Validate documentation to support quality measures, clinical decision support tools, and clinical standards.
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Reviewed by: Arkangel AI clinical review team, Clinical quality and medical AI content
Healthcare organizations face critical quality challenges that impact patient outcomes and revenue
Quality depends on documentation, yet teams can only manually review a small share of charts. Missed diagnoses, care-gap omissions, and weak documentation slip through—hurting patient outcomes, lowering HEDIS/STARS scores, and exposing providers to audit risk. The gap widens as volume grows, because adding reviewers rarely keeps pace with chart counts.
Missed diagnoses, medication errors, and overlooked screenings create poor outcomes and erode patient trust in your organization.
Payer contracts and government programs tie reimbursement to clinical quality scores, directly impacting your revenue.
Poor documentation exposes providers to audit risks, compliance violations, and contributes to clinician burnout.
Transform your quality workflow with intelligent automation that scales
AI reviews 100% of charts in real time against HEDIS/STARS measures, clinical decision support, or your own standards. It surfaces care gaps, builds provider scorecards, and sends automated feedback to clinicians. Because every chart is checked—not a sample—quality scores rise, documentation stays audit-ready, and improvement scales without expanding your review team.
Review 100% of charts for HEDIS/STARS measures, integrate with clinical decision support (UpToDate, DynaMed), or define custom standards.
Identify care gaps, create provider scorecards, and build targeted clinical education programs to drive better outcomes.
Increase quality scores, strengthen payer relationships, and ensure audit-ready documentation for maximum reimbursement.
A simple three-step process to transform your clinical quality workflow
Rollout has three steps. An engineer configures the AI to your quality criteria and EHR. The platform then reviews every chart in real time, pulling directly from the record with reasoning and recommendations. Finally, it sends automated feedback to clinicians and aggregates dashboards—turning one-off audits into continuous, measurable quality improvement.
Work with a dedicated engineer to configure the AI environment and train on your organizational quality criteria.
Review 100% of charts in real-time, pulling directly from your EHR with detailed reasoning and recommendations.
Send automated feedback to clinicians, create education workflows, and aggregate dashboard insights for continuous improvement.
How AI chart review compares with manual quality audits on coverage, feedback speed, and outcomes.
Manual quality audits sample a fraction of charts, so care gaps and documentation errors go undetected until scores drop or an audit lands. AI reviews every chart in real time, flags gaps against your quality measures, and feeds findings straight to clinicians—lifting HEDIS/STARS performance without growing the review team.
| Capability | Arkangel AI | Manual quality review |
|---|---|---|
| Chart coverage | Reviews 100% of charts | Samples a small share |
| Feedback speed | Real-time clinician feedback | Delayed, periodic audits |
| Measure alignment | Checks every chart vs HEDIS/STARS | Inconsistent, reviewer-dependent |
| Scalability | Scales without added reviewers | Needs more staff as volume grows |
| Audit readiness | Continuously audit-ready records | Manual prep for each audit |
70%
of customers reduced denials by holding claims with documentation errors before submission.
Everything you need to know about chart intelligence for clinical quality
See how chart intelligence surfaces the quality gaps hiding in your records