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

Dynamics of Emergency Department Crowding Initial View from the waiting room. Follows from IM-369 Sim and IM-340 CLD. Proceed to IM-349 

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). New Model has been developed, this is a very draft model.

Dynamics of Emergency Room Crowding with treatment spaces. Here we investigate the effect of constrained spaces and ignore any changes in treatment time or staffing effects. Many of the consequences occur before treatment with potential arrivals being turned away and arrivals leaving without being treated.  

Dynamics of Emergency Department Crowding Initial Simplest Simulation of the View from the waiting room. Start of a simple introductory series which proceeds to IM-338  A simple CLD is at IM-340

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

Dynamics of Emergency Department Crowding Initial Simplest Simulation of the View from the waiting room. Start of a simple introductory series which proceeds to IM-338  A simple CLD is at IM-340

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).

Extension of IM-7981 with dynamics of daily ward discharges and did not waits. For an adjusted bed capacity stock see IM-14144.For backlog and services see IM-8382

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). New Model has been developed, this is a very draft model.

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). New Model has been developed, this is a very draft model.

WIP Conceptual map of initial scope of the effects of the ED 4 hour rule based on June WA Teleconference. See also the addition of unintended consequences at IM-7775 and the potential wider context map in IM-6167. For a simulation see IM-8237