Clinical trial NCT04186104: Artificial Intelligence in Children's Clinic
Official title: Application of Artificial Intelligence in Children's Clinic
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Artificial Intelligence
Outpatient
Keywords: Artificial Intelligence
Outpatient
process improvement
Lead sponsor: Shanghai Jiao Tong University School of Medicine
Sponsor class: OTHER
First posted: 2019-12-04
Enrollment: 626
Sex: ALL
Minimum age (years): 2
Maximum age (years): 18
Standard ages: CHILD
ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: In China, the number of children's medical services is still far behind the growing demand for children's health care. The phenomenon of children's parents queuing overnight for registration is no longer surprising. This is because of the increase in the number of children and the shortage of pediatric talents. In the department of pediatrics, the number of patients increases year by year, but pediatrician is short of supply from beginning to end. In addition to outpatient service, pediatricians in large hospitals also perform operations, scientific research and other tasks. As a result, many doctors have to give up their vacations, which makes them miserable and reduces their enthusiasm for work. The long queuing time also reduced the satisfaction of patients, resulting in the intensification of the conflict between pediatric doctors and patients.

This research project aims to create a human-computer integrated system and develop a new diagnosis process embedded with artificial intelligence (AI). The function of AI system mainly includes 3 aspects. (1) The patient uses a mobile phone application embedded with AI that allows him to have check-up before see a doctor. The program will ask the patient a number of questions. Then, based on the patient's answers, AI will recommend a series of examination, all of which would be reviewed by the physician beforehand. After the patient pays for it, he could go straight to do the examination. So, next he could go to the doctor with the examination report which saves the patient the trouble of queuing. (2) At the same time, the AI system could also automate the medical history. The patient would complete self-help history collection in the spare time. The AI system collects the medical history and automatically import it to the doctor's computer. Doctors' main job is to modify the medical history generated by AI. To some extent, it lightens the burden of doctors. (3) During the visit, the AI system automatically captures the information in the patient's electronic medical record and generates the possible diagnosis. This process is of great help to junior doctors, and may serve as a cue.

In short, this study is helpful to effectively reduce the waiting time of patients and greatly increase their medical experience. While reducing the work intensity of doctors, the outpatient procedure of our hospital has been effectively optimized to alleviate the shortage of pediatricians to some extent.

Detailed description: Relying on mobile application and computer software, it would achieve:

1. Intelligent guidance and matching the department;
2. Intelligent medical history collection, and AI medical record generation;
3. Automatically recommend examination items;
4. Assist in clinical diagnosis and make intelligent diagnosis suggestion.

Eligibility criteria: Inclusion Criteria:

Patients aged 2 months to 18 years old and will go to Shanghai children's medical center for treatment.

Exclusion Criteria:

1. People who don't agree to participate.
2. People who can't cooperate.
3. People who are difficult to follow up.

Primary outcomes:
measure: Evaluate the efficiency of the two processes
timeFrame: up to 1 months
Secondary outcomes:
measure: Evaluate patients' rate of satisfaction for medical processes
timeFrame: up to 1 months
measure: Economic measurements
timeFrame: up to 1 months
measure: Work efficiency of doctors
timeFrame: up to 1 months
Other outcomes:
Locations:
city: Shanghai
country: China
facility: Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine
state: Shanghai
city: Shanghai
country: China
facility: Shanghai Children's Medical Center
Study officials:
affiliation: Shanghai Children's Medical Center
name: Shijian Liu, Ph.D
role: PRINCIPAL_INVESTIGATOR
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