Research on the Application of “AI Technology + Precision Medicine” in Ultrasound Intelligent Information Management Systems
This study explores the application of “AI Technology + Precision Medicine” in ultrasound intelligent information management systems, aiming to standardize and optimize medical processes and investigate methods for managing ultrasound diagnostics and treatment. The study constructed an intelligent ultrasound management system and compared metrics from May to October 2020 (before system operation) with those from November 2020 to March 2021 (after system operation). Key metrics included the average time to complete ultrasound orders (hours), the average daily actual completed workload (sites/cases), the average patient waiting time (minutes), the pre-exam waiting time (hours), and patient satisfaction. After the implementation of the ultrasound intelligent management system, the completion time for ultrasound orders decreased from (71.36 ± 12.62) hours to (19.65 ± 3.25) hours; the average daily actual completed workload increased from (1652.38 ± 102.36) to (2385.46 ± 126.47); the average patient waiting time dropped from (42.36 ± 8.69) minutes to (21.56 ± 4.62) minutes; the pre-exam waiting time reduced from (27.02 ± 8.85) hours to (4.84 ± 0.97) hours; and the patient satisfaction rate increased to 91.26%. The ultrasound intelligent management system helps healthcare professionals optimize scheduling processes, increase ultrasound order completion rates, reduce patient waiting time, accelerate bed turnover rates, and enhance patient satisfaction.
Authors
- Huanmei Wu (ORCID: https://orcid.org/0000-0003-0346-6044)
- Wei Chu (ORCID: https://orcid.org/0000-0002-7704-5544)
- Chunyou Wang
- Jingjing Li (ORCID: https://orcid.org/0000-0003-0811-4988)
- Wu Huijie
- X. Lucas Lu (ORCID: https://orcid.org/0000-0001-6905-6887)
Publication Details
- Journal
- Journal of medicine and physical education.
- Published
- 2024-10-01
- DOI
- https://doi.org/10.62517/jmpe.202418505
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00