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

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

Patients on Treatment represented as people in a swimming pool. Fast Switchers change costumes. Lapsed Users sit by the pool. Misdiagnosed people are in the wrong pool. Extended from IM-305

Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. Current premier version for vincy to update

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

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

This model shows the dynamics of use of a new medical technology based on its scope of use and perceived relative benefit. The technology needs cumulative usage to fix its glitches, and the benefits will be diluted  as the scope of use widens.

DIabetes incidence inflow, Prevalence stock and deaths outflow

Aim: To gain insight into what map and model representations in applied systems methods in IM-1267 can assist identifying and explaining the improvement strategies (leverage points) described by Donella Meadows Places to Intervene Article. The context is social learning for collective action to improve real world events. Information Sources are adapted from IM-920

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

Kermack–McKendrick Epidemic SIR Infectious Disease Model - Metrics by Guy Lakeman

This is a simple SIR infectious diseases 3 stock model with Susceptibles, Infectives and Recovereds stocks. In the initial description the R signified Removed and could include Deaths, Recovered with immunity to infection (Resistant) or those who had fled the epidemic. Note the need to initiate the epidemic by adding a pulse of a single infected person at time 0.

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).

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

Summary of several AIHW reports on Aged Care Pathways from 2011-2017

Model for Rehab 2139 Board Game by Mark Heffernan and Lynette Lee

From Adapting ‘Agility’ to Healthcare Service Delivery, by Tom Rust, Khalid Saeed, Isa Bar-On, Oleg Pavlov Paper from July 2013 System dynamics Conference Cambridge MA and also 2012 Conference paper  Could be extended by adding dynamics described in going solid insight

Jack Homer's model via ithink and Mark Heffernan.  From Jack's  paper Worker burnout: a dynamic model with implications  for prevention and control System Dynamics Review 1985 1(1)42-62. See IM-641 for the Causal loop diagram

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

Rich picture version of Causal loop diagram based on Jack  Homer's paper Worker burnout: a dynamic model with implications  for prevention and control System Dynamics Review 1985 1(1)42-62 See IM-333 for the Simulation model

 

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

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

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

Dynamic system underlying project life cycles From Roberts Edward B The Dynamics of Research and Development p5 Harper & Row NY 1964

Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017.