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

Mind map example of a medication management project.

See also IM-692 for CLD

Summary of US apa2017 report pdf link

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

Simple Bass diffusion modified from Sterman Business Dynamics Ch9, with additional discarding

https://youtu.be/LRlkwN_cFnQ

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).

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

Rich Picture Version of Insight 386 The Dynamics of Human Service Delivery General Theory from the Book by Levin, Roberts, Hirsch et al. Ballinger 1976 ISBN 0-88410-132-0

Business case for investment in national eHealth Infrastructure Programs

WIP to explain risk factors and burden of disease

WIP AnyLogic Hybrid Model methods and examples taken from Nate Osgood's Bootcamps around 2017

Causal loop diagram of the dynamics of emergency and elective admissions competing for vacant ward beds in a hospital. From

Lane, David C. and Monefeldt, C. and Rosenhead, Jonathan (2000) Looking in the wrong place for healthcare improvements: a system dynamics study of an accident and emergency department.  Journal of the Operational Research Society, 51 (5). pp. 518-531. ISSN 0160-5682 

See IM-7981 for Simulation Model

Overview of Evaluation Approaches from Pawson and Tilley's Book comparing Realist, Constructivist, Experimental and Pragmatic Evaluation Approaches. Combined with Van de Ven's Alternative Philosophies of Science in his Engaged Scholarship book. See also Burrell and Morgan's Sociological paradigms webpage

Clone of IM-24317 for adding other funding insights Im-633 and 636 and contrasting economic drivers of mental health with other health care based on JHPPL David Mechanic 2016 issue articles, esp Glied article (paywalled) Backed up generic version at IM-59166

Causal Loop Diagram of the Dynamics of Emergency Department Overcrowding

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

Bond Graph Kinetic Modeling Metabolic Map by J LeFevre  http://www.systemdynamics.org/conferences/2004/SDS_2004/PAPERS/379LEFEV.pdf

See also IM-857 and IM-2235 for more detail

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

Fig 3.1 Sociotechnical system underlying health IT-related adverse events NAP IOM Report

A Launchpad for Applied Social Work Theory Metaphors and Connections.Adapted from Table 14.3 p563 and Table 14.4 p564 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 0-495-00659-94

Hypertension Generic Patient Flow Causal Loop Diagram version of Insight 305

From the Plausibility of life book esp p 220-227

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.

This is an insight about food-born pathogens and what factors are affected by it's outbreaks. This is a huge issue that is not very well-known. The pathogens in food has been increasing their resistance to antibiotics by mutations. Because we are generally using antibiotics more each day, the resistance in these pathogens is growing more rapidly then it did before.