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The MedStar System is intended to transfer patient physiological data from a range of patient monitors to a remote station, such as a Disease Management Center, for subsequent transfer by a Hospital Information System for review by a healthcare professional. The MedStar System is intended for use with any patient requiring Out-of-Hospital monitoring. The MedStar System is not used directly with a patient.

The MedStar Unit is intended for Out-of-Hospital Use. The associated Collection Server is intended for use in a Disease Management Center, Hospital or Hospital-Type facility, Medical Clinic or Physician's Office. The MedStar System is intended for sale by or on the order of a physician only.

The MedStar System is indicated for Out-of-Hospital Use with any patient requiring Out-of-Hospital monitoring The associated Collection Server is intended for use in a Disease Management Center, Hospital or Hospital -Type facility, Medical Clinic or Physician's Office.

The MedStar Monitoring System comprises the MedStar Unit and the associated Collection Server. The MedStar Unit is a portable, battery-operated unit for controlling the transmission of data from a range of compatible patient monitors or measurement devices to a remote monitoring center. Data is transmitted via telephone lines to the associated data collection server at the remote site. The MedStar Unit is contained in a small plastic enclosure with an LCD screen mounted into the top of the case. A User push button control is located adjacent to the display. Four serial communication ports are located at the side of the unit for connection to the serial data ports of specific patient monitors. Two standard phone jacks are also located at the side of the unit for connection to standard phone outlets. Two recessed programming buttons are included on the opposite side of the enclosure to the phone jacks. The Collection Server comprises a Personal Computer-type Processor Unit incorporating an additional electronics board to control phone line transmission to and from the MedStar Unit. The MedStar System accepts serial data from Blood/Glucose Monitors, Weight Scales, and NIBP Monitors. Monitored/measured data is transferred from a patient monitor/measurement device via that unit's serial data port under the control of a serial port protocol. The data is then stored in the MedStar Unit prior to undergoing Dual Tone Multiple Frequency, DTMF, encoding to facilitate phone line transmission to a remote site. A Collection Server receives and decodes the transmitted data and stores the data locally for subsequent transfer by a Hospital Information System for review by a healthcare professional. In addition to transferring encoded data from the three measurement devices described above, EKG data may also be transferred directly from an EKG Monitor to the Collection Server, via phone line, using an EKG Monitor's standard audio data output.

The provided text does not contain detailed information about the acceptance criteria or a study proving the device meets specific acceptance criteria in the format requested. The document is a 510(k) summary and FDA clearance letter for the MedStar System, a "Telephone Electrocardiograph transmitter and receiver."

Here's a breakdown of what can be extracted and what is missing:

The document primarily focuses on establishing substantial equivalence to predicate devices and describing the device's function and intended use. While it mentions "bench testing was conducted to establish the MedStar System's accuracy and performance to specification," it does not provide the specifics of these tests, acceptance criteria, or their results in a quantifiable manner.

Here's a breakdown based on your request, highlighting what's missing:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Sample Size for Test Set: Not specified. The document mentions "bench testing," which implies laboratory-based testing, but does not provide details of the sample size (e.g., number of transmission cycles, number of data points, number of connected devices, length of tests).
• Data Provenance (country of origin, retrospective/prospective): Not specified. Bench testing is typically performed in a controlled laboratory environment.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Number of Experts: Not applicable or not specified. This type of device (data transmission system) would likely rely on technical specifications and objective measurements rather than expert human interpretation for "ground truth" in the way a diagnostic imaging AI would. The "ground truth" for its performance would be whether the transmitted data accurately reflects the input data from the patient monitors.
• Qualifications of Experts: Not applicable or not specified.

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

• Adjudication Method: Not applicable or not specified. Adjudication methods are typically used in studies involving human interpretation (e.g., radiological reads) where there might be disagreement among experts. For a technical data transmission device, performance is typically assessed against a predefined technical standard or the known input data, not through expert consensus adjudication.

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:

• MRMC Study: No. The MedStar System is a data transmission device, not a diagnostic AI or an AI intended to directly assist human readers in interpretation. It facilitates the transfer of physiological data for subsequent review by healthcare professionals, but it does not perform analysis or interpretation itself. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to this device.
• Effect Size of Improvement: Not applicable.

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

• Standalone Performance: Yes, in a sense. The "bench testing" mentioned would assess the device's technical performance (e.g., data transmission accuracy, reliability, compliance with communication protocols) in a standalone capacity. However, the details of these tests are not provided. The device's primary function is to transmit data without human intervention in the transmission process itself.

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

• Type of Ground Truth: The ground truth for this device would be the original, untransmitted physiological data as measured by the connected patient monitors (Blood/Glucose Monitor, Weight Scale, NIBP Monitor, EKG Monitor). The "accuracy" and "performance to specification" would be demonstrated by comparing the data received by the Collection Server to the data originally sent by the patient monitors.

8. The sample size for the training set:

• Training Set Sample Size: Not applicable. The MedStar System is described as a hardware device with embedded software for data handling and transmission. It is not an AI/Machine Learning algorithm that typically requires a "training set" in the context of learning patterns or making predictions. Its functionality is based on established communication protocols and hardware design.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" in the AI/ML sense for this device. Its "performance to specification" would be verified through engineering and bench testing against known, controlled inputs according to its design.

In summary, the provided document is a regulatory submission focused on demonstrating substantial equivalence and describing the device. It lacks the detailed study information, acceptance criteria, and performance metrics typically found in a clinical or analytical validation study report for a diagnostic or AI-driven device.

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