Evidence map›Paper›PMID 35206259›Full record

ArticleInternational journal of environmental research and public health2022

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

Hanbit Lee, Eun Kyoung Choi, Kyung A Min, Eunjeong Bae, Hooyun Lee, Jongsoo Lee

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hanbit LeeSchool of Mechanical Engineering, Yonsei University, Seoul 03722, Korea.ORCID 0000-0003-1941-1953
Eun Kyoung ChoiCollege of Nursing and Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul 03722, Korea.ORCID 0000-0003-4622-2437
Kyung A MinSeverance Hospital, Yonsei University Healthcare System, Seoul 03722, Korea.
Eunjeong BaeCollege of Nursing and Brain Korea 21 FOUR Project, Yonsei University, Seoul 03722, Korea.ORCID 0000-0003-1583-8933
Hooyun LeeGraduate School of Nursing, Yonsei University, Seoul 03722, Korea.ORCID 0000-0001-7346-7902
Jongsoo LeeSchool of Mechanical Engineering, Yonsei University, Seoul 03722, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

PhysiciansWaiting ListsAmbulatory CareHumansOutpatientsReferral and Consultationoperations research in health servicesoutpatient waiting timeprobabilistic meta-modelingqueueingstatistical analysis

Identifiers

PMID35206259
PMCPMC8871932

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.