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510(k) Data Aggregation

    K Number
    K014094
    Date Cleared
    2002-01-11

    (30 days)

    Product Code
    Regulation Number
    884.2740
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The intended use of the WatchChild™ Obstetrical Patient Data Management System is a complete Obstetrical Information System which has the ability to record, store, and display data from fetal monitors and maternal vital signs monitors, and manages patient information from the initial fetal stress tests through post delivery discharge. Information from the system organizes clinical data, which would normally be provided on paper records or other clinical systems and devices. This system serves as a decision support tool as well as an electronic medical record. This device is intended for use in a hospital/clinical environment.

    Device Description

    The WatchChild™ Obstetrical Patient Data Management System (The WatchChild™ System) is a complete Obstetrical Information Management System that has the capability to record, store, and display fetal and maternal data from initial fetal stress tests through labor, delivery and discharge. Specifically, data from fetal monitoring and maternal vital signs monitoring equipment can be recorded, stored, and displayed on the WatchChild System via automation of the following areas:

    • . Admission/Discharge/Transfer (ADT)
    • Labor and Delivery notes ●
    • Nursing notes ●
    • Physician's notes .
    • Fetal Strip faxing ●
    • r etail Obstetrical trend reports (e.g., patient enrollments and discharges over . time)
      The WatchChild™ System has the ability to simultaneously display graphic and text The Viatenonilia - Oystem has the clinician to view a patient's fetal strip along with her medical data. Interaction with the WatchChild™ System is accomplished with her modiour data. Interface (GUI). The user activates buttons on the screen through a graphiodi ason internationse. The WatchChild™ System is offered with an utilizing entrer a light pon of a modeo. WORM technology) that replaces conventional paper storage. In addition, an optional physician's remote access is also available. paper storage. In addition, a physician can call from outside the hospital and display real time and/or trended data for any patient connected to the system, as well as perform annotations to the patient's fetal strip.
      The WatchChild™ System can be installed as a stand-alone system or connected to the Hospital's Information System.
    AI/ML Overview

    The information provided indicates that no clinical testing was performed or deemed applicable for the Hill-Rom Manufacturing, Inc. The WatchChild™ System (K014094). The submission focused on demonstrating substantial equivalence to a predicate device through nonclinical testing, primarily software verification and validation. Therefore, an acceptance criteria table, details on sample sizes, ground truth establishment, expert involvement, and MRMC studies are not available, as they are typically associated with clinical performance evaluations.

    Here's a breakdown of the requested information based on the provided text:


    1. Table of Acceptance Criteria and Reported Device Performance:

    Not applicable. The provided document explicitly states, "Clinical testing is not applicable for this device." The submission is for substantial equivalence based on technological characteristics and nonclinical software verification. Therefore, no clinical performance metrics or acceptance criteria are reported.


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

    Not applicable for clinical efficacy. The "testing" mentioned refers to nonclinical software verification and validation. Details on the sample size for this nonclinical testing are not provided, nor is information on data provenance from a clinical context.


    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

    Not applicable. No clinical testing involving expert-established ground truth was conducted.


    4. Adjudication Method for the Test Set:

    Not applicable. No clinical testing with an adjudication method was performed.


    5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

    Not applicable. No MRMC comparative effectiveness study was conducted. The device is an Obstetrical Patient Data Management System, not designed for AI-assisted image interpretation by human readers.


    6. If a Standalone (i.e. algorithm only without human-in-the loop performance) was done:

    The device is an "Obstetrical Patient Data Management System" which records, stores, and displays fetal and maternal data. It is a system intended to manage and organize clinical data, rather than a standalone algorithm making diagnostic decisions. Its performance demonstration was through nonclinical software verification and validation, ensuring its functionality as a data management system. Therefore, a standalone "algorithm only" performance study in the typical sense (e.g., for diagnostic accuracy) was not performed.


    7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.):

    Not applicable for clinical efficacy. The "ground truth" for the nonclinical software verification and validation would relate to expected software behavior, functional correctness, and data integrity, rather than medical ground truth like pathology or expert consensus on clinical outcomes.


    8. The Sample Size for the Training Set:

    Not applicable. This device is an Obstetrical Patient Data Management System. There is no indication of machine learning or AI components that would require a "training set" in the context of diagnostic algorithm development. The testing focused on software verification and validation.


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

    Not applicable. As no training set for an AI/ML algorithm was mentioned, the method for establishing its ground truth is irrelevant.

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