Manifold

Automatically detects and maps disparate EHR data formats, coding standards (ICD-10, SNOMED CT, etc.), and field definitions across different healthcare systems. Reconciles conflicting data representations into a unified schema without manual field-by-field configuration.

Consolidates patient records and research datasets from multiple healthcare institutions into a single queryable repository. Handles deduplication, record linking, and temporal data alignment across different data collection timelines.

Automates the process of requesting, approving, and delivering datasets across research institutions. Manages data sharing agreements, approval workflows, and secure data transfer without manual export/import cycles.

Exports integrated datasets in standard formats (CSV, SPSS, R, SAS) compatible with statistical analysis software. Supports direct integration with common research tools and maintains data integrity during export.

Enables secure sharing of de-identified patient datasets across research institutions with built-in HIPAA compliance controls. Automatically applies de-identification rules, tracks data access, and maintains audit trails for regulatory compliance.

Provides shared workspace for research teams to view, annotate, and modify datasets simultaneously across institutions. Maintains version history, change tracking, and conflict resolution for concurrent edits.

Analyzes integrated datasets for completeness, consistency, and validity issues. Generates detailed quality reports identifying missing values, outliers, inconsistencies, and data integrity problems with recommendations for remediation.

Enables researchers to define inclusion/exclusion criteria and automatically identify matching patients from integrated datasets. Supports complex criteria combining demographics, diagnoses, procedures, lab values, and temporal conditions.

Constructs and displays patient clinical timelines showing events, procedures, diagnoses, lab results, and medications in chronological order. Enables researchers to visualize disease progression and treatment patterns across time.

Manages user roles, permissions, and data access policies across research teams and institutions. Enforces role-based access control (RBAC), tracks who accessed what data and when, and supports institutional data governance policies.

Maintains detailed records of data origin, transformations, and usage throughout the research pipeline. Tracks which source systems contributed to final datasets and documents all data processing steps for reproducibility and compliance.

Implements and enforces institutional data governance policies including data retention, usage restrictions, and compliance requirements. Automatically applies policies to datasets and alerts when policy violations occur.