Experiment on the Use of Innovative Computer Vision Technologies for Analysis of Medical Images in the Moscow Healthcare System
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 133,000
- 试验地点
- 1
- 主要终点
- Number of errors
研究概览
简要总结
It is planned to integrate various services based on computer vision technologies for analysis of the certain type of x-ray study into Moscow Unified Radiological Information Service (hereinafter referred to as URIS).
As a result of using computer vision-based services, it is expected:
- Reducing the number of false negative and false positive diagnoses;
- Reducing the time between conducting a study and obtaining a report by the referring physician;
- Increasing the average number of radiology reports provided by a radiologist per shift.
详细描述
Recently a growth in the number of radiology studies across multiple modalities has been observed alongside the modest increase in staffing levels. This carries higher risks of increased workload and efficiency losses. The integration of computer vision-based services into URIS will improve the radiologists' productivity and job performance.
Existing prerequisites for conducting the study:
- Increasing the number of preventive and diagnostic radiological studies entails the growing workload for radiologists and increased risk of interpretation errors, which in turn leads to the decrease in quality of medical care.
- When a radiologist opens a worklist of studies, in the absence of special notes, he/she writes a report in the random order, not being able to select from the list the studies that require the most attention and prompt response (studies with pathological findings), which increases the time of diagnosis.
- The absence of the structured pre-filled template of report leads to the increase in time for preparing reports.
- A radiologist has to spend considerable time evaluating the dynamics of pathological changes, which also increases the time to prepare a report as well as the risk of error.
- Interpretation of preventive studies requires double reading, which is implemented inefficiently due to the staff shortage.
Study objectives:
- Study the diagnostic accuracy of the Services in accordance with the methodological guidelines No. 43 "Clinical trials of software based on intelligent technologies (diagnostic radiology)" (recommended by the Expert Council on Science of the Moscow Healthcare Department, Protocol No. 8 of June 25, 2019).
- Audit the studies conducted with Services application in order to determine the number of interpretation errors, and compare it with the audit result without their application (hypothesis 1).
- Conduct timekeeping to estimate time for preparing a report and the total number of evaluated studies with and without using the Services (hypothesis 2,3).
- Conduct a survey of radiologists who use the Services in their work, in order to determine their opinion about the implementation of innovative technologies in the diagnostic process.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Crossover
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age (over 18 years)
- •Gender (male and female)
- •Referral for the study
- •Signed informed consent to participate in the Experiment
- •Chest computed tomography and Low-dose computed tomography for lung cancer detection or mammography for breast cancer detection or chest X-ray for lung pathology detection
排除标准
- •Another type of study (including a different modality and anatomical area)
结局指标
主要结局
Number of errors
时间窗: Upon completion, up to 4 years
Change of at least 30% in the number of errors in interpretation of the studies with using computer vision-based services compared to the number of errors in interpretation without their application.
次要结局
- Number of reports(Upon completion, up to 4 years)
- Report turnaround time(Upon completion, up to 3 year)
- Change in the errors of services per the feedback form(Upon completion, up to 4 years)
