Nurses' Perceptions About Smart Beds in Hospitals.

The purpose of this study was to examine nurses' perceptions of the smart mattress equipped with Internet of things, which are incorporated into patients' beds. In addition, their concerns and suggestions about smart mattress were explored. A total of 349 nurses in a tertiary hospital participated in a cross-sectional survey. Data were collected using questionnaires. Descriptive statistical analysis was used for survey data, whereas content analysis was used for qualitative data from open-ended questions. The participants' intention to accept the smart mattresses was 12.5 (SD, 1.73) on average, indicating a high level of acceptance. The participants expected the smart mattresses to decrease their physical work burden, improve work efficiency, and prevent pressure ulcers. However, they were concerned about an increase in other aspects of their workload and in patient safety problems due to false alarms, inaccuracies, and malfunctions of the device. Nurses suggested various features that can be integrated into smart mattress. It is critical to address nurses' perceptions, expectations, and concerns during the conceptual and developmental stage of new technology in order to improve the usability, acceptance, and adoption of smart mattresses and other new innovations in hospital settings.

Nurses' needs for care robots in integrated nursing care services.

AIMS: To determine the need for care robots among nurses and to suggest how robotic care should be prioritized in integrated nursing care services. BACKGROUND: Korea is expected to be a super-aged society by 2030. To solve care issues with elderly inpatient caused by informal caregivers, the government introduced "integrated nursing care services"; these are comprehensive care systems staffed by professionally trained nurses. To assist them, a care robot development project has been launched. DESIGN: The study applied a cross-sectional survey. METHODS: In 2016, we conducted a multicentre survey involving 302 Registered Nurses in five hospitals including three tertiary and two secondary hospitals in Korea. The questionnaire consisted of general characteristics of nurses and their views on and extents of agreement about issues associated with robotic care. RESULTS: Trial centre nurses and those with ≥10 years of experience reported positively on the prospects for robotic care. The top-three desired primary roles for care robots were "measuring/monitoring", "mobility/activity" and "safety care". "Reduction in workload", especially in terms of "other nursing services" which were categorized as nonvalue-added nursing activities, was the most valued feature. The nurses approved of the aid by care robots but were concerned about device malfunction and interruption of rapport with patients. CONCLUSION: Care robots are expected to be effective in integrated nursing care services, particularly in "measuring/monitoring". Such robots should decrease nurses' workload and minimize nonvalue-added nursing activities efficiently. No matter how excellent care robots are, they must cooperate with and be controlled by nurses.

An evaluation of the time for nursing activity in a hospital using a full Electronic Medical Record System (EMR).

This study was designed to analyze the time for direct and indirect nursing activity to evaluate the workload of nurses using a full Electronic Medical Record (EMR) system on practice. The result is that the mean time for nursing activity per nurse was 499.56 minutes, the mean time for direct nursing activity per nurse was 251.1 minutes (50.3%), and the mean time for indirect nursing activity per nurse was 248.42 minutes(49.7%). The time for direct nursing activity was more than the time for indirect nursing activity. There was a significant difference in the time for nursing activity according to workplace (p < 0.00*), but no difference according to nursing career. Regarding 3 duty-shifts, the time for direct nursing activity was highest in the evening shift and the time for indirect nursing activity was highest in the night shift.