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ARKA Clinical Decision Support is designed to meet all four criteria for Non-Device CDS under FD&C Act §520(o)(1)(E) and FDA's January 2026 final guidance on Clinical Decision Support Software. Recommendations support, not replace, the clinician's judgment. Every recommendation is anchored in a published guideline or peer-reviewed source, with the basis available for independent review. CLIN emphasizes imaging appropriateness at order entry.
This recommendation is intended to support, not replace, clinical judgment. It is generated by ARKA, software designed to meet the four criteria for Non-Device Clinical Decision Support under FD&C Act §520(o)(1)(E) and FDA's final guidance on Clinical Decision Support Software (January 2026). The clinician is responsible for the final decision.
For Radiology leadership
You own appropriateness, dose stewardship, and radiologist time. Yet 20–50% of advanced imaging does not change management, ~25% of imaging cost is avoidable, and appropriateness criteria tables are the primary ordering resource for only ~1.6% of physicians — the guidance exists, but it lives in PDFs outside the workflow.
Your scorecard
The KPIs your board and leadership team track — where imaging leakage shows up first.
The problem
Benchmark-backed pain points tied to the metrics you own.
20–50% low-value
Low-value studies consume scanner time, dose, and reads that should go to the right test.
~1.6% adoption
Static criteria tables are the primary resource for ~1.6% of physicians — out of the chart, out of mind.
~25% of cost avoidable
~25% of imaging cost and ~20% of radiation dose are avoidable; inappropriate contrast/radiation is a safety and medicolegal exposure.
The fix
Each lever maps to a pain above — same order, same grid, so the pairing is obvious.
AIIE scores each order on structured FHIR context — not a generic table — with ~87.5% concordance to signed-off guideline scenarios (synthetic cohort; real-world validation in progress).
SHAP attribution shows why each order was flagged; every output links to the Evidence Library — defensible, not black-box.
ARKA-ED trains residents and PAs on appropriate ordering, improving quality upstream of the scanner.
The numbers
Modeled or published figures — labeled with their basis.
~87.5%
Guideline concordance (synthetic)
signed-off scenario cohort; real-world eval in progress
<800ms
in-flow, non-blocking score
engine SLA
35–40%
orders auto-clear, no queue
conservative modeled
Evidence
What we bring to the conversation — sourced from the ARKA buyer playbook.
Pushback
The concerns we hear most — and how we address them.
ARKA is non-blocking, silent unless a guideline fires, <800ms, with a one-click neutral override — pilot acceptance ran 64%. It cuts noise versus flag-everything tools.
Adoption of static criteria is ~1.6–2.4%. ARKA puts patient-specific guidance in the chart at order entry, so it is used by default, not looked up.
No. ARKA evaluates whether to order the study from structured data; it never reads pixels. It is Non-Device CDS under §520(o)(1)(E).
Your agenda
Three questions to put on the table — we'll answer with your data, not generic slides.
Question 1: What is your current appropriateness / guideline-adherence rate?
Question 2: How much scanner time goes to low-yield studies?
Question 3: How do residents learn appropriate ordering?
Explore
Jump into the modules most relevant to your seat.
45-minute clinical deep-dive with a live demo on a de-identified case series; an ARKA radiologist participates.
Quick answers
No — under 800ms, in-flow, with no extra clicks.
~87.5% guideline concordance on signed-off scenarios today (synthetic self-consistency, not a clinical-accuracy claim); retrospective real-world evaluation is in progress and a prospective pilot is planned — see the evidence ladder. Every output cites the Evidence Library.
45-minute clinical deep-dive with a live demo on a de-identified case series; an ARKA radiologist participates.
