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Developing a prototype system of computer-aided appointment scheduling: A radiology department case study.

Ping-Shun Chen¹, Chin-Hui Lai², Ying-Tzu Chen¹

¹Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan, Taiwan.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine

|August 7, 2023

Summary

This summary is machine-generated.

This study introduces a computer-aided system to optimize radiology appointment scheduling. The system effectively classifies patient examination times, improving efficiency and medical treatment quality.

Keywords:

Data mining appointment scheduling system decision tree patient appointments stepwise multiple regression analysis

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Area of Science:

Medical Informatics
Operations Research
Radiology

Background:

Hospital appointment scheduling is complex due to diverse patient needs, examinations, and resources.
The radiology scheduling problem presents unique challenges with multiple technologists, rooms, and examination types.

Purpose of the Study:

To develop a computer-aided appointment scheduling system for radiology.
To address the complexities of scheduling radiological examinations based on patient and resource factors.

Main Methods:

Utilized stepwise multiple regression analysis (SMRA) to predict examination image quantities.
Employed K-Means clustering and decision tree classification to categorize patient examination times.
Integrated patient data including body part, department, gender, and age for scheduling.

Main Results:

Developed a prototype system capable of creating feasible patient appointment schedules.
Classified patient examination times into distinct categories based on body parts, departments, and technologists.
Demonstrated a method for generating efficient schedules considering multiple variables.

Conclusions:

The proposed system effectively schedules appointments for diverse radiological services.
Addresses challenges of diversity and uncertainty in radiology scheduling.
Aims to enhance the overall quality of medical treatment through optimized scheduling.