Evaluation of the Pressure Injury Prevention Information System

Exploring the Usage Effectiveness of a Nursing Charge System

The nursing charge system for inpatient accounting has been utilized in healthcare institutions for years. However, the level of its effectiveness in meeting the needs of nursing services, including further development, has not been systematically evaluated. A cross-sectional study based in Delone and McLean's information system success model was applied to explore the level of effective nursing charge system usage across the five dimensions of system quality, information quality, service quality, user satisfaction, and net benefits. We conducted a survey of the inpatient units of a medical center in Taiwan from June 23, 2021, to July 23, 2021. A total of 214 valid questionnaires were collected. Using a 5-point Likert scale, the dimension with the highest score was information quality (3.71), followed by service quality (3.37), user satisfaction (3.36), net benefits (3.31), and system quality (3.23). Older nurses ( r = -0.176) and those with more clinical experience ( r = -0.151) viewed the nursing charge system as having less information quality. The comfort level with using the computer was positively associated with system quality ( r = 0.396), information quality ( r = 0.378), service quality ( r = 0.275), user satisfaction ( r = 0.417), and net benefits ( r = 0.355). The opinions of nurses are vital. User feedback and advice should be investigated regularly to achieve system optimization.

Exploring the Effectiveness of Nurses' Usage of a Wound-Photography System

As a result of rapid advancements in health information technology, uploading health-related information and records onto an electronic health record system has become a common practice. Photographs of patients' wounds have been uploaded electronically, but widespread acceptance by nurses has been prevented owing to issues such as file size and equipment. This research explores the attitude and satisfaction toward using an electronic health record for uploading wound photos. Through the integration of the Technology Acceptance Model, Information System Success Model, and other study results, this research aims to explore the impact of the following variables: system quality, information quality, perceived usefulness, perceived ease of use, user attitude, user satisfaction, and net benefits. We also tested nurses' understanding regarding the process of taking photographs and explored the photograph quality and the photography uploading rates. The results revealed that users were satisfied with the wound-photography system, but some believed that the system stability, processing time, and image resolution should be improved. In addition, more than 80% of the nurses correctly answered photo-taking questions, the study photos reached 70% of the quality standards, and the average uploading rate was 74%. The results could serve as guidelines for system design in the future.

Acceptance of a robotic system for nursing care: a cross-sectional survey with professional nurses, care recipients and relatives

BACKGROUND

The end-users' acceptance is a core concept in the development, implementation and evaluation of new systems like robotic systems in daily nursing practice. So far, studies have shown various findings concerning the acceptance of systems that are intended to assist people with support or care needs. Not much has been reported on the acceptance of robots that provide direct physical assistance to nurses in bedside care. Therefore, this study aimed to investigate the acceptance along with ethical implications of the prototype of an assistive robotic arm aiming to support nurses in bedside care, from the perspective of nurses, care recipients and their relatives.

METHODS

A cross-sectional survey design was applied at an early stage in the technological development of the system. Professional nurses, care recipients and relatives were recruited from a university hospital and a nursing home in Germany. The questionnaire was handed out following either a video or a live demonstration of the lab prototype and a subsequent one-to-one follow-up discussion. Data analysis was performed descriptively.

RESULTS

A total of 67 participants took part in the study. The rejection of specified ethical concerns across all the respondents was 77%. For items related to both perceived usefulness and intention to use, 75% of ratings across all the respondents were positive. In the follow-up discussions, the participants showed interest and openness toward the prototype, although there were varying opinions on aspects such as size, appearance, velocity, and potential impact on workload.

CONCLUSIONS

Regarding the current state of development, the acceptance among the participants was high, and ethical concerns were relatively minor. Moving forward, it would be beneficial to explore the acceptance in further developmental stages of the system, particularly when the usability is tested.

Automation in nursing decision support systems: A systematic review of effects on decision making, care delivery, and patient outcomes

OBJECTIVE

The study sought to summarize research literature on nursing decision support systems (DSSs ); understand which steps of the nursing care process (NCP) are supported by DSSs, and analyze effects of automated information processing on decision making, care delivery, and patient outcomes.

MATERIALS AND METHODS

We conducted a systematic review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. PubMed, CINAHL, Cochrane, Embase, Scopus, and Web of Science were searched from January 2014 to April 2020 for studies focusing on DSSs used exclusively by nurses and their effects. Information about the stages of automation (information acquisition, information analysis, decision and action selection, and action implementation), NCP, and effects was assessed.

RESULTS

Of 1019 articles retrieved, 28 met the inclusion criteria, each studying a unique DSS. Most DSSs were concerned with two NCP steps: assessment (82%) and intervention (86%). In terms of automation, all included DSSs automated information analysis and decision selection. Five DSSs automated information acquisition and only one automated action implementation. Effects on decision making, care delivery, and patient outcome were mixed. DSSs improved compliance with recommendations and reduced decision time, but impacts were not always sustainable. There were improvements in evidence-based practice, but impact on patient outcomes was mixed.

CONCLUSIONS

Current nursing DSSs do not adequately support the NCP and have limited automation. There remain many opportunities to enhance automation, especially at the stage of information acquisition. Further research is needed to understand how automation within the NCP can improve nurses' decision making, care delivery, and patient outcomes.