A Randomized Controlled Trial Comparing Performance of Primary Care Clinicians in the Interpretation of SPIROmetry With or Without Artificial Intelligence Decision Support Software
试验速览
- 阶段
- 不适用
- 入组人数
- 228
- 试验地点
- 1
- 主要终点
- Preferred Diagnostic Performance
研究概览
简要总结
To evaluate whether an artificial intelligence decision support software (ArtiQ.Spiro) improves the diagnostic accuracy of spirometry interpreted by primary care clinicians, as measured by Clinician Diagnostic Accuracy (vs Reference Standard).
详细描述
This is a randomised controlled study to evaluate the effects of AI support software on the performance of primary care clinicians in the interpretation of spirometry. Clinicians will be provided with a clinical dataset of 50 entirely anonymous, previously recorded real-world spirometry records to interpret and will be asked to complete specific questions about diagnosis and quality assessment. The records will be randomly selected from a database comprising spirometry records from 1122 patients undergoing spirometry in primary care and community -based respiratory clinics in Hillingdon borough between 2015-2018.
Participating clinicians will be allocated at random to receive either spirometry records alone or spirometry records with the addition of an AI spirometry interpretation eport. The clinical spirometry records will be de-identified (name, date of birth, address, postcode, occupation, GP, medications data removed), by a member of the clinical care team.
Study participants (participating clinicians) will independently examine the same 50 spirometry records through an online platform. For each spirometry record, the primary care clinician participant will answer questions about technical quality, pattern interpretation, preferred diagnosis, differential diagnosis and self-rated confidence with these answers.
The study statistician will be blinded to treatment allocation up to completion of analysis and interpretation.
The reference standards for spirometry technical quality and pattern interpretation will be made by a senior experienced respiratory physiologist but without access to AI report.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- Double (Investigator, Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 99 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Clinicians working in primary care (for at least 50% of their job plan) in the UK, who refer for or perform spirometry (typically GP, practice nurse)
- •Able to access spirometry traces on study platform
- •Provide written informed consent via study platform
排除标准
- •1. Clinicians who have completed specialist training in respiratory medicine and recognised by the General Medical Council with a right to practise as a NHS consultant in respiratory medicine
研究组 & 干预措施
Control
Participants to report 50 spirometry records alone
Intervention
Participants report the same 50 spirometry records provided in the control arm with an artificial intelligence-powered spirometry interpretation report
干预措施: Artificial Intelligence-powered Spirometry Interpretation Report (Other)
结局指标
主要结局
Preferred Diagnostic Performance
时间窗: Six months
A correct case is where the preferred diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
次要结局
- Quality Assessment self-rated confidence(Six months)
- Differential diagnostic performance(Six months)
- Quality assessment performance(Six months)
- Pattern interpretation self-rated confidence(Six months)
- Diagnostic self-rated confidence(Six months)
- Pattern interpretation(Six months)