Menu

CMS Imaging's Response to COVID-19
LinkedIn
Facebook
Twitter
YouTube
Instagram
RSS Feed
Medicom logo

deepmed

Medicom deepMed

Anonymized clinical data for research, machine learning, and AI applications.


Based on Imagex’s building blocks for indexing and federating access to images and reports, deepMed is Medicom’s system for collecting and de-identifying clinical information for research, machine learning, and AI applications.



HIGHLIGHTS

Automated de-identification.

  • Automates de-identification of images, even when there is burned-in PHI
  • Connects directly to a database (EMR or RIS) and PACS/VNA at a facility
  • Cases can be located based on information in the RIS or EMR like patient demographics, history, diagnosis, conditions, procedure type and outcomes
  • Secures delivery of big data sets

Overview

Automatic, bulk de-identification of cases that fully complies with regulatory requirements.


HIPAA PRIVACY COMPLIANCE

Medicom complies with and de-identifies all data in accordance with §161.514(a)-(c) of the HIPAA Privacy Rule.

BURNED IN PHI REMOVAL

Any burned in PHI are removed using a customized implementation where blackout zones are identified on an image defined by a health system user from each modality.

deepMed contains multiple safeguards to ensure that all PHI has been stripped from the DICOM header and removed from images, including:

  • Checks on image size,
  • OCR (optical character recognition) scans for text, and
  • Detection of image boundaries.

SANITIZATION OF IDENTIFYING INFORMATION

DICOM tags and text containing individually identifiable data are sanitized in deepMed’s automated process - fields are extracted and replaced with randomly generated characters.

CHECKPOINT

Images that fail deepMed’s quality control mechanisms are held in Checkpoint for manual review.

Checkpoint groups images based on reason for quality control failure and another identifier (usually modality).

FEATURES

DeepMed

De-Identification and Anonymization
Conforms with the HIPAA Safe Harbor methodology.
De-identification is performed locally on customer device.
DICOM header sanitization.
Report sanitization.
Burned-in protected health information (PHI) sanitization.
Store de-identified data to remote or local destinations.
Supports longitudinal data collection.
Supports 3D mammography files.
Supports re-identification.
Supports inclusion of other clinical or research documents.
Integrates with databases (EHR, RIS) and DICOM archives.
Supports query construction with DICOM and SQL.
Accessible via a web interface.
Provide remote de-identification access to partners. Pending