Study on Optimal Appointment Pattern using Plastic Surgery Appointment Data

성형외과 예약 고객 데이터를 반영한 최적 예약 패턴 연구

  • Received : 2018.07.17
  • Accepted : 2018.09.14
  • Published : 2018.09.30

Abstract

Purpose: This study investigates the best appointment pattern which can enhance customer's satisfaction and hospital's efficient management reflecting plastic surgery clinic's service characteristics. Methodology: The data of this study is obtained from Plastic surgery Clinic which is located in the civic center. By collecting and analyzing the data, we build the simulation model using ARENA. Based on 5 appointment patterns that was suggested in formal appointment scheduling studies, we experiment 3 simulation models; 'Basic Appointment Pattern' that has no restriction, 'Restriction on Second Customer' that restricts the number of second customer's in each slot, 'Restriction on Process Time' that restricts the number of second customer who has long process time in each slot. We can check robustness of the appointment patterns by experimenting on off-peak day and peak day, during peak season. Findings: This study confirms that these 2 restrictions can give a better result than 'Basic Appointment Pattern' that just simply distributes customers by number. Especially, the performance of Triangle-like pattern which is the best appointment pattern in the formal study has been improved by adding restrictions. Based on 'DET', 'Restriction on Second Customer' shows a better result. Meanwhile, based on 'E(WT)', 'Restriction on Process Time' shows a better result. Overall, based on 'DET+E(WT)', 'Restriction on Second Customer' shows a better result. Practical Implications: The purpose of each hospital may alter as demand for plastic surgery grows increasingly. Thus, each hospital should be always prepared to introduce appointment pattern for changed purpose. In order to respond flexibly to these changes, it is necessary for medical personnel to improve the awareness or for hospital to create an environment by constructing appointment program so that medical personnel does not need to put more labor on work.

Keywords

Acknowledgement

Supported by : 한국연구재단

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