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A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol for a Content Analysis

机译:用于分析患者生成的叙事数据的系统框架:内容分析的协议

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Background Patient narrative data in online health care forums (communities) are receiving increasing attention from the scientific community for implementing patient-centered care. Natural language processing (NLP) methods are gaining more and more attention because of the enormous data volume. However, state-of-the-art NLP still cannot meet the need of high-resolution analysis of patients’ narratives. Manual qualitative analysis still plays a pivotal role in answering complicated research questions from analyzing patient narratives. Objective This study aimed to develop a systematic framework for qualitative analysis of patient-generated narratives in online health care forums. Methods Our systematic framework consists of 4 phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results. Data collection and data preparation phases are constructed based on text mining methods for identifying appropriate online health forums for data collection, differentiating posts of patients from other stakeholders, protecting patients’ privacy, sampling, and choosing the unit of analysis. Content analysis phase is built on the framework method, which facilitates and accelerates the identification of patterns and themes by an interdisciplinary research team. In the end, the focus of interpretation of the results phase is to measure the data quality and interpret the findings regarding the dimensions and aspects of patients’ experiences and concerns in their original contexts. Results We demonstrated the usability of the proposed systematic framework using 2 case studies: one on determining factors affecting patients’ attitudes toward antidepressants and another on identifying the disease management strategies in patient with diabetes facing financial difficulties. The framework provides a clear step-by-step process for systematic content analysis of patient narratives and produces high-quality structured results that can be used for describing patterns or regularities in patients’ experiences, generating and testing hypotheses, and identifying areas of improvement in the health care systems. Conclusions The systematic framework is a rigorous and standardized method for qualitative analysis of patient narratives. Findings obtained through such a process indicate authentic dimensions and aspects of patient experiences and shed light on patients’ concerns, needs, preferences, and values, which are the core of patient-centered care.
机译:背景患者在线医疗论坛(社区)中的叙述数据正在接受来自科学界的越来越多的关注,以实施以患者为中心的护理。自然语言处理(NLP)方法由于数据量庞大而越来越多地受到关注。然而,最先进的NLP仍然无法满足对患者叙事的高分辨率分析的需求。手动定性分析仍在回答复杂的研究问题方面发挥关键作用,分析患者叙述。目的本研究旨在为在线医疗论坛的患者生成的叙事进行定性分析系统框架。方法,我们的系统框架由4个阶段组成:(1)数据收集,(2)数据准备,(3)内容分析,以及(4)对结果的解释。数据收集和数据准备阶段基于文本挖掘方法构建,用于识别数据收集的适当在线健康论坛,区分其他利益攸关方的患者职位,保护患者隐私,采样和选择分析单位。内容分析阶段建立在框架方法上,促进​​并加速了跨学科研究团队的模式和主题的识别。最后,解释结果阶段的焦点是测量数据质量,并解释关于患者在原始背景下的患者经历的尺寸和方面的结果。结果我们展示了使用2个案例研究所提出的系统框架的可用性:一个关于影响患者对抗抑郁药态度的决定因素,另一个关于鉴定患有财务困难的患者疾病管理策略。该框架为患者叙述的系统内容分析提供了一个明确的逐步处理,并产生高质量的结构结果,可用于描述患者经验的模式或规律,生成和测试假设,并识别改进领域医疗保健系统。结论系统框架是一种严格且标准化的患者叙事定性分析的方法。通过这种过程获得的结果表明了患者的患者的担忧,需求,偏好和价值观的真实尺寸和方面,以及患者中心护理的核心。

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