The fetal heart rate (FHR) is a marker of fetal well-being in utero (when monitoring maternal and/or fetal pathologies) and during labor. Here, we developed a smart mobile data module for the remote acquisition and transmission (via a Wi-Fi or 4G connection) of FHR recordings, together with a web-based viewer for displaying the FHR datasets on a computer, smartphone or tablet. In order to define the features required by users, we modelled the fetal monitoring procedure (in home and hospital settings) via semi-structured interviews with midwives and obstetricians. Using this information, we developed a mobile data transfer module based on a Raspberry Pi. When connected to a standalone fetal monitor, the module acquires the FHR signal and sends it (via a Wi-Fi or a 3G/4G mobile internet connection) to a secure server within our hospital information system. The archived, digitized signal data are linked to the patient's electronic medical records. An HTML5/JavaScript web viewer converts the digitized FHR data into easily readable and interpretable graphs for viewing on a computer (running Windows, Linux or MacOS) or a mobile device (running Android, iOS or Windows Phone OS). The data can be viewed in real time or offline. The application includes tools required for correct interpretation of the data (signal loss calculation, scale adjustment, and precise measurements of the signal's characteristics). We performed a proof-of-concept case study of the transmission, reception and visualization of FHR data for a pregnant woman at 30 weeks of amenorrhea. She was hospitalized in the pregnancy assessment unit and FHR data were acquired three times a day with a Philips Avalon® FM30 fetal monitor. The prototype (Raspberry Pi) was connected to the fetal monitor's RS232 port. The emission and reception of prerecorded signals were tested and the web server correctly received the signals, and the FHR recording was visualized in real time on a computer, a tablet and smartphones (running Android and iOS) via the web viewer. This process did not perturb the hospital's computer network. There was no data delay or loss during a 60-min test. The web viewer was tested successfully in the various usage situations. The system was as user-friendly as expected, and enabled rapid, secure archiving. We have developed a system for the acquisition, transmission, recording and visualization of RCF data. Healthcare professionals can view the FHR data remotely on their computer, tablet or smartphone. Integration of FHR data into a hospital information system enables optimal, secure, long-term data archiving.
Auto-injection devices must be easy and intuitive to use, especially in emergency situations. However, there are many reports of safety-related issues affecting auto-injectors and pen injectors, due to usability deficits. To minimize this type of problem, the identification of potential use errors is an important and critical task in usability engineering. The aim of this systematic, qualitative literature review was to identify and catalog use errors related to disposable auto-injection devices. The key terms "auto-injector", "usability", and "safety/errors" were used to search in the PubMed and Scopus databases for articles from peer-reviewed journals and conference proceedings published in English or French between 2000 and 2017. Use errors, close calls, and operational difficulties were identified, extracted and hierarchically classified. The analysis showed that of the 1415 initially identified publications, 38 met all the eligibility criteria. A qualitative analysis identified 232 instances of use errors and close calls, which were classified into 10 main categories and then 39 subcategories. The present results could be used to guide the design, evaluation and risk analyses of disposable autoinjection devices. Our approach is in line with the European Union's latest regulations on improving the safety of medical devices-especially those concerning transparency and traceability.
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