Volume 2, Issue 1

Volume 2, Issue 1

Research Article
Open Access
Optimizing patient flow with an iBeacon-based in-hospital navigation system: A framework and case study
Zhigang Sun
Zhigang Sun
Department of Information Management, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Pudong New Area, Shanghai 201318, China.
,
Feifei Gu
Feifei Gu
Department of Information Management, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Pudong New Area, Shanghai 201318, China.
,
Bei Tian
Bei Tian
Department of Information Management, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Pudong New Area, Shanghai 201318, China.
,
Ming Hu
Ming Hu
398429579@qq.com
Department of Information Management, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Pudong New Area, Shanghai 201318, China.
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Background: Hospital outpatient services handle a large number of patients daily, with busy and standardized processes, making them crucial to the hospital' s daily operations. Approximately one-third of outpatients seek assistance at the information desk daily, with 60% of these inquiries related to department location and the treatment process. Despite the hospital displaying prominent maps and signs, many patients still get lost, repeatedly search for departments, or endure long waits, hindering patient satisfaction. Objective: To design and implement an intelligent indoor navigation system deeply integrated with the hospital information system (HIS). This system helps patients quickly and conveniently plan their routes, improve the overall medical experience, reduce the workload of medical staff and hospital operating costs, and implement the hospital' s "one-phone-for-all" outpatient service process optimization concept. Methods: This study constructed a real-time navigation system integrating Bluetooth iBeacon positioning technology, a 3D electronic map, and a WeChat official account platform. The system architecture is deeply integrated with the HIS to achieve proactive navigation based on the treatment process. This study employed a retrospective cohort analysis to compare the differences in patient time spent on key medical routes before and after the system' s implementation, and analyzed its application effectiveness using actual system usage data. Results: The system provides real-time, intelligent, and dynamic route guidance and path planning, effectively reducing patient navigation time, optimizing the medical experience, and lowering the workload and operating costs of patient guidance services. During the COVID-19 pandemic, the system provided strong support for the implementation of hospital epidemic prevention measures, reduced unnecessary contact between medical staff and patients, and ensured the safety of both.

Medical Artificial Intelligence
ISSN: 2957-5524
ZENTIME PUBLISHING CORPORATION LIMITED