Aug 2026· Peritoneal Dialysis International· pp.
8968608261476545
· 0 citations· 9 references
Medicine
TL;DR
The Archimedes APD system usability was found to be safe, accessible and easy for its intended users and use environments after the relatively short training period compared to the status quo.
Abstract
BackgroundBecause automated peritoneal dialysis (APD) systems are used in the home and operated by patients or their care partners, the human-device interface must be thoughtfully designed to facilitate intuitive operation to reduce the risk of errors that could occur during their use. User-friendly design should also help reduce anxiety to peritoneal dialysis (PD) adoption by patients incident to end-stage kidney disease (ESKD). Usability issues remain a significant barrier to PD adoption and are an important contributor to premature death, serious injuries, and PD technique failure.MethodsA summative human factors usability study was conducted on a novel, gravity-based APD device (Archimedes™) with 15 current or former PD patients and 15 dialysis nurses. Participants were trained for 2 h, followed by a training decay period, then evaluated with critical Use Scenario tasks consisting of Simulated Use tasks and Knowledge tasks reflecting tasks that could result in patient harm if performed incorrectly.ResultsOf the Simulated Use tasks evaluated, 97.3% were deemed successful across all users. This high success rate demonstrates the effectiveness of the Archimedes APD device in facilitating the tasks required for PD. For patients, success outcomes were achieved in 96.8% of Simulated Use tasks. Nurses achieved a success rate of 97.8% for Simulated Use tasks evaluated. For Knowledge tasks, success outcomes were achieved in 99.3% and 98.6% of tasks for patients and nurses.ConclusionIn this summative human factors usability study, the Archimedes APD system usability was found to be safe, accessible and easy for its intended users and use environments after the relatively short training period compared to the status quo.
GenAI-assisted processes can provide rapid, actionable design mitigations that reduce error likelihood and enhance patient autonomy, establishing a replicable pipeline for producing heuristic-driven design libraries across diverse medical device contexts.
F. Montalvo, Kathren Pavlov, Phuoc Thai et al.· Proceedings of the Internati...· 0 citations
The nature of therapy interrupting system errors in automated peritoneal dialysis (APD) cyclers of a German PD reference care centre is analysed and resolution strategies to these errors based on routinely collected health data and user experience are suggested to safely guide nephrology professionals and patients duri...
Annemarie Albert, Stefan Richter, R. Woitas et al.· BMC Health Services Research· 0 citations
BACKGROUND
Peritoneal dialysis (PD) naturally lends itself to artificial intelligence (AI) integration due to its generation of dense, longitudinal and structured data. PD outcomes are strongly influenced by modifiable factors such as dialysate composition, dwell time, and fluid balance, making prediction directly acti...
J. Arriola-Montenegro, Tamar Ratishvili, Andrea G. Kattah· Blood Purification· 0 citations
Hemodialysis (HD) patients and providers have long struggled with intra-dialytic hypotension (IDH), a complication that continues to challenge the safety and effectiveness of HD. IDH is associated with chronic end-organ damage and remains an independent risk factor for mortality among HD patients. Persistent hemodynami...
Rubash Nath Yogi, P. Chhetri, D. Manandhar et al.· Nepal Medical College Journa...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.