Dynamics of Emergency Room Crowding with treatment spaces. Here we investigate the effect of constrained spaces and ignore any changes in treatment time or staffing effects. Many of the consequences occur before treatment with potential arrivals being turned away and arrivals leaving without being

Dynamics of Emergency Room Crowding with treatment spaces. Here we investigate the effect of constrained spaces and ignore any changes in treatment time or staffing effects. Many of the consequences occur before treatment with potential arrivals being turned away and arrivals leaving without being treated.  

 
 Adapted from Fig 7.1 p.269 of the Book: James A. Forte ( 2007),  Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice   Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Adapted from Fig 7.1 p.269 of the Book: James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice  Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Based on Psychological Medicine Dec 2015  article   Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder  by A. K. Wittenborn, H. Rahmandad, J. Rick and N. Hosseinichimeh, mentioned  here
Based on Psychological Medicine Dec 2015 article Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder by A. K. Wittenborn, H. Rahmandad, J. Rick and N. Hosseinichimeh, mentioned here
 Simplified version of  IM-852   Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers See Stock Flow Map   Insight 810  

Simplified version of IM-852  Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers See Stock Flow Map  Insight 810 

 An adaptation of the URBAN1 Model from Navid Ghaffarzadegan, John Lyneis and George P Richardson's How small system dynamics models can help the public policy process. System Dynamics Review 27: 22-44 (2011) Conference version at  http://bit.ly/HlxtZj   and LA Alfeld and AK Graham's Introduction to

An adaptation of the URBAN1 Model from Navid Ghaffarzadegan, John Lyneis and George P Richardson's How small system dynamics models can help the public policy process. System Dynamics Review 27: 22-44 (2011) Conference version at http://bit.ly/HlxtZj  and LA Alfeld and AK Graham's Introduction to Urban Dynamics 1974 p 195.

An element of Perspectives: The Foundation of Understanding and Insights for Effective Action. Register at http://www.systemswiki.org/

 
 Adapted from Fig 8.1 p.310 of the Book: James A. Forte ( 2007),  Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice   Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Adapted from Fig 8.1 p.310 of the Book: James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice  Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

From Cultural Worldview and Preference for Childhood Vaccination Policy  PSJ Article   Nov 2014
From Cultural Worldview and Preference for Childhood Vaccination Policy PSJ Article  Nov 2014
 Modified from Sterman (2006) and Gene Bellinger's Assumptions  IM-351  by Dr Rosemarie Sadsad UNSW See also  Complex Decision Technologies IM  and  IM-63975

Modified from Sterman (2006) and Gene Bellinger's Assumptions IM-351 by Dr Rosemarie Sadsad UNSW See also Complex Decision Technologies IM and IM-63975

WIP AnyLogic Hybrid Model methods and examples taken from Nate Osgood's Bootcamps around 2017
WIP AnyLogic Hybrid Model methods and examples taken from Nate Osgood's Bootcamps around 2017
WIP integrating Epidemiology Systems Science and Policy making, mainly based on books and AJE articles by Keyes and Galea
WIP integrating Epidemiology Systems Science and Policy making, mainly based on books and AJE articles by Keyes and Galea
From David Rees PhD dissertation "Developing a Theory of Implementation for
Better Chronic Health Management" Health Services Research
Centre, Victoria University of Wellington, New Zealand
From David Rees PhD dissertation "Developing a Theory of Implementation for Better Chronic Health Management" Health Services Research Centre, Victoria University of Wellington, New Zealand
Description of client process through reporting an IOD incident at TBH
Description of client process through reporting an IOD incident at TBH
From David Rees PhD dissertation "Developing a Theory of Implementation for
Better Chronic Health Management" Health Services Research
Centre, Victoria University of Wellington, New Zealand
From David Rees PhD dissertation "Developing a Theory of Implementation for Better Chronic Health Management" Health Services Research Centre, Victoria University of Wellington, New Zealand
 Rich picture, Based on Lyneis JM and Ford DN System Dynamics Applied to Project Management Syst. Dyn. Rev. 23, 157-189 (2007)

Rich picture, Based on Lyneis JM and Ford DN System Dynamics Applied to Project Management Syst. Dyn. Rev. 23, 157-189 (2007)

 WIP for Continuity of care ISO From  Wikipedia  Initial Insight Representation from ContSys  IM-4008  with split off  patient  and professional statecharts See  IM-2846  for Agent with infectious disease and  IM-6913  for ED Physician INteraction

WIP for Continuity of care ISO From Wikipedia Initial Insight Representation from ContSys

IM-4008 with split off patient and professional statecharts See IM-2846 for Agent with infectious disease and IM-6913 for ED Physician INteraction
 
 Adapted from Fig 12.1 p.476 of the Book James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice; Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Adapted from Fig 12.1 p.476 of the Book James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice; Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet    Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.     Isolation is when someone exposed to infected people,
A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet

Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.

Isolation is when someone exposed to infected people, get infected, detected, and send to hospital.

Assumption:
- No births
- Dead only caused by SARS
- Contact between susceptible and infected are constant. Contact does not affected by population density
- Quarantine factor for susceptible and exposed is same.
- Quarantine and isolation is fully efective. Someone who quarantined or isolated cannot transmit or exposed to SARS
- Someone who has already recovered from SARS gained fully effective immunity, thus cannot re-infected
WIP summaries of  bill mitchell's blog  postings related to the connections between macroeconomics and wellbeing, particularly via unemployment and inflation
WIP summaries of bill mitchell's blog postings related to the connections between macroeconomics and wellbeing, particularly via unemployment and inflation
See reference in diagram notes. WIP for Environment part of primary care regional model. GP centric calibration by JPS at  IM-14117  See also  IM-3126  for Regional Health Service Use Context
See reference in diagram notes. WIP for Environment part of primary care regional model. GP centric calibration by JPS at IM-14117 See also IM-3126 for Regional Health Service Use Context
 WIP based on Geoffrey Brennan's Selection and the Currency of Reward chapter expanded from  IM-396  

WIP based on Geoffrey Brennan's Selection and the Currency of Reward chapter expanded from IM-396 

 Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker     Glucose Insulin Model Info:  Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Spr

Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker


Glucose Insulin Model Info:

Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Springer 1998, Ch 24 p255-261, by Mark Heffernan.