PHEMI Health DataLab is a unique, integrated big data management system that allows healthcare organizations to enhance innovation and generate value from healthcare data by simplifying the ingestion and de-identification of data with NSA/military-grade governance, privacy, and security built-in.
Conventional products simply lock down data, PHEMI goes further, solving privacy and security challenges and addressing the urgent need to secure, govern, curate, and control access to privacy-sensitive personal healthcare information (PHI).
Built on a privacy-by-design architecture, the software gives researchers, scientists and clinicians access to more information through responsible data sharing and provides a governance framework to facilitate compliance with privacy regulations.
PHEMI Health DataLab can scale to any size of organization, is easy to deploy and manage, connects to hundreds of data sources, and integrates with popular data science and business analysis tools.
PHEMI facilitates data sharing and provides a governance framework to assist with privacy regulation compliance using best-of-breed Privacy By Design end-to-end architecture to ensure that privacy measures are integrated into every step of the data pipeline and access to sensitive data is restricted to those allowed under the access policy.
A single pane of glass interface and integration with popular analytics tools enables self-serve innovation. Turnkey managed services and system integration accelerates time to analytics, machine learning, and AI.
PHEMI is deployment agnostic and offers flexibility by enabling data to be ingested from the cloud or on-premise and stored in the cloud/hybrid cloud. Data can be ingested from disparate sources, using hundreds of pre-built NiFi connectors, processors, and format converters, including medical data like ECG, x-rays, genomic, HL7, DICOM, and VCF.
PHEMI will organize data from ingest to application, with full provenance, anonymization, and tracking included. Original data is stored in unchanged, and new subsets have full auditability. Catalog, inventory, and index data for quick query performance. Versioning provides a time machine.
PHEMI protects privacy while enabling the secure, responsible sharing of data for research. Sensitive data is de-identified by masking, rounding, tokenizing, or encryption while still preserving the value inherent in the data. De-identification is done once to create multiple forms of anonymized data for different levels of access. Ensure privacy is uniformly and consistently enforced at scale with Attribute-Based Access Controls (ABAC) and role-based governance rules.