Classification of patient‐ and clinician‐generated secure messages using a theory‐based taxonomy

Health Science Reports(2021)

引用 0|浏览4
暂无评分
摘要
Abstract Background As secure electronic message exchange increases between patients and clinicians, we must explore and understand how patients and clinicians use those messages to communicate between clinical visits. Objective To present the application of a taxonomy developed specifically to code secure message content in a way that allows for identification of patient and clinician communication functions demonstrated to be associated with patients' intermediate and health outcomes. Method We randomly sampled 1031 patients who sent and received 18 309 messages and coded those messages with codes from our taxonomy. We present the prevalence of each taxon (ie, code) within the sample. Results The most common taxon among initial patient‐generated messages were Information seeking (29.09%), followed by Scheduling requests (27.91%), and Prescription requests (23.09%). Over half of subsequent patient‐generated messages included responses to clinic staffs' questions (58.31%). Six in 10 clinic staff responses included some form of Information sharing with process‐based responses being most common (32.81%). A third of all clinician‐generated messages (36.28%) included acknowledgement or some level of fulfilment of a patient's task‐oriented request. Clinic staff sought information from patients in 20.54% of their messages. Conclusion This taxonomy is the first step toward examining whether secure messaging communication can be associated with patients' health outcomes. Knowing which content is positively associated with outcomes can support training of, and targeted responses from, clinicians with the goal of generating message content designed to improve outcomes. Patient Contribution This study is based on analyses of patient‐initiated secure message threads.
更多
查看译文
关键词
electronic messaging,health IT,patient‐centered communication,patient‐provider communication
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