Clinical Research Blog
Top 5 Clinical Trial Enrollment Metrics to Watch in 2026
Clinical trial success in 2026 will depend on more than enrollment numbers. From time to first patient in to diversity benchmarks, discover the five key metrics that will define performance—and how sites can prepare to meet evolving sponsor and regulatory expectations.
AI-Powered Patient Recruitment: How Integrated Tools Accelerate Clinical Trial Enrollment
Clinical trial enrollment has long been slowed by manual chart reviews and fragmented workflows. By embedding AI-powered patient matching directly into CRIO’s platform, and pairing it with Delfa’s multi-channel engagement, BEKhealth is helping sites accelerate recruitment, reduce…
Combating Health Misinformation with Accurate, Transparent Data
Health misinformation erodes trust and slows trials. Accurate, transparent, and inclusive data helps clinical research build confidence, strengthen participation, and counter misinformation effectively.
Why Overworked Teams Lead to Enrollment Delays and How AI Can Help
The clinical research industry blames enrollment delays on “hard-to-find patients,” but the real culprit is overworked research coordinators making split-second triage decisions. Those accumulated “maybe later” patients are what’s really stretching your timelines.
How AI Can Drive Diversity in Clinical Trials and Improve Patient Outcomes
AI is revolutionizing clinical trials by enhancing patient diversity, improving recruitment processes, and ensuring more inclusive research. This post explores how AI is paving the way for more equitable trials and better patient outcomes.
AI in Clinical Research: Why NLP and LLMs Work Better Together
BEKhealth combines NLP and LLMs to power smarter clinical workflows—using each where it works best, from patient matching to summarization and communication.
Smarter Site Selection: What Sites Can Do to Stand Out in Feasibility Scoring
Sponsors are using data-driven feasibility scoring tools to decide which sites get selected for studies. This post explains how sites can proactively stand out by using EMR data, performance metrics, and AI-powered tools to prove trial readiness.
The Hidden Cost of Protocol Deviation and How Better Patient Matching Solves It
Protocol deviations are often viewed as isolated issues, but they usually point to deeper workflow challenges at the site level. This post explores how smarter patient matching—powered by AI and EMR data—can help clinical research teams reduce preventable deviations and improve overall trial quality.
What If You Could Skip the Manual Chart Review? AI Tools Built for CRCs
Clinical research coordinators are often buried in manual chart reviews that slow recruitment and strain site resources. This post explores how EMR search tools for clinical research coordinators, powered by AI, can streamline patient identification, reduce workload, and help research teams move from reactive to proactive enrollment—without sacrificing accuracy or oversight.
From Static Lists to Real-Time Matches: How AI Is Revolutionizing Trial Eligibility Screening
Traditional trial recruitment is too slow. Learn how real-time eligibility screening uses AI to surface eligible patients instantly—cutting enrollment delays, reducing manual work, and helping sites hit their goals faster.
Safeguarding Patient Trust: Ethics and Privacy in Real‑World Data AI
As AI becomes more embedded in clinical research, protecting patient trust is more important than ever. This post explores how to ethically use real-world data—balancing innovation with privacy, transparency, and responsible stewardship.
AI & the Clinical Research Coordinator: Redefining Roles, Not Replacing Them
Many research teams hesitate to adopt AI in patient recruitment—not because they doubt its potential, but because they fear disruption. This post explores why that hesitation is often misplaced, and how a practical, system-friendly approach to AI is already transforming recruitment timelines and workflows.
It’s Not Too Late: How to Implement AI-Powered Patient Recruitment—Fast and Without the Headaches
Many research teams hesitate to adopt AI in patient recruitment—not because they doubt its potential, but because they fear disruption. This post explores why that hesitation is often misplaced, and how a practical, system-friendly approach to AI is already transforming recruitment timelines and workflows.
Human-in-the-Loop: Combining Purpose-Built AI and the Human Touch to Ensure Data Accuracy
In clinical research, speed and precision can’t come at the cost of trust. BEKhealth’s human-in-the-loop model bridges the gap between AI-driven patient matching and clinical oversight—pairing powerful, purpose-built technology with expert human review. The result? Faster, more accurate recruitment that research teams can rely on.
Inside BEKplatform’s Ontology: The 24 Million-Term Engine Powering Better Patient Matches
BEKhealth’s proprietary ontology decodes medical language across 30 million records—turning fragmented data into actionable matches that accelerate trial enrollment, improve feasibility, and expand access for patients who’ve long been overlooked.