Use and impact of an online community for hospital patients.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION(2020)

引用 11|浏览125
暂无评分
摘要
Objective: Although patient-peer support technologies have demonstrated effectiveness in a variety of health contexts-including diabetes, weight loss, and cancer-less is known about how hospitalized patients can benefit from this support. We investigated the nature of peer support in the hospital and the impact this support had on patients' hospital stays. Materials and Methods: We created a technology, resembling an online health community, in which patients could exchange advice about their hospitalization. We deployed it at 1 pediatric hospital and 1 adult hospital. With 30 participants, we conducted bedside interviews, observed how they used the technology during their hospitalization, and completed follow-up phone interviews. Results: Participants shared advice about several topics, including adjusting to the hospital and building relationships with providers. Contrary to concerns that such a system would primarily serve as a place for patients to "complain," sentiment analysis showed that 23 of 36 (64%) of the shared advice reflected positive sentiment. Patients also reported positive impacts to their quality, safety, and hospital experience due to the inpatient peer support community. Discussion: Participants benefited from peer support that transcended diagnoses and individual health conditions. The shared experience of being in the hospital was sufficient to yield valuable and practical peer support. Participants who did not contribute their own advice still experienced benefits from reading their peers' advice. Conclusions: Our study demonstrated the positive nature of peer advice exchanged, and the benefits of this advice on patients' hospital stays. Inpatient peer support technologies could be an additional resource for patients to engage in their care.
更多
查看译文
关键词
peer support,patient-facing technology,human-computer interaction,quality and safety,patient engagement,online health communities
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