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The Efficia CMS200 central monitoring system is intended for use by healthcare professionals for central viewing of physiologic waves, parameters, and trends from other networked medical devices (patient monitors and vital signs monitors) for multiple patients. It provides secondary operator notification of alarms from other networked medical devices. It provides for the retrospective review of alarm conditions, physiologic waves and parameters from multiple patients. The intended use of the printer, when present, is to provide hardcopy text, graphics, and wave data. The Efficia CMS200 may provide for connection and information exchange to external systems. The Efficia CMS200 is intended for use in hospitals and out-of-hospital patient care settings (such as clinics, outpatient surgery facilities, long-term care facilities and physician offices) in which care is administered by healthcare professionals.

The subject Efficia CMS200 Central Monitoring System is comprised of medical device software, model S863352, which is installed on a PC platform. The subject Efficia CMS200 includes S863352, the PC and peripherals. The Efficia CMS200 software is not marketed separately.

The subject Philips Efficia CMS200 Central Monitoring System is a central station. It provides continuous remote monitoring of up to 32 beds. It obtains data from networked patient monitors and provides centralized viewing of waveric data and alarms from all the connected beds. It is providing secondary alarm notification. It allows for retrospective data review. It can transfer data to an electronic medical record system (EMR).

Here's a breakdown of the acceptance criteria and study information for the Philips Efficia CMS200 Central Monitoring System, based on the provided document:

1. Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria for performance metrics (e.g., specific accuracy rates, sensitivity, specificity, or error margins) with corresponding reported device performance values. Instead, it relies on demonstrating substantial equivalence to a predicate device and compliance with relevant standards.

The "Performance Data" section indicates that:

• "Performance data supports that the subject device performances to the same level of performance as the predicate device."
• "The clinical preference testing supports that the customer requirements are met."
• The device is in compliance with various international standards (IEC 62304, IEC 62366, IEC 60601 series, ISO 80601 series, ANSI/AAMI EC-13).

Therefore, the acceptance criteria are implicitly tied to meeting the same performance level as the predicate device (Philips SureSigns Central K131032) and compliance with relevant safety and performance standards. The "reported device performance" is that it meets these criteria.

2. Sample Size for Test Set and Data Provenance

• Test Set Sample Size: The document mentions a "clinical user preference study" but does not specify the sample size (number of users or cases) involved in this study.
• Data Provenance: Not explicitly stated, but the device is marketed in various countries, suggesting a broader provenance. The document indicates that for countries where the Efficia CMS200 is already marketed, there have been no reported adverse events. This implies some form of real-world use data contributes to the assessment, but it's not a formal "test set" in the context of a controlled study.

3. Number of Experts and Qualifications for Ground Truth (Test Set)

The document does not detail the use of experts to establish ground truth for a quantitative test set in the traditional sense (e.g., for diagnostic accuracy). The "clinical user preference study" involved "users" or "healthcare professionals," but their specific qualifications or number are not provided for establishing "ground truth," as this study was more focused on user acceptance and identifying enhancement requests rather than diagnostic accuracy.

4. Adjudication Method (Test Set)

Not applicable, as a formal quantitative test set requiring adjudication of diagnostic outcomes is not described in the provided document. The clinical user preference study was likely qualitative feedback.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not done or at least not described in this document. The device is a central monitoring system for displaying physiological data and alarms, not an AI-powered diagnostic tool for interpretation. The "AI" component (if any in the context of this document) would be in the algorithms for processing physiological data, which are not detailed as AI in the modern sense.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study of the algorithm without human-in-the-loop performance is not explicitly described in terms of specific performance metrics (e.g., accuracy of alarm detection). However, the document states:

• "Performance data supports that the subject device performances to the same level of performance as the predicate device."
• It complies with various IEC and ISO standards that likely include requirements for the standalone performance of physiological monitoring systems.

The core technology (S863352 software) is assessed for compliance with standards applicable to medical device software (IEC 62304) and usability (IEC 62366), and its ability to meet system requirements when connected to compatible patient monitors (IEC 60601 series, ISO 80601 series, ANSI/AAMI EC-13). This implies that the software's functional performance itself was evaluated to ensure it operates correctly in a standalone context, though specific performance metrics are not given.

7. Type of Ground Truth Used

• For demonstrating substantial equivalence: The primary "ground truth" or reference point for establishing the device's acceptability is the predicate device (Philips SureSigns Central K131032). The document extensively compares the functionalities, software, hardware, and performance against this predicate to assert substantial equivalence.
• For compliance: Compliance with various international standards (IEC, ISO, ANSI/AAMI) serves as a ground truth for safety, effectiveness, and performance.
• For the clinical user preference study: "Customer requirements" and "enhancement requests" from healthcare professionals served as the qualitative ground truth for user acceptance.
• For the "no adverse events" claim: Real-world outcomes data (absence of reported adverse events) from countries where the device is already marketed functions as a form of ground truth for safety.

8. Sample Size for Training Set

The document is a 510(k) submission for a central monitoring system, which is a re-branding and enhancement of an existing product. It does not describe an "AI algorithm" in the modern sense that would require a distinct "training set" for machine learning. Therefore, a sample size for a training set is not applicable as described in this document. The software development process likely involved traditional verification and validation on various test cases, but these are not referred to as a "training set."

9. How Ground Truth for Training Set Was Established

As noted above, the concept of a "training set" for AI is not applicable here. The "ground truth" for the software's functionality and performance would have been established through a combination of:

• Engineering specifications and requirements: Defining how the system should operate.
• Predicate device's established performance: The SureSigns Central's proven functionality and safety.
• Relevant regulatory standards: Defining required performance characteristics (e.g., alarm accuracy, data display integrity).
• Clinical validation related to patient monitors: The linked patient monitors (e.g., SureSigns VM Series, Efficia CM Series) would have their own established performance and accuracy for physiological measurements, which the CMS200 then displays and processes.

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The SureSigns VS3 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSignsVS3 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The SureSigns VS4 vital signs monitor is for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The SureSigns VS4 is for monitoring, recording and alarming of multiple physiological parameters in healthcare environments for patient types listed below. Additionally, the monitor may be used in transport situations within a healthcare facility.

The subject devices are multi-parameter patient monitors, specifically the SureSigns VS3 and SureSigns VS4. Modifications to the VS4 include the addition of CO2, SpHb, Respiratory Rate RRa, and Masimo SpO2 measurements. Both VS3 and VS4 have the QuickNBP mode added.

This is a 510(k) summary for Philips SureSigns VS3 and VS4 vital signs monitors, describing modifications to add additional measurement capabilities. The provided text, however, does not contain information about specific acceptance criteria or a detailed study proving the device meets said acceptance criteria with numerical performance data. It broadly states that "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the subject device. Testing involved system level tests, performance tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the subject device and test results showed substantial equivalence."

Therefore, I cannot fulfill all parts of your request with the provided information.

However, based on the information available, here's what can be extracted:

• Acceptance Criteria and Reported Device Performance: This information is not explicitly provided in a table or numerical format. The document states that "Pass/Fail criteria were based on the specifications cleared for the subject device and test results showed substantial equivalence," implying that the devices met pre-defined specifications. However, the exact criteria and corresponding performance metrics are not detailed.

• Sample Size for Test Set and Data Provenance: This information is not explicitly stated in the provided text.

• Number of Experts and Qualifications: This information is not mentioned in the provided text.

• Adjudication Method: This information is not mentioned in the provided text.

• Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: There is no indication that an MRMC study was done. The device is a vital signs monitor, which typically involves direct measurement rather than interpretation by multiple human readers in the way an AI-assisted diagnostic tool might.

• Standalone (Algorithm Only) Performance Study: The document mentions that the new features are achieved by using OEM modules that are "FDA cleared under Kxxxxxx." This implies that the performance of these modules as standalone components was already established in their respective clearances. For instance, for CO2 measurement, the Oridion microMediCO2 OEM module was cleared under K094012; for SpHb, RRa, and Masimo SpO2, the Masimo Rainbow SET Radical 7R CO-Oximeter was cleared under K100428; and for Temporal Temperature, the Exergen TemporalScanner Thermometer was cleared under K011291. The QuickNBP mode is described as based on the "same algorithm that provides the regular NBP measurements" in the existing devices. Therefore, while not explicitly called a "standalone study," the reliance on previously cleared, established technologies suggests that their standalone performance has been demonstrated.

• Type of Ground Truth Used: Not explicitly stated for the overall device's performance. However, for the OEM modules incorporated, their original clearances would have involved appropriate ground truth methods for each physiological parameter (e.g., direct measurement for temperature, arterial blood gas analysis for SpO2 calibration, etc.).

• Sample Size for Training Set: This information is not applicable as the document describes hardware modifications incorporating existing, cleared OEM modules and leveraging existing algorithms. It does not mention the development or training of new algorithms that would require a distinct training set.

• How Ground Truth for Training Set Was Established: Not applicable given the nature of the device modifications.

In summary, the provided text primarily focuses on the substantial equivalence argument for modifications to existing vital signs monitors by integrating previously cleared OEM modules and leveraging existing algorithms. It does not contain the detailed performance study information with specific acceptance criteria, sample sizes, expert involvement, or adjudication methods that your request entails for a newly developed AI/diagnostic device.

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