An interventional study of Artificial Intelligence-powered Spirometry Interpretation Report in Lung Disease, sponsored by Royal Brompton & Harefield NHS Foundation Trust. Recruiting at 1 site in United Kingdom. Open to participants aged 18 Years to 99 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-02-16.
Sponsored by Royal Brompton & Harefield NHS Foundation Trust · Not applicable, Interventional, and Health services research
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).
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.
The reference standard for diagnosis will be made by a panel of three respiratory specialists from the clinical care team with access to medical notes and results of relevant investigations but without access to AI report.
3,303 studies on the registry are indexed under Lung Diseases; 355 are open to participants now.
This study's planned enrollment of 228 is above the median of 72 across 2,118 interventional studies indexed under Lung Diseases.
Browse Lung Diseases studies →Royal Brompton & Harefield NHS Foundation Trust is the lead sponsor of 137 studies on the registry; 18 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Participants to report 50 spirometry records alone
Participants report the same 50 spirometry records provided in the control arm with an artificial intelligence-powered spirometry interpretation report
Other: Artificial Intelligence-powered Spirometry Interpretation Report
A report generated by artificial intelligence powered software that assessed technical quality of spirometry and estimates the diagnostic probability of six categories: COPD/Asthma/ILD/ Normal/Other obstructive/Other Unidentified
Also known as: ArtiQ.Spiro
Preferred Diagnostic Performance
A correct case is where the preferred diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
Time frame: Six months
Pattern interpretation
A correct case is where the participants' selected pattern matches the reference pattern. Options are: Normal, Airflow obstruction, Possible restriction or non-specific pattern, Possible Mixed Disorder. Units will be percentage of total cases that are correct.
Time frame: Six months
Differential diagnostic performance
A correct case is where the preferred or differential diagnosis matches the reference final diagnosis. Units will be percentage of total cases that are correct.
Time frame: Six months
Quality assessment performance
A correct case is where the participant's quality grade matches the reference quality grade. Options are: Acceptable (Grade A/B) or Not Acceptable (Grades C/D/E/F/U). Units will be percentage of total cases that are correct.
Time frame: Six months
Pattern interpretation self-rated confidence
Pattern interpretation self-rated confidence will be measured on a visual analogue scale (0-10) where 0 = not confident at all; 10= very confident)
Time frame: Six months
Diagnostic self-rated confidence
Diagnostic self-rated confidence will be measured on a visual analogue scale (0-10) where 0 = not confident at all; 10= very confident)
Time frame: Six months
Quality Assessment self-rated confidence
Quality Assessment self-rated confidence will be measured on a visual analogue scale (0-10) where is 0 = not confident at all; 10= very confident)
Time frame: Six months
Plan to share: No
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Royal Brompton & Harefield NHS Foundation Trust