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The BD Intraosseous Vascular Access System provides intraosseous access in the proximal tibia, distal tibia and humeral head (proximal humerus) of adult and pediatric patients, and the distal femur in pediatric patients when intravenous access is difficult or impossible to obtain in emergent, urgent, or medically necessary cases for up to 24 hours.

The BD Intraosseous Vascular Access System provides clinicians and emergency personnel with access to the intraosseous space for resuscitation and lifesaving fluid delivery for up to 24 hours. The BD Intraosseous Vascular Access System consists of the following:
•a single use hypodermic needle (with needle safety cap),
•a powered or manual driver to assist with needle insertion,
•an extension set, and
•an adhesive-backed securement dressing.

For insertions using the powered driver, the hypodermic needle includes a needle hub that mates with a stylet connected to a drive adapter hub. The drive adapter hub includes a ferromagnetic material that is attracted by the magnet in the powered driver and attaches to the powered driver prior to needle insertion. The BD Intraosseous Vascular Access System is an easy-grip, hand-held, battery-powered device used to assist in the insertion of the subject device needle through the bone cortex. The assembly of the hypodermic needle and stylet with connected drive adapter hub is referred to as the needle set.

This is a 510(k) summary for a medical device called the "BD Intraosseous Vascular Access System EMS Powered Driver". This document details various aspects of the device and its claim of substantial equivalence to a predicate device. However, it does not contain a study proving the device meets acceptance criteria derived from a clinical trial or a formal comparative effectiveness study (MRMC study) as would be typical for an AI/ML powered device.

Instead, this document focuses on demonstrating substantial equivalence to a previously cleared predicate device by comparing technical characteristics and performance based on adherence to recognized consensus standards and in-house protocols. This is a common pathway for medical device clearance when significant changes are not made that would require new clinical data.

Therefore, many of the specific points you requested (like sample size for test set, number of experts for ground truth, adjudication methods, MRMC study effect size, standalone performance, training set size, and ground truth establishment for training set) are not applicable to the information provided in this 510(k) summary because it primarily describes a device modification with performance demonstrated through engineering verification and validation, not a clinical study to assess diagnostic or therapeutic accuracy of an AI.

However, I can extract the acceptance criteria and performance information as presented for this type of device submission:

1. Table of Acceptance Criteria and Reported Device Performance

The document states: "The subject device met all predetermined acceptance criteria derived from the above listed reference standards and demonstrated substantially equivalent performance as compared to the cited predicated device."

It lists numerous standards and guidance documents that cover various aspects of the device's performance, safety, and functionality. The "acceptance criteria" for this type of submission are meeting the requirements of these standards. The "reported device performance" is that it did meet these criteria, thus demonstrating substantial equivalence.

Since specific quantitative acceptance criteria and corresponding reported values are not presented in a table format in the provided text, I will summarize the categories of performance assessed based on the listed standards.

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

This document does not specify a "test set" in the context of clinical data for an AI/ML device. The testing conducted was largely engineering verification and validation against standards and internal protocols to ensure the device modifications (changes in driver shape, materials, battery, software firmware, and switch) did not raise new questions of safety or effectiveness compared to the predicate device. Therefore, clinical trial-style sample sizes and data provenance (e.g., country of origin, retrospective/prospective) are not detailed here.

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

Not applicable. This is not an AI/ML diagnostic or prognostic device requiring expert-established ground truth from a test set of medical cases. Performance was assessed against engineering and safety standards.

4. Adjudication Method for the Test Set

Not applicable. See point 3.

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

Not applicable. This is a hardware device (an intraosseous vascular access system powered driver), not an AI/ML solution designed to assist human readers or clinicians with interpretation tasks.

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

Not applicable. This is a physical medical device, not an algorithm. Its function is to assist in inserting a needle, not to provide diagnostic or prognostic information.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

Not applicable in the conventional sense for AI/ML devices. The "ground truth" for this device's performance is adherence to established engineering, safety, and performance standards as outlined in the numerous ISO, IEC, ANSI AAMI, and FDA guidance documents.

8. The Sample Size for the Training Set

Not applicable. This device is not an AI/ML system that utilizes a training set of data.

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

Not applicable. See point 8.

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