Safe and usable ensemble formation for networked medical devices: a comparative study of 5G, NFC and pop-up pairing

Incorrectly formed medical device ensembles can cause therapy to be performed at the wrong site or display safety-critical data from the wrong patient. This early, exploratory study investigates which wireless ensemble-creation techniques minimize risk while remaining safe and usable in intraoperative workflows. The goal is to identify the most promising methods among 5G, NFC, and pop-up pairing.

Eight techniques (5G proximity/location, pop-up pairing, QR Code, Near-Field Communication (NFC) Tag and Reader, device-ID copying, manual selection, device interaction, and SDC context lookup) and five clinical situations (patient bedside, transport, prep room, operating room (OR), post OR) were examined. Five interoperability and clinical experts rated the importance of risk- and usability-related criteria for each situation, as well as how well the criteria are being fulfilled by the different methods. The criteria weights and the method-specific ratings were combined in a quantitative decision matrix to identify the three most promising approaches, which were implemented in a click-dummy prototype and evaluated through formative testing with two clinicians.

The analysis rated 5G, NFC, and pop-up pairing the highest when combining all categories. Subsequent formative tests with clinicians from the University Hospital Bonn support technical feasibility and highlight clear trade-offs. In this small sample (n = 2), NFC was perceived as the safest and most preferred technique. 5G offered speed and automation potential, but raised critical concerns regarding accuracy. Pop-up pairing was considered flexible yet error-prone when multiple devices entered pairing mode simultaneously.

This is a systematic comparison of wireless SDC-ensemble techniques. Early clinical feedback favors NFC for its perceived safety, while 5G and pop-up pairing approaches require additional refinements to mitigate residual risks. As one participant pointed out: "I prefer a reliable and slower over an automated but error-prone method".