Frequently Asked Questions

BEKhealth does two things with a site’s EHR data: it identifies the right patients for research, and it turns clinical records into real-world data. For research, the platform reads structured fields and unstructured clinical notes, applies protocol-specific logic, and validates results through clinical quality review to sharpen feasibility, site selection, and enrollment. For real-world data, BEKhealth curates high-fidelity, EHR-derived longitudinal datasets that support real-world evidence, regulatory submissions, and post-market research. Both run on the same AI chart abstraction and patient matching engine.

BEKplatform is BEKhealth’s AI-powered technology for patient matching and feasibility. It analyzes structured and unstructured EHR data to surface protocol-eligible patients, then validates matches through human clinical QA. Sites use it to respond to feasibility requests, identify eligible patients, and attract more studies.

BEKnetwork is a collaborative of community-based research sites and healthcare organizations working together to accelerate clinical research and real-world evidence. It includes two parts. BEKnetwork Site Selection provides real-time, patient-level insight for feasibility, site selection, and protocol optimization. BEKnetwork Real World Data provides curated, high-fidelity, EHR-derived longitudinal data for retrospective and prospective research. Both are powered by BEKplatform, BEKhealth’s AI chart abstraction and patient matching platform.

BEKhealth serves sponsors, CROs, PE-backed site networks, and individual research sites. Sponsors and CROs use it for feasibility, site selection, and real-world data. Site networks use it to win more trials, increase study volume, and generate new revenue from their de-identified data through approved real-world data partnerships.

What you need to get started with BEKhealth depends on the use case. For site selection and patient matching, sites provide access to their EHR data under an executed BAA, along with the protocol or therapeutic criteria to evaluate. Sites can use BEKplatform and join BEKnetwork for site selection without participating in real-world data. Real-world data is a separate, opt-in path governed by a DUA: contributing sites supply de-identified EHR data, while sponsors and CROs bring the research question or cohort of interest. In all cases, BEKhealth handles integration, de-identification where required, and matching configuration. The fastest way to begin is to request a demo.

BEKhealth interprets physician notes, reports, and free-text documentation using clinical language models and medical ontologies, transforming unstructured data into structured eligibility signals that can be used for feasibility, recruitment, and cohort building.

BEKplatform combines AI interpretation with human-in-the-loop clinical review, protocol logic validation, and structured quality assurance processes to ensure that patients flagged as eligible meet true clinical criteria, not just surface-level matches.

BEKplatform offers fully autonomous automation. BEKhealth combines the AI interpretation with clinical QA, site governance, and controlled workflows to ensure accuracy, trust, and regulatory alignment.

BEKhealth supports all major EHRs, including Epic, Oracle Cerner, MEDITECH, NextGen, and others. Integrations follow established interfaces and are designed to minimize IT burden. A full list of supported EHRs can be found here.

BEKhealth’s AI is completely contained within your organization and never leaves the four walls. We enforce privacy through purpose-driven data extraction, expert-determined de-identification, site-level data segregation, enterprise encryption, and role-based access controls. Identifiable data is only used when explicitly required for approved workflows. 

Data is de-identified using expert determination methodologies that remove direct identifiers and reduce re-identification risk while preserving clinical utility for research, feasibility, and real-world evidence generation.

BEKhealth enforces HIPAA compliance through purpose-driven data extraction, expert-determined de-identification, site-level data segregation, enterprise-grade encryption, and role-based access controls. AI is used within these safeguards to support research without exposing patient identity.

BEKhealth embeds compliance into system design through HIPAA-aligned architecture, data governance controls, audit trails, access management, and structured onboarding processes with BAAs and DUAs.

BEKhealth is designed so research sites retain ownership and control over their data. Patient data originates from the site’s own EHR and is accessed only for explicitly agreed-upon purposes, including approved real-world data initiatives, with all use governed by site agreements and compliance requirements.

Identifiable data is used when contractually required for site-approved workflows, such as trial recruitment, and is technically enforced based on the approved use case.

For feasibility and real-world data use cases, BEKhealth works with de-identified data.

No. Sites can use BEKplatform for AI-powered patient matching and join BEKnetwork for site selection without participating in real-world data. Real-world data is a separate, opt-in program with its own agreements and revenue share. Sites choose whether and when to take part, and they retain ownership and control of their data throughout.

BEKhealth reduces manual chart review by interpreting patient records before coordinators open a chart. The platform analyzes structured EHR data and unstructured clinical documentation to pre-filter patients who appear aligned with protocol criteria.

Rather than replacing human review, BEKhealth narrows the patient pool and organizes relevant clinical context so chart review becomes a focused validation step. Clinical quality review ensures accuracy is maintained while significantly reducing time spent reviewing non-eligible patients.

When AI cannot confidently interpret a patient record, it is flagged for review rather than assumed eligible. The platform highlights areas of uncertainty and routes the record for clinical quality or coordinator validation, ensuring final decisions are based on documented evidence and human review.

Clinical data contains ambiguity, nuance, and context that cannot always be resolved algorithmically. Human oversight ensures that AI supports decision-making without replacing clinical judgment.

BEKplatform analyzes your site’s own EHR data, including structured fields and unstructured clinical notes, to assess how well protocol criteria align with patients you actually have. AI and clinical review interpret existing documentation, capturing diagnoses, treatments, labs, and clinical context that coded data alone often misses.

This produces feasibility insights grounded in documented patient records, reducing overestimation and improving confidence in enrollment projections before a study is activated.

By applying protocol logic earlier and more accurately, BEKhealth helps identify patients who truly meet criteria—reducing late-stage disqualifications that lead to screen failures.