Burckhardt Philipp, Padman Rema
Carnegie Mellon University, Pittsburgh, PA.
AMIA Annu Symp Proc. 2015 Nov 5;2015:1821-30. eCollection 2015.
The Internet has emerged as a popular source for health-related information. More than eighty percent of American Internet users have searched for health topics online. Millions of patients use self-help online forums to exchange information and support. In parallel, the increasing prevalence of chronic diseases has become a financial burden for the healthcare system demanding new, cost-effective interventions. To provide such interventions, it is necessary to understand patients' preferences of treatment options and to gain insights into their experiences as patients. We introduce a text-processing algorithm based on semantic ontologies to allow for finer-grained analyses of online forums compared to standard methods. We have applied our method in an analysis of two major Chronic Kidney Disease (CKD) forums. Our results suggest that the analysis of forums may provide valuable insights on daily issues patients face, their choice of different treatment options and interactions between patients, their relatives and clinicians.
互联网已成为健康相关信息的热门来源。超过80%的美国互联网用户曾在线搜索健康话题。数百万患者利用在线自助论坛交流信息并获取支持。与此同时，慢性病患病率的不断上升已成为医疗系统的一项经济负担，这就需要新的、具有成本效益的干预措施。为了提供此类干预措施，有必要了解患者对治疗方案的偏好，并深入了解他们作为患者的经历。我们引入了一种基于语义本体的文本处理算法，以便与标准方法相比，能够对在线论坛进行更细致的分析。我们已将我们的方法应用于对两个主要的慢性肾脏病（CKD）论坛的分析。我们的结果表明，对论坛的分析可能会为患者面临的日常问题、他们对不同治疗方案的选择以及患者、其亲属和临床医生之间的互动提供有价值的见解。
