Abstract for:Heuristic Decision Making in System Dynamics Modeling- Case Study: Antibiotic Prescribing
The interactions between health providers and patients, and perceptions of each group towards prescribing, play a crucial role on prescribing decisions. For example, patient’s expectation to receive antibiotic, and also health providers’ perception of patient’s expectation could influence on prescription rates. The objective of this study is to compare different heuristic formulations for utility perception variables within a system dynamics (SD) model, based on results from simulated policy scenarios. A common formulation used for modeling perception variables is the smooth function. We investigate other formulations such as peak-end formula. We use the case of antibiotic prescribing rates for acute respiratory tract Infections (ARTIs) from the National Ambulatory Medical Care Survey (NAMCS) database between 1993 and 2015. Our simulation model shows that applying the peak-end formation has different results in comparison with the smooth formulation when we do the policy analysis. This confirms that further investigation is needed to validate the use of appropriate heuristic formulas in modeling perception variables.