Characterizing an Effective Hospital Admissions Scheduling and Control Management System: A Genetic Algorithm Approach
2012, Proceedings of the 2010 Winter Simulation Conference
Jonathan E. Helm, Marcial Lapp, Brendan D. Seee
Proper management of hospital inpatient admissions involves a large number of decisions that have
complex and uncertain consequences for hospital resource utilization and patient flow. Further,
inpatient admissions has a significant impact on the hospital’s profitability, access, and quality of
care. Making effective decisions to drive high quality, efficient hospital behavior is difficult, if not
impossible, without the aid of sophisticated decision support. Hancock and Walter (1983) developed
such a management system with documented implementation success, but for each hospital the
system parameters are “optimized” manually. We present a framework for valuing instances of this
management system via simulation and optimizing the system parameters using a genetic algorithm
based search. This approach reduces the manual overhead in designing a hospital management system
and enables the creation of Pareto efficiency curves to better inform management of the trade-offs
between critical hospital metrics when designing a new control system.
Helm, Jonathan E., Marcial Lapp, and Brendan D. See (2010), "Characterizing an Effective Hospital Admissions Scheduling and Control Management System: A Genetic Algorithm Approach," Proceedings of the 2010 Winter Simulation Conference, pp. 2387-2398, 2010.