论文标题
遵守个人健康设备：糖尿病管理案例研究
Adherence to Personal Health Devices: A Case Study in Diabetes Management
论文作者
论文摘要
个人健康设备可以连续监控健康参数。但是，这些设备的好处通常与使用频率直接相关。因此，遵守个人健康设备至关重要。本文采用了数据挖掘方法来研究糖尿病管理中的连续葡萄糖监测器的使用。我们评估了来自44名受试者的两个独立数据集60-270天。我们的结果表明：1）错过目标目标（即次优结果）是与个人健康设备的佩戴行为相关的因素，而2）较长的不遵守持续时间，通过缺失的数据或数据差距确定，与较差的结果显着相关。更具体地说，我们发现当用户处于异常血糖类别时，多达33％的数据差距发生。最长的数据差距发生在最严重的葡萄糖类别中。此外，控制糖尿病的受试者的平均数据间隙持续时间比患有良好控制的糖尿病的受试者的平均数据间隙持续时间更长。这项工作有助于文献上关于上下文感知系统的设计，这些系统可以利用数据驱动的方法来理解影响非磨牙行为的因素。结果还可以支持有针对性的干预措施，以改善健康结果。
Personal health devices can enable continuous monitoring of health parameters. However, the benefit of these devices is often directly related to the frequency of use. Therefore, adherence to personal health devices is critical. This paper takes a data mining approach to study continuous glucose monitor use in diabetes management. We evaluate two independent datasets from a total of 44 subjects for 60 - 270 days. Our results show that: 1) missed target goals (i.e. suboptimal outcomes) is a factor that is associated with wearing behavior of personal health devices, and 2) longer duration of non-adherence, identified through missing data or data gaps, is significantly associated with poorer outcomes. More specifically, we found that up to 33% of data gaps occurred when users were in abnormal blood glucose categories. The longest data gaps occurred in the most severe (i.e. very low / very high) glucose categories. Additionally, subjects with poorly-controlled diabetes had longer average data gap duration than subjects with well-controlled diabetes. This work contributes to the literature on the design of context-aware systems that can leverage data-driven approaches to understand factors that influence non-wearing behavior. The results can also support targeted interventions to improve health outcomes.
