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The IDM100 for use by clinicians and patients to collect, store, and transmit general patient health information and patient vital signs data between the patient and a health care professional. The IDM100 is intended for use on neonate (up to 28 days), pediatric (29 days to 12 years), adolescent (>12 years &

The IDM100 is an integrated medical tablet with diagnostic equipment and secure HIPAA-compliant video conferencing capability facilitating Virtual Exam Rooms (VER) between patients and care providers anywhere. It captures patient vital signs and cardiopulmonary information with clinical accuracy. The IDM100 syncs the data seamlessly with electronic medical records (EMR) providing real-time access for all stakeholders in the continuum of care. The IDM100 transmist the the patient data over a secure internet connection.

The provided document is a 510(k) Summary for the IDM100 device. While it describes various tests performed for safety and effectiveness, it does not clearly present specific acceptance criteria in a table format for performance metrics or a detailed study proving the device meets these criteria in the way typically expected for a detailed clinical performance study report.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (Tempus IC2, K152124) by comparing indications for use, technological characteristics, and by performing various verification and validation tests against recognized standards.

Here's an attempt to extract and synthesize the requested information based on the provided text, highlighting where information is not explicitly available:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are generally implied by conformity to specific standards and satisfactory results from various tests, rather than explicit numerical thresholds given in a table. The document focuses on demonstrating that the IDM100's components meet established standards for similar devices or that its overall performance is comparable to a predicate device.

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

• ECG Clinical Testing:
  • Sample Size: "18 normal and abnormal ECG patients" were compared for the 12-lead ECG function.
  • Data Provenance: Not specified (e.g., country of origin). It's described as a "clinical evaluation," suggesting prospective data collection for this specific comparison, but this is not explicitly stated.
• Other Tests (e.g., Low Perfusion, Tympanic Thermometer, NIBP): Sample sizes are not mentioned. These appear to be bench or lab-based tests rather than patient studies.

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

• ECG Clinical Testing: The document states that the IDM100 and the Welch Allyn CP150 (predicate) "provide comparable testing result, with no impact to the interpretation of the patients ECG." This implies that the interpretation was assessed, likely by experts, but the number and specific qualifications of these experts are not provided.
• Other Tests: Ground truth for these tests would typically be established by calibrated instruments or reference standards, not human experts in the conventional sense.

4. Adjudication Method for the Test Set

• ECG Clinical Testing: An explicit adjudication method (e.g., 2+1, 3+1) is not described. The statement "no impact to the interpretation of the patients ECG" suggests an expert review or comparison, but the process is not detailed.
• Other Tests: Adjudication methods are not applicable for these types of technical compliance tests.

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

• A formal MRMC comparative effectiveness study, comparing human readers with AI assistance versus human readers without AI assistance, was not mentioned or described in this document. The device itself is a vital signs monitor and data collection system, not an AI interpretation device that assists human readers in diagnostic tasks.

6. Standalone (Algorithm Only) Performance Study

• This device is not an algorithm that provides standalone diagnostic interpretations; it's a medical tablet integrating various diagnostic tools. Therefore, a standalone algorithm performance study, as typically understood for AI/ML devices, was not performed or described. The components (e.g., ECG, NIBP, SpO2) within the IDM100 undergo their own performance evaluations against standards, which implicitly represent their "standalone" capability. The statement "Passing IEC 60601-02-25 confirms the safety and accuracy for IDM100 12-lead and 3-lead IDM ECG testing" relates to the standalone performance of the ECG module.

7. Type of Ground Truth Used

• ECG Clinical Testing: The ground truth for the "normal and abnormal ECG patients" is implicitly their clinical presentation/diagnosis as determined by standard clinical practice and the predicate device's output, which the IDM100 was compared against. It's a comparison to a predicate device's output and clinical interpretation, rather than de novo gold standard like pathology or long-term outcomes.
• Other Tests (e.g., Tympanic Thermometer, NIBP): The ground truth for these tests comes from calibrated reference standards as defined by the respective international standards (e.g., EN1060-3 for NIBP).

8. Sample Size for the Training Set

• This document describes a medical device integrating existing, FDA-cleared diagnostic components and a tablet interface for data collection and transmission. It does not mention the use of a machine learning or AI algorithm that would require a distinct "training set" for an AI model.

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

• As the document does not describe the use of a machine learning or AI algorithm requiring a training set, this question is not applicable.

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The monitors are indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. The monitors are intended to be used for monitoring and recording of, and to generate alarms for, multiple physiological parameters of adults, pediatrics, and neonates. The monitors are intended for use by trained healthcare professionals in a hospital environment. The MP5 and MP5SC monitors are also intended for use during patient transport inside the hospital environment; only the MP5 monitor is for use during patient transport outside of the hospital environment. The MP5 and MP5SC when used with the TRx4841A/TRx4851A IntelliVue Telemetry System Transceiver or with the IntelliVue Cableless Measurement Devices, are intended for use in a hospital environment and during patient transport inside the hospital environment. The monitors are only for use on one patient at a time. They are not intended for home use. Not therapeutic devices. The monitors are for prescription use only. The ECG measurement is intended to be used for diagnostic recording of rhythm and detailed morphology of complex cardiac complexes (according to AAMI EC 11). ST segment monitoring is intended for use with adult patients only and is not clinically validated for use with neonatal and pediatric patients. The Predictive Temperature measurement is intended for use with adult and pediatric patients in a hospital environment. The SSC Sepsis Protocol, in the Protocol Watch clinical decision support tool, is intended for use with adult patients only. The Integrated Pulmonary Index (IPI) is intended for use with adult and pediatric (1 to 12 years) patients only. The IPI is an adjunct to and not intended to replace vital sign monitoring. The derived measurement Pulse Pressure Variation (PPV) is intended for use with sedated patients receiving controlled mechanical ventilation and mainly free from cardiac arrhythmia. The PPV measurement has been validated only for adult patients.

The Philips IntelliVue Patient Monitor family comprises the multi-parameter patient monitor models: IntelliVue Patient Monitors MP5 and MP5SC, that consist of display units including built-in and central processing units (CPU) and physiological measurements. All monitors share the same system architecture and exactly the same software is executed on each monitor. The IntelliVue Patient Monitors measure multiple physiological parameters such as surface ECG, invasive and non-invasive etc., generate alarms, record physiological pressure, signals, store derived data, and communicate derived data and alarms to central stations via the IntelliVue Clinical Network. The subject modification introduces the optional The Philips Tympanic Temperature Module (866149) for the IntelliVue Patient Monitors MP5 and MP5SC. This Tympanic Temperature extends the capability of the IntelliVue Patient Module Monitors MP5 and MP5SC to interface the Genius™ 2 Tympanic Temperature Probe (cleared by Covidien, K060649). Additionally the software revision J.21 is made available for the IntelliVue Patient Monitors MP5 and MP5SC.

The provided text is a 510(k) summary for a patient monitor and mainly focuses on showing substantial equivalence to previously cleared devices. It does not contain the kind of detailed study information (like sample sizes for test and training sets, data provenance, expert qualifications, ground truth establishment, or specific performance metrics with acceptance criteria) that would typically be associated with performance studies for AI/ML devices.

The document discusses "Verification & Validation Activities" but these primarily reference compliance with general safety and EMC standards (IEC 60601-1-2 and IEC 60601-1), environmental testing, and software functionality testing. These tests confirm the device works safely and to specifications, but they don't involve the kind of performance metrics against ground truth that your questions imply for AI/ML models.

The "acceptance criteria" discussed are largely implicit: that the device works safely, effectively, and correctly in accordance with specifications and labeling claims, and that all applicable requirements of the standards are met. "Reported device performance" is also general, stating it "worked safely and according to their specifications" and "met all reliability requirements and performance claims."

Therefore, based on the provided text, I cannot complete the requested tables and information for most of your points. This document is a regulatory submission for a patient monitor with an added temperature module and software update, not a clinical performance study for an AI/ML diagnostic or prognostic device.

If this were a document for an AI/ML device, the detailed information you requested would be crucial. Since it's not, I can only address what is present in the text.

Here's an attempt to answer the questions based only on the provided text, with many fields explicitly stated as "Not Applicable" or "Not Provided" due to the nature of the document:

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 provided. The document describes engineering and system-level verification and validation, not a clinical trial with a "test set" in the context of AI/ML performance evaluation.
• Data Provenance (country of origin, retrospective/prospective): Not provided.

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)

• Not applicable. The "ground truth" for this monitoring device is its adherence to technical specifications, safety standards, and functional claims, not expert-labeled clinical data.

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

• Not applicable. No expert adjudication process is described.

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

• Not applicable. This is not an AI/ML diagnostic or prognostic device, and no MRMC study is mentioned.

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

• Not applicable. This is a patient monitor, not an algorithm being evaluated for standalone performance in the context of AI/ML. Its performance is inherent in its operation (e.g., accuracy of parameter measurement, alarm functionality).

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

• The "ground truth" for this device appears to be defined by its engineering specifications, adherence to recognized consensus standards (like IEC 60601), and functional requirements for safety and effectiveness.

8. The sample size for the training set

• Not applicable. This document does not describe an AI/ML model that requires a training set.

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

• Not applicable. This document does not describe an AI/ML model or a training set.

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