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The DASH 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, inter-hospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and prehospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The DASH 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The DASH 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The DASH 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12 lead ECG analysis (12SL). Additionally, the network interface allows for the display and transfer of network available patient data.

The provided text is a 510(k) summary for the GE DASH 3000/4000 Patient Monitor. It does not contain specific acceptance criteria or a detailed study section with reported device performance metrics against those criteria.

Instead, it outlines the device's intended use, technological equivalence to predicate devices, and a high-level summary of tests and standards it complies with. It concludes with a general statement about safety and effectiveness.

Therefore, I cannot populate the requested table or provide detailed information for many of the questions based on the provided text.

Here is what can be inferred or stated based on the text, with limitations noted:

1. A table of acceptance criteria and the reported device performance:

Limitations: The document only states compliance with these standards and general equivalence. It does not provide specific numerical performance metrics (e.g., accuracy, precision, sensitivity, specificity, or specific error ranges) for each physiological parameter that would typically define "acceptance criteria" in a detailed study.

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

• Not provided. The document mentions "Software and hardware testing," "Safety testing," "Environmental testing," and "Final validation" but gives no details on sample sizes, types of data (e.g., clinical, simulated), or provenance.

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/Not provided. This device is a patient monitor, not an AI/imaging device requiring expert interpretation for ground truth. The "ground truth" for a patient monitor would typically be established by comparing its measurements to established reference standards or other calibrated devices. The document does not detail this process.

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

• Not applicable/Not provided. Adjudication methods are typically used in studies involving human interpretation (e.g., radiologists) where there might be disagreement in assessments. For a patient monitor, performance is usually assessed against objective, measurable standards.

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

• No. This is a patient monitor, not an AI-assisted diagnostic tool that would typically involve a multi-reader multi-case study comparing human performance with and without AI.

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

• Not applicable/Not provided in the context of an "algorithm only" AI device. The device is a physiological monitor; its performance is inherently standalone in terms of measuring vital signs. The summary describes general testing and compliance with standards, implying the device's functions work as intended, but doesn't detail standalone algorithmic performance in the way it would for an AI-driven image analysis tool.

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

• Not specified, but inferred to be reference standards or calibrated measurement devices. For physiological monitors, ground truth for parameters like ECG, blood pressure, temperature, etc., is typically established by using highly accurate and calibrated reference instruments or simulated physiological signals that mimic real-world conditions. The document does not describe the specific ground truth methods.

8. The sample size for the training set

• Not applicable. This device precedes the era where "training sets" for deep learning models were a standard part of medical device submissions. It appears to be a traditional hardware and software medical device, not an AI/machine learning product. Therefore, there is no "training set" in the modern sense.

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

• Not applicable. As a traditional device, there is no "training set" (as understood in machine learning) or associated ground truth establishment for such a set.

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The Dash 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, inter-hospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and pre-hospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, non-invasive blood pressure, pulse. temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The Dash 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The Dash 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The Dash 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12 lead ECG analysis (12SL). Additionally, the network interface allows for the display and transfer of network available patient data.

The GE Medical Systems Information Technologies Dash 3000/4000 Patient Monitor is a physiological patient monitor designed to monitor, display, and print a patient's basic physiological parameters. These parameters include electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide, and anesthetic agents. The device also offers features like arrhythmia detection, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12-lead ECG analysis (12SL).

This submission describes the acceptance criteria and study used to demonstrate the substantial equivalence of the Dash 3000/4000 Patient Monitor to predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list specific numerical acceptance criteria for each physiological parameter monitored by the Dash 3000/4000 Patient Monitor, nor does it provide detailed reported device performance values in a quantitative table.

Instead, the submission outlines a general approach to compliance and testing. The "Test Summary" section states:
"The Dash 3000/4000 Patient Monitor complies with the voluntary standards as detailed in Section 9 of this submission. The following quality assurance measures were applied to the development of the system:

• Requirements specification review
• Code inspections
• Software and hardware testing
• Safety testing
• Environmental testing
• Final validation"

The "Conclusion" then states:
"The results of these measurements demonstrated that the Dash 3000/4000 Patient Monitor is as safe, as effective, and performs as well as the predicate devices."

This implies that the acceptance criteria were based on adherence to relevant voluntary standards and that the device's performance was found to be comparable to that of the predicate devices for all specified physiological parameters. Without "Section 9" or further detailed test reports, specific numerical performance figures and acceptance thresholds cannot be extracted from this summary.

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

The provided 510(k) summary does not specify the sample size used for the test set. It mentions "software and hardware testing," "safety testing," and "environmental testing," but does not provide details about the number of patients, data points, or scenarios included in these tests.

The data provenance (e.g., country of origin, retrospective or prospective) is also not mentioned in the summary. The studies appear to be internal verification and validation tests rather than clinical trials with external data sources.

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

The provided summary does not mention the use of experts to establish ground truth for any specific physiological parameter. The testing appears to be focused on technical performance against established standards and predicate device comparisons rather than requiring expert adjudication of clinical outcomes or interpretations.

4. Adjudication Method for the Test Set

Since the summary does not indicate the involvement of experts for establishing ground truth, there is no adjudication method mentioned (e.g., 2+1, 3+1). The testing described likely relied on instrumental measurements and technical specifications.

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

The summary does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The device is a physiological patient monitor, and the described testing focuses on its technical performance and compliance with standards, not on human reader interpretation accuracy or the effect of AI assistance.

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

The summary does not explicitly describe a standalone performance study in terms of "algorithm only without human-in-the-loop performance." However, the "Test Summary" detailing "software and hardware testing" and "final validation" implies that the device's functionality was evaluated in a standalone manner to ensure it meets requirements and performs as intended. The listed physiological parameters are measured and displayed by the device itself, suggesting an inherent standalone performance evaluation against established reference methods or predicate devices.

7. Type of Ground Truth Used

The type of ground truth used for the testing highlighted in the summary would be based on:

• Voluntary standards: Compliance with recognized industry and regulatory standards (as mentioned in Section 9, although not provided).
• Predicate device comparison: Performance being "as safe, as effective, and performs as well as the predicate devices," indicating that the predicate device's performance serves as a benchmark for comparison.
• Technical specifications and requirements: The device's performance against its own "requirements specification."
• Instrumental measurements: For parameters like ECG, blood pressure, temperature, etc., the "ground truth" would be derived from calibrated reference instruments or established measurement methodologies.

8. Sample Size for the Training Set

The Dash 3000/4000 Patient Monitor is presented as a physiological monitoring device, not a machine learning or AI-driven diagnostic algorithm that typically relies on a distinct "training set." Therefore, the concept of a "training set sample size" as understood in AI/ML contexts does not apply to the information provided in this 510(k) summary. The device's functionality is based on established signal processing and measurement techniques, not on a data-driven learning model requiring traditional training data.

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

As noted above, the concept of a "training set" is not applicable to the type of device and information provided in this 510(k) summary. Therefore, how ground truth for a training set was established is not relevant or described.

Ask a specific question about this device

The Dash 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, interhospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and pre-hospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The Dash 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The Dash 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The Dash 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations. PA wedge. ST analysis, and interpretive 12 lead ECG analysis (12SL).

Additionally, the network interface allows for the display and transfer of network available patient data.

This document describes a 510(k) submission for a medical device and, as such, focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific quantitative acceptance criteria in a clinical study for a novel AI algorithm. Therefore, many of the requested points, particularly those related to detailed study design, ground truth establishment, expert review, sample sizes for training/test sets, and comparative effectiveness studies with AI, are not applicable or cannot be extracted from this type of regulatory submission.

The submission primarily states that the device is "as safe, as effective, and performs as well as the predicate devices" based on compliance with voluntary standards and internal quality assurance measures.

Here's an attempt to answer the questions based on the provided text, noting where information is not available:

Acceptance Criteria and Device Performance (Based on available information)

Study Details

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

   • Sample Size: Not specified.
   • Data Provenance: Not specified. The document states "The Dash 3000/4000 Patient Monitor complies with the voluntary standards as detailed in Section 9 of this submission" and lists quality assurance measures, which would typically involve testing, but no details on specific test sets or study types (e.g., patient data, simulated data) are provided.

2. 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. This is a traditional medical device (patient monitor) regulatory submission based on substantial equivalence to predicate devices and compliance with performance standards, not a specific AI/machine learning algorithm requiring expert-established ground truth for a test set in the same manner.

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

   • Not applicable for the reasons stated above.

4. 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. The device is a physiological patient monitor, not an AI-assisted diagnostic tool that would typically undergo an MRMC study.

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

   • Not applicable. This is not an algorithm-only device; it's a patient monitor system. Its performance is inherent to the system's design and functionality in monitoring physiological parameters.

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

   • Not explicitly stated in terms of a "ground truth" as it would be for an AI diagnostic device. The "ground truth" for a patient monitor's accuracy would typically be established through validation against validated reference devices or established physiological measurement standards during product testing, as implied by "compliance with voluntary standards" and "safety testing."

7. The sample size for the training set

   • Not applicable. This is not an AI/machine learning device that involves a "training set" in the conventional sense.

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

   • Not applicable for the reasons stated above.

Ask a specific question about this device

The Dash 3000/4000 Patient Monitor is intended for use under the direct supervision of a licensed healthcare practitioner. The intended use of the system is to monitor physiologic parameter data on adult, pediatric and neonatal patients. The Dash is designed as a bedside, portable, and transport monitor that can operate in all professional medical facilities and medical transport modes including but not limited to: emergency department, operating room, post anesthesia recovery, critical care, surgical intensive care, respiratory intensive care, coronary care, medical intensive care, pediatric intensive care, or neonatal intensive care areas located in hospitals, outpatient clinics, freestanding surgical centers, and other alternate care facilities, intra-hospital patient transport, inter-hospital patient transport via ground vehicles (i.e., ambulance, etc.) and fixed and rotary winged aircraft, and pre-hospital emergency response.

Physiologic data includes but is not restricted to: electrocardiogram, invasive blood pressure, noninvasive blood pressure, pulse, temperature, cardiac output, respiration, pulse oximetry, carbon dioxide, oxygen, and anesthetic agents as summarized in the operator's manual.

The Dash 3000/4000 Patient Monitor is also intended to provide physiologic data over the Unity network to clinical information systems and allow the user to access hospital data at the point-of-care.

This information can be displayed, trended, stored, and printed.

The Dash 3000/4000 Patient Monitor was developed to interface with non-proprietary third party peripheral devices that support serial data outputs.

The Dash 3000/4000 Patient Monitor is a device that is designed to be used to monitor, display, and print a patient's basic physiological parameters including: electrocardiography (ECG), invasive blood pressure, non-invasive blood pressure, oxygen saturation, temperature, impedance respiration, end-tidal carbon dioxide, oxygen, nitrous oxide and anesthetic agents. Other features include arrhythmia, cardiac output, cardiac and pulmonary calculations, dose calculations, PA wedge, ST analysis, and interpretive 12 lead ECG analysis (12SL). Additionally, the network interface allows for the display and transfer of network available patient data.

The provided document refers to the K020290 submission for the GE Medical Systems Information Technologies Dash 3000/4000 Patient Monitor. This submission is a 510(k) premarket notification, which means the device is seeking substantial equivalence to a predicate device rather than presenting novel acceptance criteria or a detailed clinical study for efficacy.

Therefore, the document does NOT contain the specific information requested in the prompt regarding:

• A table of acceptance criteria and reported device performance.
• Sample sizes, data provenance, number of experts, adjudication methods, or ground truth details for a test set.
• Information on multi-reader multi-case (MRMC) comparative effectiveness studies.
• Details of a standalone algorithm performance study.
• Sample size and ground truth establishment for a training set.

Instead, the document focuses on the regulatory aspects of a 510(k) submission, confirming the device's intended use, classification, and that it "employs the same functional scientific technology as its predicate devices."

The "Test Summary" section lists quality assurance measures applied to the development, which are general engineering and quality management practices, not specific clinical performance studies with acceptance criteria as typically understood for AI/ML devices. These measures include:

• Risk Analysis
• Requirements Reviews
• Design Reviews
• Testing on unit level (Module verification)
• Integration testing (System verification)
• Final acceptance testing (Validation)
• Performance testing
• Safety testing
• Environmental testing

The conclusion states: "The results of these measurements demonstrated that the Dash 3000/4000 Patient Monitor are as safe, as effective, and perform as well as the predicate device." This is a statement of substantial equivalence, not a report of meeting specific numerical performance criteria from a clinical study.

In summary, the provided document does not contain the detailed study results and acceptance criteria as requested because it is a 510(k) summary for a patient monitor, which relies on demonstrating substantial equivalence to a predicate device rather than presenting novel clinical performance data against predefined acceptance criteria in the manner expected for an AI/ML device.

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