Nephrology Nurses' Perspectives for the Designs of Mobile Hemodialysis Devices: A Human Factors Engineering Approach.

Nephrology nursing journal : journal of the American Nephrology Nurses' Association(2022)

引用 0|浏览1
暂无评分
摘要
The goal of this study was to guide the early conceptual designs of two devices intended to improve the quality of life for patients on hemodialysis: a portable hemodialysis device and a wearable hemodialysis device. Thirty-two nephrology nurses were interviewed using a mixed approach of open-ended, rating, and rank-order questions. Results show most nurses try to persuade patients to try a modality of treatment that offers them the best clinical outcome and highest quality of life. Many nurses, however, indicate that patients are often not given the opportunity to choose their preferred modality of treatment, and that current hemodialysis treatments are one-size-fits-all and should be more individualized. Nurses also believe high-frequency home-based, portable, or wearable hemodialysis treatments are better for patients than in-center treatments, and patients can learn to safely connect and disconnect a hemodialysis device to their catheter. Using content analysis, we identified six categories of potential benefits a patient may experience using either a portable or a wearable hemodialysis device. We also identified six categories of potential barriers that may hinder nephrology nurses in recommending either a portable or a wearable hemodialysis device to their patients and seven categories of ideal features for the designs of the devices. Statistical analysis of rank-order questions shows nephrology nurses prefer a wearable hemodialysis device in the form of a belt compared to other designs (p < 0.05). Findings from this study provide valuable information guiding the design process of mobile hemodialysis devices that nephrology nurses will feel comfortable recommending to their patients.
更多
查看译文
关键词
artificial kidney,human factors,mobile dialysis,nurses' perspectives,wearable medical device
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要