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EasyCare Online is a web based solution for healthcare specialists intended to:
• assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an EasyCare Online compatible home sleep test device.
• transfer and display, usage and therapeutic information that has been transmitted remotely from the patient's therapy device located in the home. It is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed therapy device for the treatment of obstructive sleep apnea or respiratory insufficiency. EasyCare Online also provides remote settings capabilities

EasyCare Online is a web application that can transfer, store, manage and display usage and therapy data from (ResMed compatible flow generators) and diagnostic data from (ResMed compatible sleep study devices). The data is transferred from the device either wirelessly through a communications module, or with the aid of an SD card and internet technology, to a central database and then displayed on the clinician's/DME's computer, through a web based application such as internet Explorer.

EasyCare Online is used to monitor and optimize the therapy of patients diagnosed with sleep apnea or respiratory insufficiency, who are using a ResMed therapy device or home sleep test study device. The application enables patient usage data to be shared across several different user groups for the primary purpose of monitoring patient compliance and home sleep studies. Clinical users. Home Medical Equipment (DME) providers and other healthcare specialists can access data with ResMed approved user accounts. Also, clinical users and DMEs are able to address any clinical issues in a timely manner and provide the necessary patient support, including the modification of device settings. EasyCare Online supports physicians in the diagnosis Sleep Disordered Breathing, by reviewing home sleep test results via their web browser or download the clinical data to their PC for further analysis.

Here's an analysis of the provided text regarding the acceptance criteria and study for the EasyCare Online device:

This 510(k) submission is for an expanded intended use of an existing device (EasyCare Online, K123557) by integrating functionality from another predicate device (ApneaLink Plus, K083575). Therefore, the "study" primarily focuses on demonstrating that the new integration does not negatively impact the existing functionality and accurately displays data from the newly integrated device. It does not involve a traditional clinical study for the diagnostic accuracy of the device itself.

Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly derived from the comparison to the predicate devices and the successful completion of non-clinical testing. The "reported device performance" is essentially the successful completion of verification activities.

Study Details

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

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

• Test Set Sample Size: "Three patient breathing pattern scripts" were used for the side-by-side testing.
• Data Provenance: Not explicitly stated. The scripts likely represent simulated or standardized data rather than individual patient data from a specific country or collected prospectively/retrospectively in a clinical setting.

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):

• This submission does not involve human expert adjudication of diagnostic outcomes. The "ground truth" for the side-by-side testing was the output of the predicate ApneaLink Plus PC software. The study's goal was to ensure the modified EasyCare Online replicated this known output accurately. Therefore, no external experts were used to establish ground truth in the traditional sense of a clinical diagnostic study.

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

• None (in the context of human adjudication). The "adjudication" was a direct comparison of output data between the modified device and the predicate device's software.

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 was not an MRMC study. The device is a data management and display system, not a diagnostic AI system intended for direct human assistance in interpretation in the way a typical diagnostic image analysis AI would be.

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

• Yes, in spirit. The core of the "testing" was comparing the data processing and display capabilities of the modified EasyCare Online (algorithm/software only) against the known output of the predicate ApneaLink Plus PC software (also algorithm/software only). The "standalone" performance here refers to the software's ability to process and present data identically to an established, cleared device.

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

• The "ground truth" for the side-by-side testing was the output of the predicate ApneaLink Plus PC software (K083575). This means the existing, cleared device's performance served as the benchmark for accuracy for the data processing and display component. This is often referred to as "reference standard" or "comparator device" in such equivalence studies.

8. The sample size for the training set:

• Not applicable / Not explicitly stated. This submission does not describe the development of a novel algorithm that requires a "training set" in the machine learning sense. The changes primarily involved integrating existing functionalities and ensuring data integrity.

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

• Not applicable. As no training set for a novel algorithm was described, this question is not relevant to this submission. The "ground truth" for the device's expanded functionality was anchored to the performance of its predicate devices.

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EasyCare Online transfers and displays to clinicians, usage and therapeutic information that has been transmitted remotely from the patient's flow generator located in the home. EasyCare Online also provides remote settings capabilities.

EasyCare Online is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed flow generator for the treatment of obstructive sleep apnea or respiratory insufficiency.

EasyCare Online is a web application that can transfer, store, manage and display usage and therapy data from ResMed flow generators. The data is transferred from the flow generators either wirelessly through a communications module or with the aid of an SD card, to a central database and then displayed in a clinician computer, through a web application.

EasyCare Online is used to monitor and optimize the therapy of patients diagnosed with sleep apnea or respiratory insufficiency, who are using a ResMed therapy device. The application enables patient usage data to be shared across several different user groups for the primary purpose of monitoring patient compliance. Clinical users, Home Medical Equipment (HME) providers and other healthcare specialists can access data to monitor patient compliance. Also, clinical users and HMEs are able to address any noncompliance issues in a timely manner and provide the necessary patient support, including the modification of device settings.

The provided text is a 510(k) summary for the EasyCare Online device. It describes the device, its intended use, and argues for its substantial equivalence to previously cleared predicate devices. However, it does not contain a detailed study proving the device meets specific acceptance criteria with performance metrics, sample sizes, or information about ground truth establishment.

The document states:
"Design and non-clinical verification activities were performed on EasyCare Online as a result of the risk analysis and design process. Verification testing included end-to-end testing to verify data transfer integrity between the flow generator and EasyCare Online. All tests confirmed the product met the predetermined acceptance criteria."

This statement indicates that verification testing occurred and acceptance criteria were met, but it does not provide the details requested in your prompt.

Therefore, I cannot populate the table or provide specific details about the study, as they are not present in the provided text.

Based on the available information, here's what can be inferred and what cannot be determined:

Acceptance Criteria and Device Performance

Study Information (Based on available text)

1. Sample size used for the test set and the data provenance: Not specified in the provided text. The testing mentioned is "end-to-end testing to verify data transfer integrity," which sounds like functional verification rather than a clinical study with patient data.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable/not specified. The testing described focuses on data transfer integrity, not diagnostic or therapeutic accuracy that would require expert-established ground truth on patient data.
3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable/not specified.
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: No. EasyCare Online is a data transfer and display system for clinicians, not an AI diagnostic or assistive tool that would involve human readers or MRMC studies.
5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The "end-to-end testing to verify data transfer integrity" can be considered a standalone functional test, but it does not evaluate "performance" in the sense of clinical accuracy or decision-making.
6. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. The "ground truth" for verifying data transfer integrity would likely involve comparing transmitted data against source data, rather than clinical ground truth.
7. The sample size for the training set: Not applicable. The device is a data management and display system, not a machine learning model that requires a training set.
8. How the ground truth for the training set was established: Not applicable.

Summary of what the document implies about the "study":

The "study" was primarily functional verification and non-clinical testing to ensure data transfer integrity and compatibility with new flow generator models. It was not a clinical effectiveness study assessing diagnostic accuracy or therapeutic outcomes, nor did it involve the use of AI algorithms on patient data that would necessitate the detailed ground truth and expert validation methods you've inquired about. The device is described as a system for transferring and displaying patient usage and therapeutic information, rather than a device making automated clinical decisions.

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EasyCare Online is intended to augment the standard follow-up care of patients diagnosed with obstructive sleep apnea by displaying usage and therapeutic information that has been transmitted remotely from the patient's flow generator located in the home to the care giver. EasyCare Online also provides remote settings capabilities.

It is intended to be used by Clinicians in conjunction with ResMed compatible flow generators.

The performance and functional characteristics of EasyCare Online includes all the user features of the predicate device, ResTraxx Online (K083816).

EasyCare Online is designed to function with ResMed OSA treatment systems for the transfer, storage, retrieval and display of stored information from the flow generator to a centralized server. This information can then be accessed by the clinician where the information can be displayed on the clinician's PC using a web browser application. Flow Generator settings changes, via wireless transmission can also be made from the clinicians PC. Access to the data is limited to subscribers of the system. Patients cannot access the system.

EasyCare Online comprises two distinct components, the wireless transmitter/receiver located on the flow generator and the Server System. Data taken from the flow generator is transmitted via a wireless network and stored on the EasyCare Online database.

Here's a breakdown of the acceptance criteria and study information for the ResMed EasyCare Online device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text states: "All tests confirmed that EasCare Online met the predetermined acceptance criteria." However, it does not explicitly list the quantitative acceptance criteria. Instead, the study focuses on demonstrating "Substantial Equivalence" to predicate devices through functional testing.

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

• Sample Size: Not explicitly stated. The document refers to "End-to-End testing" and "System testing" but does not quantify the number of test cases, patient data sets, or flow generators used in these tests.
• Data Provenance: The testing was "bench testing." It is not specified if any real patient data was used for testing, or if simulated data was utilized. The document mentions the flow generators are "located in the patient's home," but the testing itself appears to be simulated environment testing ("bench testing"), not involving actual patients at home for the purpose of the 510(k) submission. Therefore, it's not strictly "retrospective or prospective" in terms of patient data collection for the study.

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

• Number of Experts: Not applicable/not stated. The ground truth for this device's performance was established through functional verification against defined requirements and specifications, not through expert consensus on medical diagnoses or interpretations. The "bench testing" would have been evaluated against technical specifications and expected system behavior.
• Qualifications of Experts: Not applicable/not stated, as the ground truth was not expert consensus.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/none. The testing involved verifying the system's functional performance against predetermined technical requirements, not subjective interpretation requiring adjudication.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done.
• Effect Size: Not applicable, as no MRMC study was performed. The device is a data management and remote setting system, not an AI diagnostic tool.

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

• Standalone Study: Yes, in essence, the "End-to-End bench testing" represents the standalone performance of the system. The device's primary function is to transfer, store, retrieve, display, and remotely set parameters, which are algorithmic and system-level functions. The testing focused on whether the system performed these functions correctly and reliably without human intervention during the data flow.
  • The document explicitly states: "No clinical trials were needed to demonstrate Safety and Efficacy. Based upon the Risk Analysis, End-to-End bench testing alone is sufficient as no new features were added that could raise concerns regarding Safety or Efficacy." This reinforces that only the standalone system performance was evaluated.

7. Type of Ground Truth Used

• Ground Truth Type: The ground truth used was functional specification and predetermined acceptance criteria for system operations, data transfer, storage, display, and remote control. It was based on engineering and software design requirements, rather than clinical outcomes, pathology, or expert medical consensus.

8. Sample Size for the Training Set

• Sample Size: Not applicable/not stated. This device is a software system for data management and remote control, not an AI/machine learning algorithm that requires a "training set" in the conventional sense. The software development lifecycle and verification activities would involve testing against requirements, but not a distinct "training set" for model learning.

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

• Ground Truth for Training Set: Not applicable. As there is no training set for an AI/ML model, there is no corresponding ground truth to be established for it. The ground truth for the overall system's development and testing was its design specifications and functional requirements.

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