DYNAMIC SIMULATION MODELLING IN HEALTH CARE - WHY WE NEED IT? HOW IT CAN HELP?

Friday, January 8, 2016
Foyer, G/F (Jockey Club School of Public Health and Primary Care Building at Prince of Wales Hospital)

Praveen Thokala, PhD, University of Sheffield, Sheffield, United Kingdom and Beate Jahn, PhD, UMIT - University for Health Sciences, Medical Informatics and Technology, Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, Hall in Tyrol, Austria
Purpose: The aim is to highlight the need for dynamic simulation modelling in health care and provide examples of how it can be used to support health care delivery. 

Method(s): Review of previous literature within health technology assessment (HTA) suggests that the issue of implementation and feasibility has been largely ignored. Economic analyses typically ignore the short-term constraints (e.g. beds, availability of computed tomography scanners, nurses) that might lead to low levels of uptake. 

Result(s): Traditional modelling techniques (e.g Markov models, decision trees, etc) are not equipped to estimate the impact of service reconfigurations or changes in the clinical pathways. There are modelling techniques that can capture these resource implications and dynamics (discrete event simulation [DES], system dynamics [SD], agent based modelling [ABM].  A brief description of these dynamic simulation modelling techniques will be provided along with some case studies of situations where dynamic simulation (ABM, SD, DES) was necessary to fully incorporate resource constraints. First, a case study of cost-effectiveness of drug-eluting stents using a DES model where resources capacities and dynamic waiting lines were explicitly modelled. Model outcomes and consequent decisions using a dynamic vs. non-dynamic approach are compared. Second, a case study of SD model for reconfiguration of health care services will be provided. Finally, guidance on choosing appropriate dynamic simulation modelling technique(s) for specific applications will be provided.

Conclusion(s): There is a need for a quantitative assessment of the resource requirements and capacity constraints, especially if there are significant changes in the amount or type of resources needed within the pathway by implementing the new technology.  There are modelling techniques that can capture these resource implications and dynamics. Further use of these dynamic simulation modelling techniques will result in efficient use of scarce health care resources.