Cited 3 times in
Physician-Customized Strategies for Reducing Outpatient Waiting Time in South Korea Using Queueing Theory and Probabilistic Metamodels
DC Field | Value | Language |
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dc.contributor.author | 최은경 | - |
dc.date.accessioned | 2022-03-11T06:17:51Z | - |
dc.date.available | 2022-03-11T06:17:51Z | - |
dc.date.issued | 2022-02 | - |
dc.identifier.issn | 1661-7827 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/188023 | - |
dc.description.abstract | 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. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | MDPI | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Physician-Customized Strategies for Reducing Outpatient Waiting Time in South Korea Using Queueing Theory and Probabilistic Metamodels | - |
dc.type | Article | - |
dc.contributor.college | College of Nursing (간호대학) | - |
dc.contributor.department | Dept. of Nursing (간호학과) | - |
dc.contributor.googleauthor | Hanbit Lee | - |
dc.contributor.googleauthor | Eun Kyoung Choi | - |
dc.contributor.googleauthor | Kyung A Min | - |
dc.contributor.googleauthor | Eunjeong Bae | - |
dc.contributor.googleauthor | Hooyun Lee | - |
dc.contributor.googleauthor | Jongsoo Lee | - |
dc.identifier.doi | 10.3390/ijerph19042073 | - |
dc.contributor.localId | A04148 | - |
dc.relation.journalcode | J01111 | - |
dc.identifier.eissn | 1660-4601 | - |
dc.identifier.pmid | 35206259 | - |
dc.subject.keyword | operations research in health services | - |
dc.subject.keyword | outpatient waiting time | - |
dc.subject.keyword | probabilistic meta-modeling | - |
dc.subject.keyword | queueing | - |
dc.subject.keyword | statistical analysis | - |
dc.contributor.alternativeName | Choi, Eun Kyoung | - |
dc.contributor.affiliatedAuthor | 최은경 | - |
dc.citation.volume | 19 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 2073 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol.19(4) : 2073, 2022-02 | - |
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