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The ALARIS Medical Systems, Inc., Medley" System with Medication Management System (MMS) is intended for use in today's growing professional healthcare environment for facilities that utilize infusion devices for the delivery of fluids, medications, blood and blood products.

The Medley™ System with MMS is intended to provide trained healthcare caregivers a way to automate the programming of infusion parameters, thereby decreasing the amount of manual steps necessary to enter infusion data. All data entry and validation of infusion parameters is performed by the trained healthcare professional according to a physician's order.

The Medley *** System (K950419) is a currently marketed modular infusion and monitoring system that consists of a Programming Module (PM) and attachable/detachable modules. Current infusion modules available are a Pump Module (K950419) and a Syringe Module (K023264). Monitoring modules currently include Pulse Oximetry (SpO2) using Nellcor (K022677) and Masimo (K010966) technology.

This traditional 510(k) Premarket Notification is being submitted to assist our customers in reducing the number of manual steps needed to program an infusion by allowing wireless communication capability to the currently marketed device, the Medley" Medication Safety System (Medley System) K950419. This Medication Management System (MMS) adds communication capability to the Medley" System thereby providing our customers with a "safety net" at the bedside to help reduce the number of programming errors at the point of care. This product will be called the Medley System with MMS.

As with the predicate device (B. Braun Medical Inc., Horizon™ Outlook with DoseCom™) this submission adds wireless communication to a server and to an existing infusion device. The Medley System was originally cleared with the capability of wired or wireless communication to include receiving infusion protocol information, uploading/downloading system configuration information and reporting infusion or system status. However, this capability was not well defined and did not include communication with a Server. It was also not clear about the local retrieval of data using optical laser scanning (bar-coding) or RF detection of information contained in documents, labels, RF ID Chips, etc. Adding MMS to the Medley System is simply an expansion of the original 510(k) indications for use for the Medley System. This submission will allow the Medley System to transmit and receive messages with the ALARIS® Server which in turn allows communication capability with external devices, including personal computers, Personal Digital Assistants (PDA's), hospital monitoring systems and Hospital Information Management Systems (HIMS).

The provided text is a 510(k) Premarket Notification for the ALARIS Medical Systems, Inc. Medley System with MMS. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain detailed information about specific acceptance criteria or a study proving the device meets those criteria, especially in the context of typical AI/ML device evaluations.

Here's a breakdown based on the information provided and what is missing:

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

2. 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. The document states "performance data" was used but doesn't detail the nature or size of the dataset.
• Data Provenance: Not specified.

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)

• Number of Experts: Not applicable. This device is an infusion pump system with communication capabilities, not an AI/ML diagnostic or prognostic device that typically requires expert-established ground truth for performance evaluation.
• Qualifications of Experts: Not applicable. The "ground truth" for this type of device would likely involve functional testing against specifications and comparison to the predicate device's operational characteristics, rather than expert interpretation of medical images or patient data.

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

• Adjudication Method: Not applicable. As noted above, this is not an AI/ML diagnostic device requiring expert adjudication.

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

• MRMC Study: No. An MRMC study is typically for evaluating the impact of AI assistance on human reader performance in diagnostic tasks. This device is an infusion pump system, which does not involve "human readers" in this context.

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

• Standalone Performance: The performance data assessed the device's ability to "meet specified requirements" and be "substantially equivalent to the predicate device." This implies an evaluation of the system's functionalities, including its communication capabilities and automation features, as a standalone entity in relation to its intended purpose. However, the exact methodology is not detailed. The automation of programming infusion parameters is a key function described.

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

• Type of Ground Truth: Not explicitly stated as "ground truth" in the AI/ML sense. For this device, the "ground truth" would likely be based on:
  • Functional specifications: Whether the device performs as designed (e.g., transmits and receives data correctly, automates programming accurately).
  • Comparison to predicate device: Demonstrating that its technological characteristics and performance are equivalent to the legally marketed predicate device (B. Braun Medical Inc., Horizon™ Outlook with DoseCom™).
  • Safety standards: Adherence to relevant safety and performance standards for infusion pumps.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This device is a hardware/software system for infusion and communication, not an AI/ML model that undergoes a "training" phase with a dataset in the typical sense.

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

• Ground Truth for Training Set: Not applicable, as this is not an AI/ML device that requires a training set with associated ground truth for model development.

In summary: The provided 510(k) document focuses on establishing substantial equivalence for an infusion pump system with added communication capabilities. It references "performance data" indicating the device meets "specified requirements" and is "substantially equivalent" to a predicate device. However, it does not provide the detailed quantitative acceptance criteria, study design, or AI/ML-specific evaluation metrics (like sample sizes for test/training sets, expert adjudication, or MRMC studies) that would typically be found in a submission for an AI/ML-enabled diagnostic or prognostic device. The nature of this device means these AI/ML-specific questions often do not directly apply.

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