Barriers and Facilitators to the Implementation of an Electronic Patient-Reported Outcome System at Cancer Hospitals in Japan.

Yu Uneno,Keita Fukuyama, Ayumi Nishimura, Kana Eguchi, Hideki Kojima, Takeshi Umino,Kikuko Miyazaki, Eiju Negora,Keiko Minashi,Osamu Sugiyama,Taichi Shimazu,Manabu Muto,Shigemi Matsumoto

Cureus(2024)

引用 0|浏览3
暂无评分
摘要
Background and objective Implementing electronic patient-reported outcomes (ePROs) in oncology practice has shown substantial clinical benefits. However, it can be challenging in routine practice, warranting strategies to adapt to different clinical contexts. In light of this, this study aimed to describe the implementation process of the ePRO system and elucidate the provider-level implementation barriers and facilitators to a novel ePRO system at cancer hospitals in Japan. Methods We implemented an ePRO system linked to electronic medical records at three cancer hospitals. Fifteen patients with solid cancers at the outpatient oncology unit were asked to regularly complete the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE™) questionnaire and European Organization for Research and Treatment Core Quality of Life questionnaire (EORTC QLQ C30) by using the smartphone app between October 2021 and June 2022. Thirteen healthcare professionals were interviewed to identify implementation barriers and facilitators to the ePRO system by using the Consolidated Framework for Implementation Research framework. Results The healthcare professionals identified a lack of clinical resources and a culture and system that emphasizes treatment over care as the main barriers; however, the accumulation of successful cases, the leadership of managers, and the growing needs of patients can serve as facilitators to the implementation. Conclusions Our experience implementing an ePRO system in a few Japanese oncology practices revealed comprehensive barriers and facilitators. Further efforts are warranted to develop more successful implementation strategies.
更多
查看译文
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