Forecasting the shortage of neurosurgeons in Iran using a system dynamics model approach
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. Sima Rafiei, . Arman Daneshvaran, . Sina Abdollahzade
Abstract CONTEXT: Shortage of physicians particularly in specialty levels is considered as an important issue
in Iran health system. Thus, in an uncertain environment, long‑term planning is required for health
professionals as a basic priority on a national scale.
AIMS: This study aimed to estimate the number of required neurosurgeons using system dynamic
modeling.
SETTING AND DESIGN: System dynamic modeling was applied to predict the gap between stock
and number of required neurosurgeons in Iran up to 2020.
SUBJECTS AND METHODS: A supply and demand simulation model was constructed for
neurosurgeons using system dynamic approach. The demand model included epidemiological,
demographic, and utilization variables along with supply model‑incorporated current stock of
neurosurgeons and flow variables such as attrition, migration, and retirement rate.
STATISTICAL ANALYSIS USED: Data were obtained from various governmental databases and
were analyzed by Vensim PLE Version 3.0 to address the flow of health professionals, clinical
infrastructure, population demographics, and disease prevalence during the time.
RESULTS: It was forecasted that shortage in number of neurosurgeons would disappear at 2020.
The most dominant determinants on predicted number of neurosurgeons were the prevalence of
neurosurgical diseases, the rate for service utilization, and medical capacity of the region.
CONCLUSIONS: Shortage of neurosurgeons in some areas of the country relates to maldistribution of
the specialists. Accordingly, there is a need to reconsider the allocation system for health professionals
within the country instead of increasing the overall number of acceptance quota in training positions.
