Theme

The evidence base for
our oncology AI

From clinical FAQs to peer-reviewed research โ€” everything you need to evaluate and trust Spiraldot Health.

Frequently Asked Questions

Common questions from oncology care teams, health system IT, and procurement.

Spiraldot Health is an AI clinical co-pilot built specifically for oncology care teams. It integrates with existing EHR systems to surface evidence-based treatment recommendations, flag drug interactions, and streamline documentation โ€” helping oncologists spend more time on patient care and less on information retrieval.
Yes. Spiraldot Health is fully HIPAA compliant and SOC 2 Type II certified. All patient data is encrypted at rest and in transit using AES-256 and TLS 1.3. We provide BAAs to all health system partners and run on HIPAA-eligible AWS services.
Spiraldot integrates with Epic, Cerner (Oracle Health), and other FHIR R4-compatible EHR platforms via our bi-directional FHIR API โ€” no custom middleware required. Integration timelines are typically 6โ€“10 weeks from contract to go-live.
General-purpose AI tools are not designed for clinical environments. They lack oncology-specific training, EHR integration, regulatory compliance, and the safety guardrails required in care settings. Spiraldot incorporates NCCN guideline alignment, curated clinical evidence, audit logs, and role-based access controls. Every recommendation is traceable and explainable.
No. Spiraldot is a decision-support tool โ€” a co-pilot, not an autopilot. It surfaces evidence-based options, relevant trial data, and risk signals to support the physician's judgment. All clinical decisions remain with the care team.
Spiraldot's AI is trained on a broad oncology corpus covering over 200 tumor types. For off-label treatments, the system surfaces supporting trial data, case series, and primary literature alongside standard-of-care guidelines โ€” giving clinicians a fuller evidence picture for complex cases.
Typical implementations take 6โ€“10 weeks from signed agreement to go-live, including EHR integration, security review, staff training, and phased rollout. We provide a dedicated implementation engineer and clinical success manager throughout. Typical time-to-first-value is under 30 days.
We offer flexible models including per-seat licensing and enterprise site licenses. Pricing scales with the size of your oncology practice or health system. Contact us for a custom quote โ€” we're happy to walk through ROI projections based on your clinical volume and workflow.

Product Comparison

How Spiraldot stacks up against general-purpose AI and legacy clinical decision support systems.

Capability Spiraldot Health General AI (GPT-4 / Gemini) Legacy CDSS
Oncology-specific trainingโœ“โœ—Partial
NCCN guideline alignmentโœ“โœ—Partial
Native EHR integration (FHIR)โœ“โœ—Partial
HIPAA compliantโœ“Enterprise onlyโœ“
SOC 2 Type II certifiedโœ“VariesVaries
Explainable AI (traceable citations)โœ“โœ—Partial
Rare tumor coverage200+ typesGeneral onlyLimited
Drug interaction flaggingโœ“โœ—โœ“
Clinical trial matchingโœ“โœ—โœ—
AI documentation assistanceโœ“Generic onlyโœ—
Audit log & role-based accessโœ“โœ—Basic
Dedicated implementation supportโœ“โœ—Varies

โœ“ = Full support ยท Partial = Limited or conditional ยท โœ— = Not available. Based on publicly documented capabilities as of 2025.

White Papers & Clinical Evidence

Peer-reviewed research, clinical validation studies, and technical deep-dives from the Spiraldot Health team.

Technical
FHIR R4 Integration Architecture for AI Clinical Decision Support Systems
A technical overview of Spiraldot's EHR integration layer, including data normalization, latency benchmarks, and security architecture for health system IT teams.
Outcomes
Reducing Oncologist Cognitive Load: Workflow Efficiency Gains with AI Co-Pilots
Time-motion study across 12 oncology practices measuring documentation time reduction, chart review speed, and clinician burnout scores before and after Spiraldot deployment.
Market Analysis
The State of AI in Oncology 2025: Adoption Barriers, ROI, and the Road to Standard of Care
Survey of 320 oncologists and health system administrators on AI adoption, top implementation barriers, and projected 3-year ROI across institution sizes.
Outcomes
The ROI of AI in Oncology: A Conservative Model for Health System Finance Teams
A 15-minute reduction per complex case across 30 monthly consults yields ~$18,000 in reclaimed physician time annually โ€” before accounting for biomarker completeness, prior auth friction, or trial identification gains.
Pharma & Biotech
Provider-Embedded Infrastructure for Trial Acceleration & Real-World Evidence: A Pharma Partner Guide
How Spiraldot's embedded eligibility logic, structured MDT decision capture, and line-of-therapy sequencing data creates a compliant, non-promotional pathway for trial feasibility and real-world drug performance insight across EUCAN markets.
Clinical Trial Matching
Automated Trial Eligibility Screening: Expanding Patient Access to Novel Therapies
How AI-powered trial matching increased clinical trial enrollment referrals by 3.2x across a 6-month pilot at a major academic medical center.

Ready to see it in action?

Request a live demo tailored to your oncology service line. Most demos take 30 minutes.