Simulation model of the WIP Conceptual map IM-7671 of initial scope of the effects of the ED 4 hour rule based on June WA Teleconference and IM-8221. See also the conceptual maps of addition of indirect effects at IM-7775 and the potential wider context map in IM-6167

Extension of IM-14124 with an adjusted bed capacity stock. For backlog and services see IM-8382

WIP Summary of Lisa Rosenbaum's Feb 2019 NEJM 3 articles and audiocast . 

From Rudolph JW Morrison JB and Carroll JS (2009) The Dynamics of Action-Oriented Problem Solving: Linking Interpretation and Choice. Academy of Management Review 34 (4) p733-756 Available online . This paper won the Forrester Award for 2012 and the presentation talk video is available. The presentation  paper abstract is available in System Dynamics Review 2013 here

A Rich Picture Story representation of ED overcrowding based on Using system dynamics principles for conceptual modelling of publicly funded hospitals] by HJ Wong et al Journal of the Operational Research Society 63, 79-88 (January 2012) | doi:10.1057/jors.2010.164 Click the +view story on the bottom left

System Zoo Z111 H Bossel p47 a variant of Michaelis Menten Enzyme Kinetics. See also IM-854 for Hannon and Ruth and IM-855 for receptor version and IM-856 for a bond graph view

Business case for investment in national eHealth Infrastructure Programs

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 

WIP Stock Flow representation of Panarchy Adaptive Cycles

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

Clone of IM-6072 which is a WIP based on Choice modelling and Mark Paich's Book and NZ work focus on Pre-ED Presentation choices, with ED and Post-ED care.  Addition of After hours 'as is' and 'to be' flow models for Medicare Locals

A Susceptible-Infected-Recovered (SIR) disease model with waning immunity

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

We add simple containment meassures that affect two paramenters, the Susceptible population and the rate to become infected.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

The questions that we want to answer in this kind of models are not the shape of the curves, that are almost known from the beginning, but, when this happens, and the amplitude of the shapes. This is crucial, since in the current circumstance implies the collapse of certain resources, not only healthcare.

The validation process hence becomes critical, and allows to estimate the different parameters of the model from the data we obtain. This simulation approach allows to obtain somethings that is crucial to make decisions, the causality. We can infer this from the assumptions that are implicit on the model, and from it we can make decisions to improve the system behavior.

Yes, simulation works with causality and Flows diagrams is one of the techniques we have to draw it graphically, but is not the only one. On https://sdlps.com/projects/documentation/1009 you can review soon the same model but represented in Specification and Description Language.

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 integrating Epidemiology Systems Science and Policy making, mainly based on books and AJE articles by Keyes and Galea

This is a high level system dynamics model which is built to determine the dynamic relationships of the FSA and Followups capacity. Therefore, it can help clinicians to find out the optimistic method in order to reduce the waiting list. At past clinicians were seeing more FSA patients, however, after few months, the followups patients overwhelmed the clinics. Therefore waiting list has been built up again. By running this model, clinicians can find out the balanced leverage point(s).

WIP Based on Sheldrick Implementation science 2016 article A system dynamics model of clinical decision thresholds for the detection of developmental-behavioral disorders. Vensim model modified to show patterns

 

Adapted from Fig 10.1 p.393 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

WIP for Nutrition and the first 1000 days

Causal loop diagram based on Jack  Homer's  Worker burnout: a dynamic model with implications  for prevention and control See IM-333 for simulation model and IM-641 for Rich Picture CLD

System Dynamics Review 1985 1(1)42-62

 

Summary of US apa2017 report pdf link

Jones AP, Homer JB, Murphy DL, Essien JDK, Milstein B, Seville DA.

Understanding diabetes population dynamics through simulation modeling

and experimentation. American Journal of Public Health 2006;96(3):488-494.

http://ajph.aphapublications.org/cgi/content/abstract/96/3/488