Oxipit Study: 1 in 552 CXR Studies Feature Clinically Significant Diagnostic Errors
Oxipit has conducted a retrospective validation study from collected internal data of ChestEye Quality performance at more than 10 pilot deployment institutions. The study concludes that 1 in 552 (0.18%) chest X-ray studies reported by a radiologist include clinically significant diagnostic mistakes. The vast majority - 78.46% - of the errors are missed findings of pulmonary nodules and lymphadenopathy.
Vilnius, Lithuania, July 20, 2022 --(PR.com)-- More than 186.000 CXR reports were analyzed in the scope of the study. The studies originate from multiple geographic regions, spanning institutions from Western, Eastern and Southern Europe, as well as Latin America. The study scope includes primary care clinics, teleradiology service providers and tertiary hospitals.
The study highlights only clinically significant diagnostic errors, focusing on the missed findings which could have a direct impact on the patient outcomes over the treatment course.
In the study, the rate of clinically significant missed findings range from 1 in 1305 (0.08%) to 1 in 109 (0.92%) depending on the type of the institution, as well as the general aspects of the population served.
The missed findings - indicated by Chesteye Quality - were later validated by the radiologists at the medical institution.
“While the rate of missed findings varies significantly depending on the type of medical institution, the diverse geographic span and multiple types of the medical institutions provide a real-world benchmark for day-to-day radiologist performance. With ChestEye Quality serving as a safety-net, such errors can be eliminated with nearly no impact on the radiologist workflow,” says Chief Medical Officer at Oxipit Dr Naglis Ramanauskas.
The study was performed by analyzing ChestEye Quality data at the software deployment sites. ChestEye Quality analyzes chest X-ray images and corresponding radiologist reports. If the software detects a mismatch, it notifies the radiologist to take a second look at the study.
The Oxipit study also indicated that an average of 30% of all studies were identified as normal with high confidence, meaning that they could be autonomously reported on by the ChestLink AI software. The range of high-confidence normal studies varied from 17% to 47% depending on the type of the medical institution. The study further solidifies ChestLink performance with up to 99.8% sensitivity.
ChestLink is the first CE marked autonomous AI application, which can produce final healthy patient reports without any involvement from a human radiologist. The platform only reports on studies, where it is highly confident that the CXR image features no abnormalities. The study highlights that ChestLink can autonomously report on nearly half of the radiologist work scope depending on the type of the medical institution.
The study highlights only clinically significant diagnostic errors, focusing on the missed findings which could have a direct impact on the patient outcomes over the treatment course.
In the study, the rate of clinically significant missed findings range from 1 in 1305 (0.08%) to 1 in 109 (0.92%) depending on the type of the institution, as well as the general aspects of the population served.
The missed findings - indicated by Chesteye Quality - were later validated by the radiologists at the medical institution.
“While the rate of missed findings varies significantly depending on the type of medical institution, the diverse geographic span and multiple types of the medical institutions provide a real-world benchmark for day-to-day radiologist performance. With ChestEye Quality serving as a safety-net, such errors can be eliminated with nearly no impact on the radiologist workflow,” says Chief Medical Officer at Oxipit Dr Naglis Ramanauskas.
The study was performed by analyzing ChestEye Quality data at the software deployment sites. ChestEye Quality analyzes chest X-ray images and corresponding radiologist reports. If the software detects a mismatch, it notifies the radiologist to take a second look at the study.
The Oxipit study also indicated that an average of 30% of all studies were identified as normal with high confidence, meaning that they could be autonomously reported on by the ChestLink AI software. The range of high-confidence normal studies varied from 17% to 47% depending on the type of the medical institution. The study further solidifies ChestLink performance with up to 99.8% sensitivity.
ChestLink is the first CE marked autonomous AI application, which can produce final healthy patient reports without any involvement from a human radiologist. The platform only reports on studies, where it is highly confident that the CXR image features no abnormalities. The study highlights that ChestLink can autonomously report on nearly half of the radiologist work scope depending on the type of the medical institution.
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Oxipit
Gediminas Peksys
+37062599148
www.oxipit.ai
Gediminas Peksys
+37062599148
www.oxipit.ai
Contact
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