A generalized system dynamics model for managing transition-phases in healthcare environments

Learning curve theory, and in particular adaptation function have proven useful to identify organizational learning patterns. Yet they are limited in the information they provide in that they provide a general understanding on how long it will take to reach a desired outcome level. The adaptation function is to be employed to plan a transition-phase, and is capable of helping managers to balance quality, time and resource cost, along with determining periods of instability and of dynamic equilibrium. The adaptation function theory is strengthened by combining it with systems thinking principles and a simulation model based on system dynamics be developed as a result. The purpose of this dissertation is to develop a transition phase management model based on a complementarist approach.

The development process encompasses 1) the analysis of systems thinking, system dynamics and adaptation function characteristics and how they can be combined, 2) the development of the simulation model, 3) extreme values tests (sensitivity analysis) and 4) validation of the model in real world projects.

Healthcare managers can benefit from the model in two ways: 1) the model is developed into a simulation model that possesses a user friendly interface; 2) Managers are able to forecast implementation quality, time and resource costs, identify variables that can be modified to obtain a better outcome by reducing periods of instability or accelerating the learning process.