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The ESCORT-LINK™ Central Station Monitor is intended to be used to provide, using a wireless LAN for communication, centralized surveillance and documentation of patient vital sign data and arrhythmia monitoring and alarms for a variable number of ESCORT II bedside monitors and a variable number of UHF telemetry transmitters in the hospital environment. It is intended for use by healthcare practitioners trained in the use of the equipment only.

The ESCORT LINK Central Station Monitor Model 20500 is a Central Station monitor comprised of a standard VGA Display, a standard Personal Computer Base, and an auxiliary base used to mount the Network communications hardware (i.e. Spread Spectrum transponders and UHF telements of the The ESCORT LINK Central Station Monitor Model 20500 can provide the centralized display, storage, and recording (or printing) of patient vital sign and waveform data that is being monitored at ESCORT II 100, 300, or 400 bedside monitors or UHF Telemetry Receivers.

Here's a breakdown of the acceptance criteria and study information for the ESCORT LINK Central Station Monitor Model 20500, based on the provided text:

Acceptance Criteria and Device Performance

The provided 510(k) summary does not explicitly state quantitative acceptance criteria or a direct table comparing them to reported device performance. Instead, it indicates that the device was designed to "functional standards developed by independent and regulatory agencies" and its performance was evaluated against these.

However, based on the "Device Testing" and "Test Conclusions" sections, we can infer the key performance areas that were tested and deemed acceptable:

The document states that the device was shown to be "safe, effective Central Station Monitor" in these areas, and "substantially equivalent" to the predicate device (ESCORT LINK Central Station Monitor Model 3200).

Study Details

The provided document offers limited specific details about the study methodology in the typical research paper format. However, it does provide some insights into the testing conducted:

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not explicitly stated. The document refers to "tests demonstrating consideration of and mitigation of hazards" and "application of system tests, reviews, and product verification and validation studies." This suggests comprehensive system-level testing rather than a specific patient-based test set with a defined sample size.
   • Data Provenance: Not specified. The context implies internal testing by Medical Data Electronics, Inc.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not specified. The document does not mention the use of external experts for establishing ground truth for a test set.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not specified. This level of detail regarding adjudication methods is not present in the document.

4. 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:

   • No. The device described is a central station monitor for vital signs and arrhythmia, not an AI-assisted diagnostic tool for human readers. Therefore, an MRMC comparative effectiveness study involving human readers would not be applicable or expected for this type of device.

5. If a standalone (i.e. algorithm only, without human-in-the-loop performance) was done:

   • Yes, implicitly. The "Device Testing" and "Test Conclusions" sections refer to "performance testing" of the "ESCORT LINK Central Station Monitor Model 20500" itself. This suggests testing the device's inherent functionality (alarm detection, arrhythmia detection, data accuracy) as a standalone system. The central station's role is to display, store, and report data, and its own algorithms for arrhythmia detection are specifically mentioned (Provided by Zymed Inc.).

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Not explicitly stated. Given the nature of the device (monitoring vital signs and arrhythmia), the "ground truth" would likely involve known, controlled physiological signals or simulated data representing various cardiac events and vital sign parameters, allowing for verification of the device's detection and reporting accuracy against these known states. This would likely be established through engineering and physiological standards.

7. The sample size for the training set:

   • Not applicable. The document describes a central monitoring system with specific hardware and software, including a "Zymed Inc." arrhythmia algorithm. It does not indicate that the device's core functionality (especially arrhythmia detection) involved a machine learning model that required a specific "training set" in the modern sense. The "Zymed Inc." algorithm would have been developed and validated by its provider, and its integration into this system would have been tested for proper function.

8. How the ground truth for the training set was established:

   • Not applicable, as a "training set" in the machine learning context is not mentioned or implied for this device.

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