Survey of application value on an intelligent consultation system for common eye diseases

Authors: Chen Jingjing,  Xiang Yifan,  Wu Xiaohang,  Liu Zhenzhen,  Yan Pisong,  Hu Weiling,  Lao Zhihao,  Ma Zena,  Xie Xiaodong,  Zhang Caoxian,  Zhang Hairong,  Zhang Yu,  Xiao Huiming,  Lin Haotian

DOI: 10.3760/cma.j.cn115989-20200325-00204
Published 2020-08-10
Cite as Chin J Exp Ophthalmol, 2020,38(08): 692-697.

Abstract                               [View PDF] [Read Full Text]

Objective

To survey the application of an intelligent consultation system for common eye diseases and evaluate its applicational effectiveness on an internet hospital platform.

Methods

A cross-sectional study was performed in Zhongshan Ophthalmic Centre of Sun Yat-sen University.Natural language processing technology was applied to develop the intelligent consultation system for common eye diseases.Its efficiency and quality were evaluated.The survey data were collected from February 1 to 29, 2020 to analyze the demographic information, consultation time, consultation category, consultation content, service satisfaction.This study protocal was approved by an Ethic Committee of Zhongshan Ophthalmic Centre of Sun Yat-sen University(2020KYPJ095).

Results

The intelligent consultation system for common eye diseases was developed and successfully deployed in Internet Hospital of Zhongshan Ophthalmic Center.The repeatability and accuracy of the intelligent consultation system were 100.0% and 99.8%, respectively.During February 1 to 29, 2020, the intelligent consultation system served 6 462 patients, including 3 082 males(47.7%) and 3 380 females(52.3%). The average age of patients was 32.3 years old.Total of 1 135(17.6%) patients used the intelligent guidance consultation, and 5 375(82.4%) patients used the intelligent outpatient consultation.The intelligence consultation system was applied by 223 patients per day with a maximum of 74 patients per hour.The survey showed that 25.6% and 36.4% of the patients felt very satisfied and relatively satisfied with the efficiency of the intelligent consultation service, respectively; 24.3% and 37.8% of the patients were very satisfied and relatively satisfied with the quality of the intelligent consultation service, respectively.

Conclusions

Intelligent consultation system for common eye diseases can meet the needs of patients because of its high repeatability and accuracy.Patients are satisfied with the service efficiency and quality of the intelligent consultation system, which avoids the risk of cross infection and releases the burden of medical staff.

Key words:

Eye diseases/diagnosis; Eye diseases/therapy; Internet hospital; Survey; Intelligent consultation system for common eye diseases

Contributor Information

Chen Jingjing
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Xiang Yifan
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Wu Xiaohang
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Liu Zhenzhen
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Yan Pisong
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Hu Weiling
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Lao Zhihao
Wupol Information Technology Co., Ltd, Guangzhou 510620, China
Ma Zena
Wupol Information Technology Co., Ltd, Guangzhou 510620, China
Xie Xiaodong
Wupol Information Technology Co., Ltd, Guangzhou 510620, China
Zhang Caoxian
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Zhang Hairong
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Zhang Yu
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Xiao Huiming
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
Lin Haotian
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Centre, Sun Yat-sen University, Guangzhou 510060, China
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Updated: December 26, 2022 — 8:29 am