论文标题
使用DAPMAV框架从社交媒体上揭示患者报告的医疗保健经验
Revealing Patient-Reported Experiences in Healthcare from Social Media using the DAPMAV Framework
论文作者
论文摘要
了解患者在医疗保健方面的经验越来越重要,并且在以患者为中心的护理方法中,医疗专业人员希望。社交媒体上的医疗保健论述为获得患者报告的体验的独特视角提供了机会,并补充了传统的调查数据。这些社交媒体报告通常是通过医疗保健系统的患者旅行的第一手说明,其细节超出了结构化调查的范围,并且比焦点小组大得多。但是,与社交媒体上的大量患者体验数据以及数据所提供的潜在好处相反,由于文本分析所需的技术水平,它吸引了相对较少的研究注意力。在本文中,我们介绍了Design-Acquire-Process-Model-Model-Analyse-Visalise(DAPMAV)框架,以提供技术概述和一种从社交媒体数据中捕获患者报告的体验的方法。我们在 /r /prostatecancer的前列腺癌数据的案例研究中应用了此框架,该框架在捕获患者关注的特定方面(例如性功能障碍),概述了该框架的价值,概述了话语,并通过这些故事表现出叙事和情感进展。我们预计该框架将适用于医疗保健领域的各种领域,包括捕获和区分少数群体,地理边界和疾病类型的经历。
Understanding patient experience in healthcare is increasingly important and desired by medical professionals in a patient-centered care approach. Healthcare discourse on social media presents an opportunity to gain a unique perspective on patient-reported experiences, complementing traditional survey data. These social media reports often appear as first-hand accounts of patients' journeys through the healthcare system, whose details extend beyond the confines of structured surveys and at a far larger scale than focus groups. However, in contrast with the vast presence of patient-experience data on social media and the potential benefits the data offers, it attracts comparatively little research attention due to the technical proficiency required for text analysis. In this paper, we introduce the Design-Acquire-Process-Model-Analyse-Visualise (DAPMAV) framework to provide an overview of techniques and an approach to capture patient-reported experiences from social media data. We apply this framework in a case study on prostate cancer data from /r/ProstateCancer, demonstrate the framework's value in capturing specific aspects of patient concern (such as sexual dysfunction), provide an overview of the discourse, and show narrative and emotional progression through these stories. We anticipate this framework to apply to a wide variety of areas in healthcare, including capturing and differentiating experiences across minority groups, geographic boundaries, and types of illnesses.