(235 days)
The On Call® Plus Diabetes Software is an optional software accessory to be used with the On Call® Plus Glucose Meters for transferring data to a computer and organizing it in tables and graphs to be used at home and by health care professionals. The software does not recommend any medical treatment or medication dosage level.
The On Call® Plus Diabetes Monitoring Software is for downloading glucose data from the On Call Plus meter to a PC through an USB to RS232 TTL level cable or RS232 to RS232 TTL level cable, with tracking and trending capabilities of glucose measurements.
The Diabetes Data Management Software is intended to be used in a clinical setting with multiple patients by a healthcare professional, or directly by the patient.
The user has the choice to install either a personal "Home" or "Professional" version. In the "Home" version, glucose results are assembled for a single user. In the "Professional" version, the software user can configure a database with multiple providers and patients. The number of providers, patients and data points is limited only by the computer's capabilities.
The provided text outlines the capabilities of the "On Call® Plus Diabetes Monitoring Software" and compares it to a predicate device, focusing on its functional characteristics rather than specific quantitative performance metrics against acceptance criteria in the typical sense of a diagnostic or therapeutic medical device.
Therefore, the table of acceptance criteria and reported device performance, and several other requested items, cannot be fully populated as they would for a device with measurable accuracy, sensitivity, or specificity. Instead, the "acceptance criteria" here relate to the software's ability to perform its intended functions and demonstrate substantial equivalence to a predicate device for regulatory approval.
Here's an attempt to answer your questions based on the provided text, acknowledging the limitations due to the nature of the device (diabetes monitoring software, not a diagnostic test):
1. Table of Acceptance Criteria and the Reported Device Performance
For this software, the "acceptance criteria" appear to be related to its functional conformity to its intended use and its substantial equivalence to the predicate device. The document does not specify quantitative performance metrics (e.g., accuracy, precision) as would be found for a glucose meter itself, but rather functional capabilities of the software.
| Acceptance Criteria (Implied from Summary) | Reported Device Performance (as stated in the document) |
|---|---|
| Software Functionality: | |
| - Ability to download glucose data | - Software successfully downloads glucose data from On Call Plus meter to a PC. |
| - Tracking and trending capabilities | - Provides tracking and trending capabilities of glucose measurements through tables and graphs (data list report, line, bar, pie charts, average day line chart, average day/week bar charts). |
| - Support for multiple users/patients | - "Professional" version allows configuration of a database with multiple providers and patients, limited only by computer capabilities. |
| - Data representation (units) | - Supports millimoles per liter (mmol/L) or milligrams per deciliter (mg/dL). |
| - Password protection | - Supports password protection for databases. |
| - Data management (delete) | - Can delete patients, providers, databases, and data stored in meters. |
| Usability/User Experience (Clinical Test): | |
| - Ease of operation by intended users | - "Study results indicate that non-professional, inexperienced lay persons were able to operate the software and obtain glucose trending reports." |
- "Participating lay persons were questioned and responded as satisfied with the ease of operation by following the User's Manual and the overall performance of the On Call® Plus Diabetes Monitoring Software." |
| Regulatory/Safety Compliance: | |
| - Compliance with software guidance | - Evaluated by performing software validation tests; compliance with "Content of Premarket Submissions for Software Contained in Medical Devices - Guidance for Industry and FDA Staff." |
| - Compliance with voluntary standards | - Compliance to EN 62366:2008 for usability engineering and EN 62304:2006 for software life cycle processes. |
| - Substantial Equivalence | - "The laboratory testing and clinical study results demonstrate that the On Call® Plus Diabetes Monitoring Software is safe, effective and easy-to-use. It demonstrates that the On Call® Plus Diabetes Monitoring Software meets all the validation and clinical requirements and is substantially equivalent to the Bayer Glucofacts Deluxe Diabetes Management Software." |
2. Sample Size Used for the Test Set and the Data Provenance
- Test Set Sample Size: The document states that "Clinical studies were conducted with lay persons," but does not specify the exact number of lay persons who participated in this usability test.
- Data Provenance: Not explicitly stated, but the submission is to the FDA from a company (ACON Laboratories, Inc.) based in San Diego, California, USA. The "clinical studies" for usability were likely conducted within the U.S. and are prospective in nature, as they involve users interacting with the device for evaluation.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
This information is not applicable or not provided in the context of this software. The "clinical study" described is a usability study where lay persons evaluate the software's ease of operation. There isn't a "ground truth" to be established by experts in the typical clinical sense (e.g., diagnosis of a condition). The "truth" being evaluated is whether lay users can successfully operate the software.
4. Adjudication Method for the Test Set
This information is not applicable or not provided. Since the primary evaluation was a usability study with lay persons, there's no mention of an adjudication process by experts to resolve disagreements on a 'ground truth' diagnosis or outcome. The evaluation seems to be based on the users' ability to perform tasks and their satisfaction.
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
This is not applicable. The device is monitoring software for diabetes glucose data, not an AI-powered diagnostic or interpretive tool that assists human "readers" (e.g., radiologists, pathologists) in making diagnoses. Therefore, an MRMC study comparing human performance with and without AI assistance is not relevant to this device.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is not applicable in the traditional sense of a diagnostic algorithm. The "On Call® Plus Diabetes Monitoring Software" is an accessory for a glucose meter. Its function is to transfer, organize, and display data collected by the meter, not to autonomously interpret or diagnose without human interaction. The "software validation test" and "clinical study" confirm its functional performance and usability.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
As this is a diabetes monitoring software solely for data management and visualization, there is no "ground truth" in the diagnostic sense (like pathology or expert consensus on a disease). The "truth" validated by the software is:
- Its ability to accurately transfer glucose readings.
- Its ability to correctly organize and display this data in various reports and charts according to its specifications.
- Its ease of use by its intended users.
The non-clinical tests focused on software validation (ensuring it performs as designed) and compliance with relevant software standards. The clinical test focused on usability by lay persons.
8. The Sample Size for the Training Set
This information is not provided and is likely not applicable in the typical machine learning sense for this device. The software appears to be rule-based for data management and visualization, rather than an AI/ML model that requires a "training set" of data to learn from. The software's development would involve standard software engineering practices and testing, not AI model training.
9. How the Ground Truth for the Training Set Was Established
This information is not provided and is likely not applicable, as explained in point 8.
§ 862.1345 Glucose test system.
(a)
Identification. A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.(b)
Classification. Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.