Physician-Customized Strategies for Reducing Outpatient Waiting Time in South Korea Using Queueing Theory and Probabilistic Metamodels

• Published in: International journal of environmental research and public health 2022-02, Vol.19 (4), p.2073
• Main Authors: Lee, Hanbit, Choi, Eun Kyoung, Min, Kyung A, Bae, Eunjeong, Lee, Hooyun, Lee, Jongsoo
• Format: Article
• Language: English
• Subjects: Customization; Genetic algorithms; Hospitals; Metamodels; Nursing; Patient satisfaction; Patients; Physicians; Probability distribution; Professionals; Queuing theory; Scheduling; Sorting algorithms; Statistical analysis
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph19042073

The time a patient spends waiting to be seen by a healthcare professional is an important determinant of patient satisfaction in outpatient care. Hence, it is crucial to identify parameters that affect the waiting time and optimize it accordingly. First, statistical analysis was used to validate the effective parameters. However, no parameters were found to have significant effects with respect to the entire outpatient department or to each department. Therefore, we studied the improvement of patient waiting times by analyzing and optimizing effective parameters for each physician. Queueing theory was used to calculate the probability that patients would wait for more than 30 min for a consultation session. Using this result, we built metamodels for each physician, formulated an effective method to optimize the problem, and found a solution to minimize waiting time using a non-dominated sorting genetic algorithm (NSGA-II). On average, we obtained a 30% decrease in the probability that patients would wait for a long period. This study shows the importance of customized improvement strategies for each physician.