Oxipit to Offer Free of Charge Retrospective CXR Quality Audit at RSNA
At the annual RSNA meeting, the AI medical imaging company will present the new ChestEye Quality AI double reading tool. To showcase vanguard ChestEye Quality capabilities, Oxipit will offer a free-of-charge quality audit for 6 months of retrospective CXR data.
Vilnius, Lithuania, November 26, 2021 --(PR.com)-- ChestEye Quality is already deployed in multiple medical institutions across Europe. With 229.617 images processed, the platform helped to identify 20% extra clinically relevant nodules, as well as numerous missed cases of pneumothorax, device malpositions, consolidations and other clinically significant findings.
ChestEye Quality analyzes final radiologist reports and corresponding CXR images. The platform then identifies impactful clinical errors and missed radiological findings.
In retrospective mode, the platform can effortlessly audit tens or hundreds of thousands of cases. Only suspicious cases are highlighted for an additional radiologist review.
In prospective operations, the platform identifies reporting errors as soon as it receives a CXR image with a corresponding radiologist report. The platform will then automatically notify the clinician on the discrepancies found.
“Multiple clinical studies indicate that double reading is the most effective way to mitigate the risks of misdiagnosis and missed findings. By introducing AI into the quality assurance workflow, ChestEye Quality puts this theory into practice. The platform enables a full real time quality audit, where only clinically relevant cases are flagged for a secondary review. A robust framework of instant notifications via email, coupled with an easy-to-use analytical platform for suspicious case review, make ChestEye a truly impactful tool for routine medical imaging operations,” noted CEO of Oxipit Gediminas Peksys.
According to Gediminas Peksys, radiology professionals operate in a cognitively intense working environment. In the ‘always-on’ prospective mode, ChestEye Quality provides clinicians with an extra level of diagnostic support.
ChestEye Quality was already tested at multiple pilot locations in Europe, including primary care centers, tertiary hospitals and teleradiology service providers. Based on data from current deployments, up to 0.5% of reports feature clinically significant errors, including missed cases of pneumothorax, device malpositions or consolidations. In current trials, ChestEye Quality also helped medical institutions identify 20% more clinically relevant lung nodules. The platform utilizes smart nodule detection models geared towards minimizing false positives.
“What makes ChestEye Quality unique, is that these errors can be identified and corrected in real time, significantly improving patient outcomes,” added Gediminas Peksys.
In addition to prospective operations, ChestEye Quality can also operate as a retrospective quality audit tool. In routine clinical practice, where often a random sample of already reported cases are selected for quality audit, ChestEye Quality reviews 100% of previously reported cases - with only suspicious cases highlighted by AI for an additional radiologist review.
“We always start a ChestEye Quality deployment with a retrospective audit. This helps to evaluate the error threshold at the medical institution. The full 6 month CXR case audit can be completed in as few as 7 day,” said Gediminas Peksys.
According to Gediminas Peksys, a full scale CXR audit may also serve specific use cases - for instance, auditing by medical insurance providers.
“At Oxipit, we believe that a competitive edge in Artificial Intelligence is only the first step in AI medical imaging product development. The success lies in defining how software is implemented and used in the clinical workflow, selecting appropriate thresholds and solving user interface challenges. Having a team of data scientists working hand-in-hand with medical doctors, helps Oxipit address real world challenges currently faced by radiology specialists,” added Gediminas Peksys.
Oxipit will present ChestEye Quality and other AI medical imaging products at booth #5131 at RSNA on November 28th - December 2nd.
ChestEye Quality analyzes final radiologist reports and corresponding CXR images. The platform then identifies impactful clinical errors and missed radiological findings.
In retrospective mode, the platform can effortlessly audit tens or hundreds of thousands of cases. Only suspicious cases are highlighted for an additional radiologist review.
In prospective operations, the platform identifies reporting errors as soon as it receives a CXR image with a corresponding radiologist report. The platform will then automatically notify the clinician on the discrepancies found.
“Multiple clinical studies indicate that double reading is the most effective way to mitigate the risks of misdiagnosis and missed findings. By introducing AI into the quality assurance workflow, ChestEye Quality puts this theory into practice. The platform enables a full real time quality audit, where only clinically relevant cases are flagged for a secondary review. A robust framework of instant notifications via email, coupled with an easy-to-use analytical platform for suspicious case review, make ChestEye a truly impactful tool for routine medical imaging operations,” noted CEO of Oxipit Gediminas Peksys.
According to Gediminas Peksys, radiology professionals operate in a cognitively intense working environment. In the ‘always-on’ prospective mode, ChestEye Quality provides clinicians with an extra level of diagnostic support.
ChestEye Quality was already tested at multiple pilot locations in Europe, including primary care centers, tertiary hospitals and teleradiology service providers. Based on data from current deployments, up to 0.5% of reports feature clinically significant errors, including missed cases of pneumothorax, device malpositions or consolidations. In current trials, ChestEye Quality also helped medical institutions identify 20% more clinically relevant lung nodules. The platform utilizes smart nodule detection models geared towards minimizing false positives.
“What makes ChestEye Quality unique, is that these errors can be identified and corrected in real time, significantly improving patient outcomes,” added Gediminas Peksys.
In addition to prospective operations, ChestEye Quality can also operate as a retrospective quality audit tool. In routine clinical practice, where often a random sample of already reported cases are selected for quality audit, ChestEye Quality reviews 100% of previously reported cases - with only suspicious cases highlighted by AI for an additional radiologist review.
“We always start a ChestEye Quality deployment with a retrospective audit. This helps to evaluate the error threshold at the medical institution. The full 6 month CXR case audit can be completed in as few as 7 day,” said Gediminas Peksys.
According to Gediminas Peksys, a full scale CXR audit may also serve specific use cases - for instance, auditing by medical insurance providers.
“At Oxipit, we believe that a competitive edge in Artificial Intelligence is only the first step in AI medical imaging product development. The success lies in defining how software is implemented and used in the clinical workflow, selecting appropriate thresholds and solving user interface challenges. Having a team of data scientists working hand-in-hand with medical doctors, helps Oxipit address real world challenges currently faced by radiology specialists,” added Gediminas Peksys.
Oxipit will present ChestEye Quality and other AI medical imaging products at booth #5131 at RSNA on November 28th - December 2nd.
Contact
Oxipit
Gediminas Peksys
+37062599148
www.oxipit.ai
Gediminas Peksys
+37062599148
www.oxipit.ai
Contact
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