(265 days)
The Health-e-Connect System with IDA is intended for use in the home and clinical settings by people with diabetes and healthcare providers as an aid in the review, analysis, and evaluation of historical glucose test results and associated usage data in support of an effective diabetes management program.
The Insulin Dose Adjustment (IDA) feature is intended only for insulin-requiring Type 2 diabetes patients to provide the physician with two reference doses.
The IDA feature is not indicated for patients who utilize insulin pumps and it is limited to adults with Type 2 diabetes on fixed dose regimen of insulin.
The Health-e-Connect System with IDA is for patients under the supervision of a physician / healthcare provider trained in the management of diabetes. Final drug dose recommendations for a patient must be made only after careful consideration of the full clinical status of the patient. No medical decision should be based solely upon the results provided by this software program.
The ALRT Health-e-Connect System (HeC) allows healthcare providers, ALRT staff, and other authorized caregivers to remotely monitor the blood glucose values of patients with diabetes and therefore can assist healthcare providers in making adjustments to the patient's care plan based upon trends in the patient's blood glucose data. There are no physical, electrical, biocompatible, or sterility specifications for this device as it is software only.
The original Health-e-Connect system (K102063) performed two functions:
- A data management tool and
- A communication platform (Health-e-Connect Remote Care System).
Modification:
The proposed modification is to add a module - Insulin Dose Adjustment (IDA) - to the Healthe- Connect System.
This is an additional module of software that monitors patient blood glucose levels uploaded from the patient's blood glucose meter, to ascertain whether the patient's current insulin dose may or may not be optimal. If trends in the patient's blood glucose are outside of the guidelines set by the AACE and ADA, the patient is flagged for a potential insulin dose adjustment. The IDA system will then employ the AACE and ADA algorithms to calculate reference doses that can be compared with the patient's current insulin dose. If there is an inconsistency between the patient's current insulin dose as compared to the reference doses calculated by AACE and ADA algorithms, this discrepancy will be flagged and an alert sent to the managing HCP requesting an insulin dose review.
The provided text describes a 510(k) submission for the "Health-e-Connect System with IDA (Insulin Dose Adjustment)". While it details the device, its intended use, and a comparison to predicate devices, it does not contain the specific acceptance criteria or an explicit study that proves the device meets those criteria with quantitative performance metrics.
The document discusses "Verification and validation testing" and a "Human Factors / Usability study" but does not provide details on the specific performance outcomes of these tests in relation to predefined acceptance criteria. It focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific numerical targets.
Therefore, I cannot populate the requested table or answer most of the questions directly from the provided text.
Here's what can be inferred or stated based on the given information, with limitations:
1. Table of acceptance criteria and reported device performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not explicit in the document. The document states "Verification testing was performed based on FDA guidance" and "Performance testing performed and all tests showed satisfactory results" for predicates, implying that the new device also met a "satisfactory" level of performance, but no specific criteria or quantitative results are provided. | Not explicit in the document. No quantitative performance metrics (e.g., accuracy, precision, sensitivity, specificity, agreement rates) are provided for the IDA feature's performance against any defined criteria. |
2. Sample size used for the test set and the data provenance:
- Sample size for test set: Not specified.
- Data provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions the device monitors "blood glucose levels uploaded from the patient's blood glucose meter," implying real-world data, but no specifics on the test set's origin.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified. The IDA feature uses "AACE and ADA algorithms to calculate reference doses." This suggests the "ground truth" for the calculated doses is based on these established clinical guidelines, rather than expert human interpretation of individual cases for the purpose of a test set.
4. Adjudication method for the test set:
- Not specified. Given that the IDA feature calculates reference doses based on established algorithms (AACE and ADA), it's unlikely a traditional human adjudication process for a test set was applied in the same way it would be for an AI model that interprets medical images. The "ground truth" is algorithmic.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
- No, an MRMC study is not mentioned. The device's function is to provide "reference doses" to a physician, not to interpret complex medical data like images that would typically necessitate an MRMC study for human reader performance evaluation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- The "Nonclinical Performance Testing" and "Verification and validation testing" suggest an evaluation of the software's functionality, which would be a form of standalone testing for the algorithm's calculation accuracy of reference doses. However, no specific performance results are provided. The function of the IDA feature is to "employ the AACE and ADA algorithms to calculate reference doses," so its standalone performance would be about its fidelity to these algorithms.
7. The type of ground truth used:
- The ground truth for the IDA feature's calculations appears to be based on the guidelines and algorithms established by the American Association of Clinical Endocrinologists (AACE) and the American Diabetes Association (ADA). The device calculates "reference doses" using these established guidelines.
8. The sample size for the training set:
- Not specified. The document primarily describes an algorithmic approach based on existing clinical guidelines rather than a deep learning model requiring a large training set in the conventional sense.
9. How the ground truth for the training set was established:
- Not explicitly a "training set" in the machine learning sense. The "ground truth" for the IDA feature's logic is derived from and established by the AACE and ADA guidelines/algorithms. The system "employs" these existing expert-developed algorithms.
§ 868.1890 Predictive pulmonary-function value calculator.
(a)
Identification. A predictive pulmonary-function value calculator is a device used to calculate normal pulmonary-function values based on empirical equations.(b)
Classification. Class II (performance standards).