Expert knowledge elicitation using computer simulation: the organization of frail elderly case management as an illustration

Authored by Jean-Christophe Chiem, Therese Van Durme, Florence Vandendorpe, Olivier Schmitz, Niko Speybroeck, Sophie Ces, Jean Macq

Date Published: 2014-08

DOI: 10.1111/jep.12101

Sponsors: United States National Institutes of Health (NIH)

Platforms: NetLogo

Model Documentation: Other Narrative Flow charts

Model Code URLs: http://sourceforge.net/projects/cmpartsim/

Abstract

Background Various elderly case management projects have been implemented in Belgium. This type of long-term health care intervention involves contextual factors and human interactions. These underlying complex mechanisms can be usefully informed with field experts' knowledge, which are hard to make explicit. However, computer simulation has been suggested as one possible method of overcoming the difficulty of articulating such elicited qualitative views. Methods A simulation model of case management was designed using an agent-based methodology, based on the initial qualitative research material. Variables and rules of interaction were formulated into a simple conceptual framework. This model has been implemented and was used as a support for a structured discussion with experts in case management. Results The rigorous formulation provided by the agent-based methodology clarified the descriptions of the interventions and the problems encountered regarding: 1 the diverse network topologies of health care actors in the project; 2 the adaptation time required by the intervention; 3 the communication between the health care actors; 4 the institutional context; 5 the organization of the care; and 6 the role of the case manager and his or hers personal ability to interpret the informal demands of the frail older person. Conclusion The simulation model should be seen primarily as a tool for thinking and learning. A number of insights were gained as part of a valuable cognitive process. Computer simulation supporting field experts' elicitation can lead to better-informed decisions in the organization of complex health care interventions.

Tags

Agent-based modelling Complexity Computer simulation knowledge case management health care organization