WIP ​Based on TAble 1 Jackson 2014 article

From Navid G's HSR 2013 paper Fig 1

Storyboarding design WIP showing some relevant  context, mechanisms and outcomes involved in modelling multiscale decision support for improving the health experiences of elderly people with multimorbidity.

A model of thermostat action including conversions between heat and temperature and outside temperature. See also, after this model, how the concept map of a thermostat at IM-735 changed to the concept map at IM-736

Rich picture version of causal loop diagram for medication errors, showing the importance of reporting, analyzing and fixing knowledge and process errors. Medication errors will tend to grow due to the use of more medications in more complex patients. This is exacerbated by the loss of staff knowledge by turnover and goal erosion in places with harmful errors.

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

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.

A work in progress conceptual model based on Using system dynamics principles for conceptual modelling of publicly funded hospitals by HJ Wong et al Journal of the Operational Research Society advance online publication, 27 April 2011 doi:10.1057/jors.2010.164. Linked concepts with annotated definitions.

IM-1175 with computable arguments, based on ideas from Micropublications paper about Claims, Evidence, Representations and Context Networks

Replaced by IM-752 Causal Loop Rich Picture unfolding from Repenning, N. and J. Sterman (2002). Capability Traps and Self-Confirming Attribution Errors in the Dynamics of Process Improvement. Administrative Science Quarterly, 47: 265 - 295. http://jsterman.scripts.mit.edu/docs/Repenning-2002-CapabilityTraps.pdf

IPCC Extreme weather events combined context diagrams  FBE WIP

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

Clone of Clone 4of IM 27348, of JPS IM-27150 of original JPS IM-14117 See reference in diagram notes. WIP for Environment part of primary care regional model

Adding change over time to relative risk, odds ratio and population attributable fraction epidemiology concepts see wikipedia and examples .

Business case for investment in national eHealth Infrastructure Programs

Summary of evolution and the modern synthesis with genetics. See also the more recent extended synthesis IM-2099

A simple generic rich picture view of interactions among concerned people with needs services and resources and abilities (including learning), which can be used as a pattern for many individual health care insights.

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

Nested multilevel inquiry across multiple levels of organization of biology concepts. Adapted from Knippels (2002) PhD Thesis at http://bit.ly/GGcKo1 . Note the similarity to the nested adaptive cycles of socio-ecological systems in IM 1169

Interacting nested fast and slow adaptive cycles from Panarchy Book  ,Resilience thinking Book Brian Walker and David Salt Island Press 2006 and the http://www.resalliance.org/ Website, See also What is Panarchy at http://bit.ly/H9RFkL

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.

Protein conformance change based on Ed Gallaher and Jim Rogers 2021 Forrester Award Lecture ISDC

Shiffman's global health political priority framework as described in 2007 Lancet article with maternal mortality example

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