | / 11卷
关键词
Critical Care; Teaching Tool; Carbon Dioxide Content; Microsimulation Model; Forward Process;
D O I
暂无
中图分类号
学科分类号
摘要
Today, computer-aided strategies in social sciences are an indispensable component of teaching programs. In recent years, microsimulation modeling has gained attention in its ability to represent predicted physiological developments visually, thus providing the user with a full understanding of the impacts of a proposed scheme. There are several microsimulation models in human medicine, and they can be either dynamic or static. If the model is dynamic the course of variables changes over time; in contrast, in the static case time constancy is assumed. In critical care there have been several approaches to implement microsimulation models to predict outcome. This commentary describes current approaches for predicting disease progression by using dynamic microsimulation in pneumonia-related sepsis.
引用
收藏
相关论文
共 50 条
  • [1] Between prediction, education, and quality control: Simulation models in critical care
    Gerlach, Herwig
    Toussaint, Susanne
    CRITICAL CARE, 2007, 11 (04):
  • [2] Outcome prediction in critical care: the Mortality Probability Models
    Higgins, Thomas L.
    Teres, Daniel
    Nathanson, Brian
    CURRENT OPINION IN CRITICAL CARE, 2008, 14 (05) : 498 - 505
  • [3] Leadership Education For Critical Care Fellows Using Simulation
    Steinbach, T. C.
    Adamson, R.
    Carlbom, D.
    Johnson, N. J.
    Kritek, P. A.
    Coruh, B.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2017, 195
  • [4] Fresh simulation options in critical care nursing education
    Archer, Elize
    AFRICAN JOURNAL OF HEALTH PROFESSIONS EDUCATION, 2010, 2 (02): : 29 - 32
  • [5] Using Simulation for Skill Acquisition in Critical Care Education
    Walker, Mandi
    Stevenson, Gina
    CRITICAL CARE NURSE, 2014, 34 (02) : E13 - E13
  • [6] CRITICAL CARE EDUCATION USING COMPUTER-SIMULATION
    EDMONDS, JF
    TAIT, GA
    BARKER, GA
    CLINICAL AND INVESTIGATIVE MEDICINE-MEDECINE CLINIQUE ET EXPERIMENTALE, 1986, 9 (03): : A26 - A26
  • [7] Performance of Critical Care Outcome Prediction Models in an Intermediate Care Unit
    Brusca, Rebeccah M.
    Simpson, Catherine E.
    Sahetya, Sarina K.
    Noorain, Zeba
    Tanykonda, Varshitha
    Stephens, R. Scott
    Needham, Dale M.
    Hager, David N.
    JOURNAL OF INTENSIVE CARE MEDICINE, 2020, 35 (12) : 1529 - 1535
  • [8] The Future of Critical Care Lies in Quality Improvement and Education
    Niven, Alexander S.
    Herasevich, Svetlana
    Pickering, Brian W.
    Gajic, Ognjen
    ANNALS OF THE AMERICAN THORACIC SOCIETY, 2019, 16 (06) : 649 - 656
  • [9] From quality control to quality insurance in critical care laboratory
    Truchaud, A
    Le Neel, T
    Brochard, H
    Malvaux, S
    Cazaubel, M
    Bard, JM
    ANNALES DE BIOLOGIE CLINIQUE, 2000, 58 (04) : 491 - 495
  • [10] THE USE OF PHARMACEUTICALS IN CRITICAL CARE - THE IMPORTANCE OF OUTCOME PREDICTION MODELS
    CLIFTON, GD
    BLUMENSCHEIN, K
    PHARMACOECONOMICS, 1995, 7 (05) : 388 - 392