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The Intelli Vue XDS Software is intended for use as an additional, independent display for viewing screens, generated by specified network-connected Philips patient monitors. The IntelliVue XDS Software alone is not intended for remotely monitoring patients without caregivers in vicinity (unattended patients).

It is indicated for local and remote operation of these Philips patient monitors. It is indicated for printing reports as generated by these Philips patient monitors. It is indicated to be used by trained healthcare professionals.

Rx Only: Caution, U.S. Federal Law restricts this device to sale by or on the order of a physician.

The IntelliVue XDS Software (867019) is a bedside information system. The IntelliVue XDS Software provides network services, printing services, patient monitor remote display services, launch pad services, input device sharing services and XDS database services.

The IntelliVue XDS Software can be connected to one or more specified Philips patient monitors and allows the remote viewing of the patient monitor generated data. Depending on the configuration, the remote operation of the network-connected patient monitor with standard off-the shelf information technology equipment input devices (touch screen, keyboard, and mouse) is also supported.

The IntelliVue XDS software does not modify or alter the Philips specified patient monitor. nor does it generate any data on its own. It is solely displaying the patient monitor generated data. It also displays the current alarm and INOP states for the patient, but does not provide an auditory alarm signal announciation function. The IntelliVue XDS Software is not a primary monitoring or alarming device.

The IntelliVue XDS Software is a software only product. It is intended to be installed on customer supplied compatible off-the shelf information technology equipment that meet the technical requirements as specified by Philips.

The provided text describes a 510(k) submission for the Philips IntelliVue XDS Software. It focuses on the substantial equivalence of the modified software (Rev. M.1) to a previously cleared version. However, it does not contain the detailed acceptance criteria and a specific study proving the device meets those criteria, as typically found in a clinical study report.

Here's an analysis based on the information provided, highlighting what is present and what is missing, and making inferences where possible:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of acceptance criteria with corresponding performance metrics. It generally states:

• "Pass/Fail criteria were based on the specifications cleared for the predicate device and all test results showed substantial equivalence."
• "The results demonstrate that the Philips IntelliVue XDS Software (SW Rev.M.1) meets all safety and reliability requirements and performance claims."

This indicates that the acceptance criteria were likely related to maintaining the functionality, safety, and reliability of the predicate device. Specific performance metrics (e.g., accuracy, latency, resolution) are not detailed.

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

The document states:

• "Testing involved software testing on integration level (functional testing and regression testing) and software testing on system level (hazard analysis testing and dedicated software performance testing)."

This refers to software engineering testing rather than a clinical study with a "test set" of patient data. Therefore, the concept of sample size for a test set of patient data and data provenance (country of origin, retrospective/prospective) is not applicable to the type of testing described. The testing focused on the software itself rather than its performance on a dataset of patient cases.

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

As the testing described is not a clinical study on patient data but rather software verification and validation, there is no mention of experts establishing ground truth for a test set in the context of medical image or signal interpretation.

4. Adjudication Method

Given the nature of the testing described (software verification and validation), an adjudication method (like 2+1 or 3+1) for a test set is not applicable.

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

An MRMC study compares human reader performance with and without AI assistance. The provided document describes software that acts as an "additional, independent display" and allows "remote operation" of patient monitors. It explicitly states:

• "The IntelliVue XDS Software alone is not intended for remotely monitoring patients without caregivers in vicinity (unattended patients)."
• "The IntelliVue XDS Software is not a primary monitoring or alarming device."

This indicates the device is an accessory display/control system, not an AI interpreting data or aiding human readers in diagnosis. Therefore, an MRMC comparative effectiveness study is not applicable and was not performed.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The described device is software that displays and allows remote operation of patient monitor data. It "does not modify or alter the Philips specified patient monitor, nor does it generate any data on its own." It "solely displays the patient monitor generated data."

While software verification and validation were performed on the algorithm itself, this is not a "standalone performance study" in the sense of an AI algorithm producing diagnostic outputs without human intervention. The software's function is to mirror existing monitor data and enable control, not to independently interpret or diagnose.

7. Type of Ground Truth Used

For the software verification and validation, the "ground truth" would be the expected functional behavior and performance defined by the software's specifications and the predicate device's characteristics. It is not based on expert consensus, pathology, or outcomes data related to patient conditions.

8. Sample Size for the Training Set

The document pertains to the verification and validation of a software application for displaying and interacting with patient monitor data, not an AI/ML algorithm that is "trained" on a dataset. Therefore, there is no concept of a "training set" as understood in AI/ML, and thus no sample size for a training set is provided or applicable.

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

As there is no training set for an AI/ML algorithm, this question is not applicable.

Summary of what is present and missing:

• Acceptance Criteria/Performance: General statements about meeting safety, reliability, and performance claims, and substantial equivalence to the predicate device. Specific quantitative criteria are not provided.
• Study Details (Test Set, Experts, Adjudication, MRMC, Standalone, Ground Truth): Not applicable or not performed in the context of a clinical study or AI performance evaluation, as the device is a display/control software, not an AI diagnostic tool.
• Training Set: Not applicable, as the device is not an AI/ML algorithm that requires training.

The provided document describes a software verification and validation process to ensure the new software version maintains the same functionality, safety, and performance as its predicate, rather than a clinical study to establish new performance claims against a defined ground truth for medical interpretation.

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