(71 days)
The IntelliBridge System is indicated for use in the data collection and clinical information management. The IntelliBridge System is not intended for monitoring purposes nor is the device intended to control any of the clinical devices (independent bedside devices / information systems) it is connected to.
The name of the subject device is the Philips IntelliBridge System. The trade name of the device is the Philips IntelliBridge System. The common usual name is data management system.
The Philips IntelliBridge System is a data management system that collects and manages clinical information from independent bedside devices. The provided 510(k) summary (K093177) does not contain detailed information about specific acceptance criteria and a study demonstrating the device's performance against these criteria in a quantitative manner that would be expected for an AI/ML medical device.
The document indicates that the device has the same intended use and fundamental technological characteristics as its predicate device (Philips DeviceLink System). The testing involved "system level tests, performance tests, and safety testing from hazard analysis." The pass/fail criteria were "based on the specifications cleared for the predicate device, the specifications of the subject device." The conclusion was that the device "meets all reliability requirements and performance claims and supports a determination of substantial equivalence."
Given the information provided, it is not possible to fill out the table with specific quantitative acceptance criteria or detailed study parameters typical for AI/ML device evaluations. The device appears to be a data integration and management system, not one that uses AI/ML for diagnostic or prognostic purposes, and thus the evaluation methods would be different.
Therefore, the following information is based only on the details explicitly stated in the provided text, and many sections will indicate "Not specified" or "Not applicable" due to the nature of the device and the content of the 510(k) summary.
1. Table of acceptance criteria and the reported device performance
| Acceptance Criteria Category | Specific Acceptance Criteria | Reported Device Performance |
|---|---|---|
| System Functionality | Meets "all reliability requirements" | "meets all reliability requirements" |
| Performance Claims | Meets "performance claims" | "meets... performance claims" |
| Safety | Passes "safety testing from hazard analysis" | Test results "showed substantial equivalence" and "meets all reliability requirements and performance claims" |
| Substantial Equivalence | Based on specifications of predicate device and subject device | "supports a determination of substantial equivalence" |
2. Sample size used for the test set and the data provenance
- Sample size for test set: Not specified. The document globally refers to "system level tests, performance tests, and safety testing."
- Data provenance: Not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of experts: Not applicable/Not specified. The device is a data management system; it does not generate diagnostic or prognostic outputs that would typically require expert-established ground truth in the way an AI/ML diagnostic tool would.
- Qualifications of experts: Not applicable/Not specified.
4. Adjudication method for the test set
- Adjudication method: Not applicable/Not specified. The testing described appears to be functional, system-level, and safety testing, not clinical performance testing requiring adjudication of interpretations.
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 done: No. This type of study is typically for AI/ML-driven diagnostic devices. The Philips IntelliBridge System is a data management system and does not involve human readers interpreting data enhanced by AI.
- Effect size of improvement: Not applicable.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone study done: Not applicable/Not specified in the context of an AI algorithm. The device, being a data management system, likely underwent extensive standalone functional and integration testing to ensure it correctly collects, transmits, and manages data, but this is not an "algorithm only" performance evaluation in the AI sense.
7. The type of ground truth used
- Type of ground truth: Not applicable. For a data management system, "ground truth" would relate to the accurate and timely transfer and storage of data according to specified protocols and system requirements, rather than a clinical outcome or expert judgment on an image/signal. The pass/fail criteria were "based on the specifications cleared for the predicate device, the specifications of the subject device."
8. The sample size for the training set
- Sample size for training set: Not applicable. This device is not an AI/ML product developed using a training set.
9. How the ground truth for the training set was established
- How ground truth was established: Not applicable. This device is not an AI/ML product developed using a training set.
§ 870.2300 Cardiac monitor (including cardiotachometer and rate alarm).
(a)
Identification. A cardiac monitor (including cardiotachometer and rate alarm) is a device used to measure the heart rate from an analog signal produced by an electrocardiograph, vectorcardiograph, or blood pressure monitor. This device may sound an alarm when the heart rate falls outside preset upper and lower limits.(b)
Classification. Class II (performance standards).