(76 days)
The TELEVISIT software allows healthcare professionals to conduct remote medical check-ups through interactive sessions with patients who have limited mobility or live in remote locations. The TELEVISIT software is intended for the purposes of collecting physiological data such as: Non-Invasive Blood Pressure; Pulse Oximetry, Temperature and Breath Sounds (Auscultation). The software provides physicians with a tool to schedule appointments with remote patients; to initiate and manage a medical check-up session, to provide data acquisition of medical device data, and to view session reports.
The intended use of the TELEVISIT software is in hospital/clinical environments with established specialized care providing access to each patient in their home and/or local community health center. TELEVISIT software is a non-invasive medical device, which does not flag any abnormal results from the medical device inputs. The TELEVISIT software does not monitor, assess or diagnose a disease, a disorder, or an abnormal physical state. The intended use for the software is data acquisition and collection only, with no treatment function or danger to the end user. The data obtained from TELEVISIT software can be used only as an aid in the diagnosis and treatment of the patient.
TELEVISIT is consist of the following 3 main components: Televisit Terminal (Patient/Physician), TELEVISIT Medical Device Gateway Box and the TELEVISIT Management Software. FDA Cleared accessories are provided to record physiological data such as: Breath Sounds (Auscultation); Non-Invasive Blood Pressure; Temperature / Thermometry; Pulse Oximetry.
The provided 510(k) summary for the TELEVISIT device does not contain detailed acceptance criteria or a comprehensive study report with specific performance metrics and statistical analysis typically found in modern AI/ML device submissions.
This submission is for a "Physiological Data Collection System" that gathers data from other FDA-cleared medical devices and transmits/stores it. The focus of the performance data in this type of submission is on the functional operation of the system itself, rather than the diagnostic or predictive accuracy of an AI algorithm.
However, based on the information provided, here's an attempt to extract and interpret the requested details:
Acceptance Criteria and Reported Device Performance
Given that this is a data collection and transmission system, the "performance" is primarily حول the accuracy and reliability of data transfer and system functionality. Quantitative accuracy metrics (like sensitivity, specificity, AUC) for diagnosis or prediction are not applicable here as the device explicitly states it "does not monitor, assess or diagnose a disease."
Acceptance Criteria (Inferred from description) | Reported Device Performance |
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Accurate transmission of physiological data from patient system to main computer system. | "Testing confirmed that TELEVISIT meets all of its intended functional requirements." |
Accurate reception of physiological data at the main computer system. | "Testing confirmed that TELEVISIT meets all of its intended functional requirements." |
Accurate transmission of physiological data from main computer system to physician's system. | "Testing confirmed that TELEVISIT meets all of its intended functional requirements." |
Meeting all intended functional requirements (scheduling, session management, data acquisition, viewing reports, archiving). | "Testing confirmed that TELEVISIT meets all of its intended functional requirements." |
Safety and effectiveness comparable to predicate devices. | "The results demonstrate that TELEVISIT is safe and effective." |
Compliance with risk analysis per ISO 14971:2000. | "A risk analysis per ISO 14971: 2000 has been performed... The results demonstrate that TELEVISIT is safe and effective." |
Study Details:
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Sample size used for the test set and the data provenance:
- Sample Size: Not specified. The document only mentions "Performance testing included verification and validation." There is no indication of the number of patient sessions, data points, or clinical scenarios used in this testing.
- Data Provenance: Not specified. It's likely that the testing was conducted internally by PHD Medical, possibly in a simulated or controlled environment, as opposed to a multi-site clinical trial with geographically diverse data. There is no mention of country of origin for the data or whether it was retrospective or prospective.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: Not applicable. For a device focused on data collection and transmission validation, "ground truth" would likely refer to the verifiable accuracy of data transfer (e.g., comparing source data values to received data values) rather than expert interpretation of medical images or patient conditions.
- Qualifications of Experts: Not specified or applicable in the context of this device's function.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not applicable. Adjudication methods are typically used for establishing ground truth in diagnostic studies where there might be disagreement in expert interpretation. For functional testing of data transmission, adjudication is not a standard practice.
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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, an MRMC study was not done. This device is a data collection system, not an AI diagnostic tool. It explicitly states it "does not monitor, assess or diagnose a disease" and "does not flag any abnormal results." Therefore, there is no AI component that would assist human readers in interpretation or diagnosis.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- This question is based on the assumption of an AI algorithm. The TELEVISIT is a software system for data collection and transmission, not an AI algorithm performing diagnosis or analysis. Its performance is about the functionality of the system itself.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- The "ground truth" for this device would be the accurate and verifiable transmission of physiological data. For example, if a blood pressure monitor reads 120/80 mmHg, the "ground truth" is that the TELEVISIT system accurately transmits and records "120/80 mmHg" without alteration or loss. There is no mention of expert consensus, pathology, or outcomes data being used since the device is not for diagnosis or treatment.
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The sample size for the training set:
- Not applicable. This device is not an AI/ML algorithm that requires a "training set." It is a software system performing specified functions.
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How the ground truth for the training set was established:
- Not applicable, as there is no training set for an AI/ML algorithm.
Summary of Limitations due to Device Type and Submission Age:
It's crucial to understand that this 510(k) submission is from 2006 for what is essentially a telehealth/telemonitoring data transmission and management system, not an AI-powered diagnostic or predictive tool. The regulatory expectations and the type of performance data required for such a device at that time differ significantly from what would be expected for a modern AI/ML device submission. The performance testing was focused on system functionality, data integrity, and compliance with general software validation and risk management standards (like ISO 14971).
§ 870.2700 Oximeter.
(a)
Identification. An oximeter is a device used to transmit radiation at a known wavelength(s) through blood and to measure the blood oxygen saturation based on the amount of reflected or scattered radiation. It may be used alone or in conjunction with a fiberoptic oximeter catheter.(b)
Classification. Class II (performance standards).