Medscape Medical NewsAll articles

RayCare 2.3

RaySearch Laboratories AB (publ) • Radiology • 07/08/2019

510(k)IEC 62304 Class C
FDA Summary PDF

Device Purpose

RayCare 2.3 is a software-based oncology information system designed to streamline cancer care by managing clinical workflows, patient data, and scheduling across radiation, medical, and surgical oncology disciplines. Its methodology involves a client-server architecture with modular functionalities, focused on efficient information transfer, storage, and display, excluding diagnostic activities and treatment delivery recording.

Summary

RayCare 2.3 is an oncology information system designed to support the comprehensive management of cancer care. Its primary functions include facilitating workflows, scheduling, and managing clinical information for patients undergoing oncology treatment and follow-up. The system enables the transfer, storage, conversion, and display of patient data across various oncology disciplines, including radiation therapy, medical oncology, and surgical oncology. RayCare 2.3 is specifically not intended for diagnostic activities but aims to streamline the administrative and clinical processes within an oncology department. It operates as a software-only system with client-server architecture, where the client part allows user interaction and the server handles processing and storage. The system comprises several functionality modules such as patient clinical data management, care administration, clinical notes, workflow and task management, charge capture, scheduling, PACS integration, an image viewer, simulation and imaging support, system administration, security features (authentication, authorization, audit logging), and hospital system integrations. Intended users are various cancer care clinic personnel, including clinical, technical, and administrative staff, with access controlled based on their roles and training. RayCare servers are hosted within the hospital IT environment, and clients operate on the internal hospital network or secure wireless networks. Non-clinical performance data, based on verification and validation against standards like ISO 14971, IEC 61217, IEC 62304, and IEC 62366, indicate the system's safety and effectiveness for its intended use. Notably, RayCare does not include functionality for recording treatment delivery sessions.

AI Regulatory Concerns

Powered byJev by TypeSafe AI

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

Oncology Information SystemWorkflow ManagementClinical Information ManagementPatient Data ManagementRadiation TherapyMedical OncologySurgical OncologySchedulingPACS IntegrationSoftware

Device Metadata

Submission Number
K191384
Company
RaySearch Laboratories AB (publ)
Panel
Radiology
Product Code
N/A
Data Type
Images
Clinical Function
Intervention
AI Function
Analysis
AI Subclass
quantification/feature localization

Relevant Clinical Questions

  • Q1. How does RayCare 2.3 handle data interoperability with existing hospital information systems (HIS) and electronic health records (EHR) beyond basic PACS integration?; What specific security measures are implemented in RayCare 2.3 to ensure patient data confidentiality and integrity, particularly regarding authentication, authorization, and audit logging in a multi-user clinical environment?; Given that RayCare 2.3 does not include functionality for recording treatment delivery sessions, what are the recommended or typical workflows for integrating this system with treatment delivery systems?; What are the limitations or specific configurations required for the "simulation and imaging" module, and how does it support advanced imaging modalities used in modern oncology?; How does the "workflow and task management" module adapt to the varying protocols and specific needs of different oncology clinics, and what level of customization is possible?

Risk Classification

ESL Analysis
FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class C (software safety classification); Authorized before §524B enforcement

Learn how Parasoft automates IEC 62304 compliance testing →

Cybersecurity Evidence

Powered by SBOMator™

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score30/100
SBOM Evidence⚠ Not mentioned in summary
Cyber Risk Assessment✓ Detected in Summary
Postmarket Plan⚠ Not mentioned in summary
§524B ApplicableNo

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials
- Not detected
ML-BOMMachine Learning Bill of Materials
- Not detected
SaaSBOMSoftware-as-a-Service Bill of Materials(server, hosted, network, wireless)
✓ Detected
HBOMHardware Bill of Materials
- Not detected
CBOMCryptography Bill of Materials
- Not detected
VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange
- Not detected
OBOMOperations Bill of Materials(configuration, environment)
✓ Detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of SaaSBOM, OBOM detected in AI-generated device summary.

• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.

• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.

• Not detected in AI-generated device summary: SBOM, ML-BOM, HBOM, CBOM, VDR/VEX. These may be present in the full FDA submission.

Preparing a similar submission?

ESL takes complete ownership of your software evidence work - SBOM & CVE remediation with SBOMator™, static analysis & unit testing with Parasoft, traceability, and full IEC 62304 lifecycle support.

Assess Your Readiness →Or contact ESL directly
RayCare 2.3 - RaySearch Laboratories AB (publ) | ESL FDA AI Device Intelligence