Health Care | Insight Maker

A simple glucose regulation causal loop diagram taken from Richard O. Foster, 1970: The Dynamics of blood sugar regulation, MSc thesis, MIT Dept of Electrical Engineering, available on the MIT System Dynamics Group Literature Collection and in the MIT Electronic Libraries. See IM-587 for Addition of Glucagon

Glucose regulation CLD 1

Geoff McDonnell

3

From Powers et al 2011 paper and Mansell's video

Clone of Perceptual Control Theory

Diana Simpson

Test Sensitivity and Specificity see ROC wikipedia and Tom Fawcett's 2006 article introduction to ROC Analysis, Can be linked to Brunswik Lens IM-1401

Test ROC Curves

Geoff McDonnell

A simple glucose regulation causal loop diagram taken from Richard O. Foster, 1970: The Dynamics of blood sugar regulation, MSc thesis, MIT Dept of Electrical Engineering, available on the MIT System Dynamics Group Literature Collection and in the MIT Electronic Libraries. See IM-587 for Addition of Glucagon

Clone of Glucose regulation CLD 1

Yun Wang

From MIT ESD work (de Weck Ilities ) esp on Survivability (Medecki) http://bit.ly/HVsceb and Unarticulated Value (Ross) 2006 PhD pdf

Clone of System change value and ilities

arwa

Proceso de contagios en COVID19

Marco Arriaza

Hypertension Generic Patient Flow Causal Loop Diagram version of Insight 305

Clone of Generic Patient Flow CLD

David Joseph McLaren

Detailed CLD - current version

Jakob Vagle

5

Adapted from Fig 5.1 p.186 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

Applied Systems Theory Map

Geoff McDonnell

3

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

Clone of Implementing Chronic Care Management

Arno Terra

version of Suicide 4 insight focussed on PTSD in Veterans

Suicide Dynamics 5

Geoff McDonnell

Simple exposition of going solid article by Cook and Rasmussen 2005 after reading p156 section 4.1 of Modelling in Healthcare by CSMG See also Resilience Cs IM

Cost Quality Workload Dynamics

Geoff McDonnell

Suicide Prevention WIP

Clone of Clone of Suicide Dynamics

Sang Min Park

SIR model with waning immunity - Metrics by Guy Lakeman

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

SIR model with waning immunity - Metrics by Guy Lakeman

Guy Lakeman

3

Inspiration for the model: The Last of Us, a video game for PlayStation 4.

In this example, we used a system dynamics model to predict a spread of a dangerous infection called Cordyceps Brain Infection, which is immune to any type of antibiotics. In the beginning, the virus was carried by only one person (Infected), which inhaled spores from a plant called cordyceps fungus.

The Infected show their first symptoms after two days, as the infection attacks higher brain functions, making the infected highly aggressive and incapable of reason or rational thoughts.

The infection can be transmitted via bodily fluids; such as saliva, or by inhaling spores from the afore mentioned plant.

It is believed that the infection can last up to 10 years, before the host dies.

Parameters such as Infectivity, Contact Rate and Immunization Rate can be adjusted, but as we are dealing with a highly infectious disease, the starting values are 0.97 (infectivity - in 97% of the cases, the infection will spread to another host); 5 (each infected attacks 5 susceptible person per day); and 0.0001 (only 1 infected per 10,000 infected gets the treatment, as the vaccine can be afforded only by the richest people on the Earth).

Simulation time is set to 50 years. The purpose of this model is to simulate what kind of an effect a deadly infection would have on World's population, if the medicine could not find a cure, or if the cure would be available only for the richest people on the Earth.

The simulation result shows that the Earth's population has been decimated with the disease, and that there are only 7,5 million people left on Earth.

Infectious Disease Model

Emir Guso

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

ED Crowding Hospitals and Beyond Rich Pic

Geoff McDonnell

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

Clone of Clone of Implementing Chronic Care Management

li xu

This simple high level model shows the basic feedback balancing loop for health services. There are many other loops and component interactions at multiple scales that add to the complexity See areas of expenditure IM for some component splits and hospital value IM for some service linkages

Health Care Supply Demand Dynamics

Geoff McDonnell

Rich picture version of nutrient flow model insight 760. From p194 of The Reflective Practitioner Donald A Schon Basic Books 1983

Nutrient Flow Model with images

Geoff McDonnell

balancing an integrated eye care training program with service needs and available resources

multi entry exit eye care training

keith masnick

WIP for IT enabled regional health services. See also IM-14104 The Ecology of Medical Care

Regional Health Services

Geoff McDonnell

Simple Bass diffusion modified from Sterman Business Dynamics Ch9. Compare with the SI infectious disease model Insight 584.

Clone of model: https://insightmaker.com/insight/610/Diffusion-of-Innovation-Bass-Model

Clone of Diffusion of Innovation Bass Model

Pradeesh Kumar

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.

Clone of COVID SEIRD - With confined JORDI PABLO

Jordi Granja I Bayot

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.

Clone of Clone of Glucose-Insulin Model in Type 1 Diabetes

Phillip Archuleta

Health Care Models