Framework Development for Dynamic System Validation

Abstract

Validation is one of the most important stages of modeling, and it is a necessity before utilizing the model for further analyses. Especially for the studies that start with conceptual models, the validation process is more complex than others. In this study, we used a multi-methodology approach to develop a framework to support the conceptual model development and validation in System Dynamics (SD) modeling. In the proposed framework, we integrated methods from SD methodology with methods from the Analytic Network Process (ANP). The proposed framework was then used for clinical laboratory performance analysis. The purpose was to use the proposed framework to conduct structural validity of the SD model, to prioritize Clinical Laboratory (CL) performance indicators, and capture their relations. Results indicate that the proposed framework can be used to generate an enriched and validated conceptual model for a CL performance system that can be useful for healthcare decision-makers. Also, the proposed multi-methodology framework can be applied to any complex systems to validate the conceptual models.