Usability Engineering Recommendations for Next-Gen Integrated Interoperable Medical Devices.

This article reports on the development of usability engineering recommendations for next-generation integrated interoperable medical devices. A model-based hazard analysis method is used to reason about possible design anomalies in interoperability functions that could lead to use errors. Design recommendations are identified that can mitigate design problems. An example application of the method is presented based on an integrated medical system prototype for postoperative care. The AAMI/UL technical committee used the results of the described analysis to inform the creation of the Interoperability Usability Concepts, Annex J, which is included in the first edition of the new ANSI/AAMI/UL 2800-1:2019 standard on medical device interoperability. The presented work is valuable to experts developing future revisions of the interoperability standard, as it documents key aspects of the analysis method used to create part of the standard. The contribution is also valuable to manufacturers, as it demonstrates how to perform a model-based analysis of use-related aspects of a medical system at the early stages of development, when a concrete implementation of the system is not yet available.

Research: User Interface Software Errors in Medical Devices: Study of U.S. Recall Data.

The current work assessed U.S. medical device recalls during 2012-15, with the goal of under-standing the impact and nature of user interface (UI) software errors in medical devices. Based on information from the Food and Drug Administration's public and internal recall databases, 423 (~140/year) medical device recalls were identified as resulting from UI software errors, which accounted for nearly one-half of recalls caused by software errors during the same period. A total of 499 UI software errors were identified as the root causes of medical device recalls, and a detailed classification of those errors (into 20 categories) was established. This error classification can be used by device manufacturers, end users (e.g., healthcare providers), and regulatory authorities to raise awareness of the type and impact of UI software errors. The classification also provides stakeholders with an evidence-based challenge to assess and improve the quality of UI software in medical devices.

Exploring medical device design and use through layers of distributed cognition: how a glucometer is coupled with its context.

Medical devices are becoming more interconnected and complex, and are increasingly supported by fragmented organizational systems, e.g. through different processes, committees, supporting staff and training regimes. Distributed Cognition has been proposed as a framework for understanding the design and use of medical devices. However, it is not clear that it has the analytic apparatus to support the investigation of such complexities. This paper proposes a framework that introduces concentric layers to DiCoT, a method that facilitates the application of Distributed Cognition theory. We use this to explore how an inpatient blood glucose meter is coupled with its context. The analysis is based on an observational study of clinicians using a newly introduced glucometer on an oncology ward over approximately 150h (11days and 4 nights). Using the framework we describe the basic mechanics of the system, incremental design considerations, and larger design considerations. The DiCoT concentric layers (DiCoT-CL) framework shows promise for analyzing the design and use of medical devices, and how they are coupled with their context.

7 Themes for guiding situated ergonomic assessments of medical devices: a case study of an inpatient glucometer.

There is relatively little guidance on the situated ergonomic assessment of medical devices, and few case studies that detail this type of evaluation. This paper reports results of a detailed case study that focuses on the design and use of a modern blood glucose meter on an oncology ward. We spent approximately 150 h in-situ, over 11 days and 4 nights, performing observations and interviews with users. This was complemented by interviews with two staff with oversight and management responsibility related to the device. We identified 19 issues with the design and use of this device. These issues were grouped into 7 themes which can help guide the situated study of medical devices: usability, knowledge gaps and mental models, workarounds, wider tasks and equipment, the patient, connection between services, and policy.