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510(k) Data Aggregation

    K Number
    K030575
    Date Cleared
    2003-03-21

    (25 days)

    Product Code
    Regulation Number
    870.1025
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MODIFICATION TO SOLAR 9500 INFORMATION MONITOR

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Solar® 9500 Information Monitoring System is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients, in high acuity areas such as operating room (OR), post anesthesia recovery (PARR), critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care. Physiologic data includes electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, anesthetic gas concentrations and mixed venous oxygen saturation, as summarized in the Solar® 9500 Operator's Manual.

    The Solar® 9500 Information Monitoring System is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital INTRAnet data via a Web Browser at the point-of-care.

    This information can be displayed, trended, stored, and printed.

    Device Description

    The Solar 9500 is a patient monitoring system that is designed to display patient physiological data that is received from the GE Medical Systems' Tram-net network and individual and multi-parameter data acquisition modules.

    The Solar 9500 Information Monitoring System is comprised of four basic components: the processing unit, color display, Tram modules(s), and Tram-rac housing. Optional components include a remote display.

    The Solar 9500 utilizes the GE Medical System's Unity Ethernet LAN allowing communication with monitoring, clinical information and cardiology products. An additional Ethernet connection is provided for connection to the hospital Enterprise Network. The Enterprise network connection allows the user access to the hospital INTRAnet, through an embedded Web Browser on the Solar 9500. This web browsing capability enables the user to log on to the hospital INTRAnet directly from the monitor allowing access to information such as patient history, up-to-the-minute lab results and cath reports. Data can also be accessed from non-GE platforms via the Enterprise network.

    The Solar 9500 system was developed to interface with third party peripheral devices that support serial and/or analog data outputs.

    AI/ML Overview

    The provided 510(k) summary for the Solar 9500 Information Monitor does not contain information regarding specific acceptance criteria for performance benchmarks or a detailed study proving the device meets those criteria. The document focuses on demonstrating substantial equivalence to a predicate device based on similar technology and general compliance with voluntary standards and internal quality assurance measures.

    Therefore, most of the requested information cannot be extracted directly from the provided text.

    Here is a summary of what information is explicitly stated or can be inferred:


    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance CriteriaReported Device Performance
    Not explicitly stated in terms of quantitative metrics or specific performance thresholds.The document states: "The results of these measurements demonstrated that the Solar 9500 is as safe, as effective, and performs as well as the predicate devices." This is a qualitative statement of performance relative to the predicate, rather than precise metrics.

    2. Sample Size Used for the Test Set and Data Provenance

    • Sample Size for Test Set: Not specified.
    • Data Provenance (e.g., country of origin, retrospective/prospective): Not specified. The document mentions "Software and hardware testing," "Safety testing," and "Environmental testing" but does not detail the nature of these tests, including the data used.

    3. Number of Experts Used to Establish Ground Truth and Qualifications

    • Number of Experts: Not specified.
    • Qualifications of Experts: Not specified.

    4. Adjudication Method for the Test Set

    • Adjudication Method: Not specified.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    • MRMC Study Done: No. The provided information does not describe any MRMC studies or a comparison of human reader performance with or without AI assistance. The device is a patient monitor, not an AI-assisted diagnostic tool in the sense of image analysis.

    6. Standalone (Algorithm Only) Performance Study

    • Standalone Study Done: The document describes "Software and hardware testing" and "Final validation," implying standalone testing of the device's functions. However, specific performance metrics for an "algorithm only" component (like a specific arrhythmia detection algorithm's sensitivity/specificity) are not provided. The device as a whole is tested, which inherently includes its algorithms.

    7. Type of Ground Truth Used

    • Type of Ground Truth: Not specified in detail. The testing mentioned ("Safety testing," "Environmental testing," "Software and hardware testing," "Final validation") typically involves comparing device outputs to known inputs or reference standards, but how the "ground truth" for specific physiological parameters or arrhythmia detection was established is not detailed. For a patient monitor, this would typically involve calibrated measurement devices or expert interpretation of physiological signals.

    8. Sample Size for the Training Set

    • Sample Size for Training Set: Not applicable/not specified. The document describes a patient monitoring system, which typically uses established algorithms and signal processing techniques rather than a "training set" in the machine learning sense from a specific dataset. Device development involves engineering, testing against specifications, and validation, not necessarily a machine learning training phase on a large dataset.

    9. How the Ground Truth for the Training Set Was Established

    • Ground Truth for Training Set: Not applicable/not specified, as there is no mention of a traditional machine learning "training set."

    Summary of Device Rationale and Testing:

    The 510(k) summary for the Solar 9500 Information Monitor relies on demonstrating substantial equivalence to a predicate device (K990068, also a Solar 9500 Information Monitor from GE Medical Systems).
    The "Test Summary" section states that the device complies with voluntary standards (as detailed in Section 9, which is not provided here) and that the following quality assurance measures were applied:

    • Requirements specification review
    • Code inspections
    • Software and hardware testing
    • Safety testing
    • Environmental testing
    • Final validation

    The conclusion is that these measures "demonstrated that the Solar 9500 is as safe, as effective, and performs as well as the predicate devices." This indicates that the primary "study" proving performance is the comparison to the predicate device and adherence to internal quality assurance processes and relevant voluntary standards. There are no specific quantitative acceptance criteria or detailed performance studies presented in this summary document beyond this qualitative statement of equivalence.

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