HealthAIdir logoHealthAIdir

EHR

An electronic health record is a digital record designed to share patient information across care settings.

technicalPublished 2026/06/06Last verified 2026/07/17

An EHR, or electronic health record, is a digital record of patient health information designed for use across care settings. In healthcare AI evaluation, EHR context matters because many tools need to read, write, summarize, or route information inside existing clinical workflows.

When reviewing an AI tool, check whether it supports the specific EHR used by the organization, what data it can access, whether it writes back to the chart, and what approval controls are available.

Application scenario: In workflow review, this term helps teams map a vendor claim to the care setting, data flow, integration point, user handoff, and oversight step where it applies. Procurement impact: Buyers should evaluate evidence, interoperability effort, security and privacy controls, pricing assumptions, support, and compliance responsibilities before shortlisting or contracting for a tool that depends on this capability.

Sources and review notes

These links support definition-level research and do not establish the regulatory status, safety, or suitability of any product.

ONC describes an electronic health record as a digital, longitudinal patient record available to authorized users and distinguishes the broader EHR concept from an EMR that is usually limited to one provider or practice. The ONC Health IT Certification Program tests Health IT Modules against specific certification criteria, and the Certified Health IT Product List records the developer, product, version, criteria, status and compliance information for certified modules. Certification therefore applies to the listed module, version and criteria; it does not prove that every product feature, interface, local configuration or downstream workflow is certified, complete, safe or interoperable. Buyers should verify the exact product, version, deployment model and modules; CHPL listing and certification status where relevant; source systems and record authority; supported data classes, standards, profiles, terminology versions and read/write operations; patient and provider identity matching; role, consent and break-glass controls; audit trails; reconciliation and clinician approval; interface fees and dependencies; migration, export, retention, downtime and disaster-recovery procedures; and testing in the intended care workflow. A vendor statement that it integrates with an EHR is insufficient without named interfaces, supported versions, responsibility boundaries, representative test results and production monitoring.

FAQs

Why does EHR integration matter for healthcare AI tools?
EHR integration affects workflow fit, data access, documentation review, and whether clinicians need to copy information between systems.

Related research

Use related glossary terms and healthcare AI tool profiles to connect terminology checks with vendor due diligence.