Business case for investment in national eHealth Infrastructure Programs

From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.

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

WIP Clone of IM-435 for Research (IM-345 was https://insightmaker.com/insight/435/Technology-and-Healthcare-Costs-and-Outcomes-2A simplified dynamic model, adapted from Engineering perspectives on healthcare delivery: Can we afford technological innovation in healthcare? Rouse, William B Systems Research and Behavioral Science 2009 Vol 26 (5) p573-582 abstract  Developed by Mark Heffernan See also IM-614 for learning effects.

From Powers et al 2011 paper and Mansell's video

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

This models the progressive decline of the ability for self-reliance and the growing dependence on outside help. ​Z508 p39-42 System Zoo 3 by Hartmut Bossel. Strong outside help causes a collapse of self-help capacity. Weak outside help produces a stable combination of wellbeing and self-help capacity.

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

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.

Simplest ED Model for Weekend  ED Performance with 1 ED area IM-11079  Ward net discharges are extended with Ward and Waitlist inflow and outflow details (informed by IM-7981) WIP

WIP for Whole of Hospital Program. Provides Context and Detail for Hospital Timeline Study IM-9382

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

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

 

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

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.

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

From Navid G's HSR 2013 paper Fig 1

Dynamics of Emergency Room Crowding a simple uncalibrated simulation which includes Wards and some simple internal ED feedback effects

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.

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