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Design and analysis of a health care clinic for homeless people using simulations
Jared Reynolds1, Zhen Zeng, Jingshan Li
1Manufacturing Center for Excellence, GE Aviation, Cincinnati, Ohio, USA.
Purpose:
Improving quality of care is important in health care management. For health care clinics, reducing patient waiting time and improving throughput with efficient utilization of the workforce are important issues to achieve better quality of care. This paper seeks to introduce a simulation study on design and analysis of a health clinic for homeless patients in Lexington, Kentucky, USA.
Design/Methodology/Approach:
Using the simulation model, the patient flow of the clinic and analyze quality of care for different staffing levels is simulated. In addition, the dependence of distributions on service times is investigated. Moreover, the impact of service time variability on quality of care (e.g. patient waiting time) is analyzed.
Findings:
The necessary staffing level and utilizations to reduce patient waiting times and improve throughput to achieve better quality of care are obtained. In addition, it is shown that the system performance is primarily dependent on the mean and coefficients of variation, rather than a complete distribution, of service times. In addition, a piece-wise linear approximation formula is proposed so that patient waiting time in the clinic can be estimated for any variability with only two simulations.
Research Limitations/Implications:
The simulation method may need long model development time and long simulation executing time for complex systems.
Practical Implications:
The quality of care delivery in a health care clinic can be evaluated using simulations. The results presented in the paper provide an easier approach for medical practitioners to evaluate different scenarios, examine needed resources, and carry out what-if analysis to predictthe impact of any changes in the system, to determine an optimal system configuration.
Originality/Value:
The paper shows that such models provide a quantitative tool for clinic operations and management to achieve better care quality. Moreover, it can be easily adapted to model other health care facilities, such as hospitals, emergency rooms, operating rooms, supply chain in health care industry.
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