Human verified automated de-identification of sensitive healthcare information for regulatory compliance
iMerit’s purpose-built application for data de-identification and PHI (Protected Health Information) removal and cleaning is fully automated with pre-trained NLP models to detect and protect sensitive patient information and have studies ready for model ingestion. Optionally add a verification and review layer with human-in-the-loop (HiTL) teams for regulatory compliance and medical confidentiality.
Pre-trained text detection model automatically identifies, blurs, and obscures protected health information.
Easily integrate optional human review and verification processes for added quality assurance across your data pipeline.
Ensure safe and compliant radiology data across all 18 HIPAA protected health identifiers.
Simplify data sharing and easily leverage de-identified assets across projects using iMerit’s file explorer plugin.
Leading healthcare provider works with iMerit to de-identify and clean burn-in on 20,000 ultrasound videos through automation and human-in-the-loop verification for AI applications.
Leading healthcare provider couldn’t utilize thousands of ultrasound videos due to them containing personally identifiable patient information burned into the images.
iMerit implemented its purpose-built de-identification solution to clean and anonymize the data in preparation for structuring.
The resulting de-identified dataset became a valuable resource for developing and training AI/ML models, leading to innovations in disease diagnosis, treatment planning, and patient care.
Streamline your data pipeline with a robust platform that converts raw files to de-identified for seamless utilization.
Fully customizable solution can meet the evolving needs and requirements of your project.
Leverage a fully automated or human-in-the-loop approach for optimal results in your data.
With intuitive import and export file explorer plugins, the solution simplifies the data exchange process.
Monitor quality and track progress to ensure project milestones are achieved.
iMerit offers two approaches in its medical data de-identification solution to meet diverse client project needs. The fully automated approach replicates the HiTL steps but excludes the HiTL correction process. The HiTL approach utilizes the PHI De-ID anonymizer plugin and text detection model to retrieve medical images, blurring burned-in text and anonymizing PHI in metadata. The HiLT correction step engages healthcare data specialists to correct any PHI burn-in. The PHI De-ID Export Plugin, in the HiTL approach, exports annotated images by obscuring detected text fields. The fully automated approach replicates the HiTL steps but excludes the HiLT correction process.
iMerit’s network of US board-certified physicians collaborates closely with our global workforce of expert medical annotators to ensure that the de-identified data meets rigorous quality control and compliance standards. Hybrid workflows on the iMerit Ango Hub platform facilitate the seamless scaling of data operations while enhancing data intelligence for effective project management.
iMerit works with clients to source, identify, and ready medical data for de-identification.
Transfer data seamlessly to Ango hub, where PHI is automatically identified and cleaned.
After de-identification, iMerit annotates and structures data for the specified model application.
Model outputs are evaluated against custom criteria to ensure quality.
Data security and compliance in Medical AI requires knowledge, vigilance, and adaptability to evolving regulatory needs. At iMerit, every annotation and process is geared towards facilitating successful FDA submission in the ever-changing regulatory landscape. With comprehensive training, robust physical safeguards, and advanced technologies, we guarantee that all data, personnel, and processes align with the latest healthcare regulatory guidelines.
The need for speed in high-quality data annotation has never been greater. iMerit combines the best of predictive and automated annotation technology with world-class data annotation and subject matter experts to deliver the data you need to get to production, fast.
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