Herrmann Maximilian, Boehme Philip, Hansen Arne, Jansson Katharina, Rebacz Patrick, Ehlers Jan P, Mondritzki Thomas, Truebel Hubert
Didactics and Educational Research in Health Science, Faculty of Health, Witten/Herdecke University, Witten, Germany.
Research & Development, Pharmaceuticals, Bayer Aktiengesellschaft, Wuppertal, Germany.
J Med Internet Res. 2020 Jan 24;22(1):e13077. doi: 10.2196/13077.
Nonadherence to medication is a driver of morbidity and mortality, and complex medication regimens in patients with chronic diseases foster the problem. Digital technology might help, but despite numerous solutions being developed, none are currently widely used, and acceptance rates remain low, especially among the elderly.
This study aimed to better understand and operationalize how new digital solutions can be evaluated. Particularly, the goal was to identify factors that help digital approaches targeting adherence to become more widely accepted.
A qualitative study using a conceptual grounded theory approach was conducted. We included patients aged 65 years and older who routinely took new oral anticoagulants. To generate theses about the digital competencies of the target group with daily medication intake, face-to-face interviews were conducted, recorded, and anonymized. After coding the interviews, categories were generated, discussed, and combined with several theses until saturation of the statements was reached.
The methodological approach led to the finding that after interviews in 20 of 77 potentially available patients, a saturation of statements was reached. The average patient's age was 75 years, and 50% (10/20) of the subjects were female. The data identified five main coding categories-Diseases and medicine, Technology, Autonomy, Patient narrative, and Attitude toward technologies-each including positive and negative subcategories. Main categories and subcategories were summarized as Adherence Radar, which can be considered as a framework to assess the potential of adherence solutions in the process of prototyping and can be applied to all adherence tools in a holistic manner.
The Adherence Radar can be used to increase the acceptance rate of digital solutions targeting adherence. For a patient-centric design, an app should be adapted to the individual patient's needs. According to our results, this application should be based on gender and educational background as well as the individual physician-patient relationship. If used in a proper, individualized manner, digital adherence solutions could become a new cornerstone for the treatment of chronically ill individuals.
不遵医嘱服药是发病和死亡的一个驱动因素,慢性病患者复杂的药物治疗方案加剧了这一问题。数字技术或许有所帮助,但尽管已开发出众多解决方案,目前却无一得到广泛应用,接受率依然很低,尤其是在老年人当中。
本研究旨在更好地理解并实施对新数字解决方案的评估方法。具体而言,目标是确定有助于提高针对服药依从性的数字方法接受度的因素。
采用概念性扎根理论方法进行了一项定性研究。纳入了年龄在65岁及以上且常规服用新型口服抗凝剂的患者。为了得出关于目标群体日常服药数字能力的论点,进行了面对面访谈、录音并匿名处理。对访谈进行编码后,生成类别、进行讨论并与多个论点相结合,直至陈述达到饱和状态。
该方法得出的结果是,在77名潜在受访患者中的20名接受访谈后陈述达到饱和。患者的平均年龄为75岁 ,50%(10/20)的受试者为女性。数据确定了五个主要编码类别——疾病与药物、技术、自主性、患者叙述以及对技术的态度——每个类别都包括正面和负面子类别。主要类别和子类别被总结为“依从性雷达”,可被视为评估原型制作过程中依从性解决方案潜力的框架,并可整体应用于所有依从性工具。
“依从性雷达”可用于提高针对依从性的数字解决方案的接受率。对于以患者为中心的设计而言,应用程序应根据个体患者的需求进行调整。根据我们研究结果,这种应用应基于性别、教育背景以及个体医患关系。如果以适当、个性化的方式使用,数字依从性解决方案可能会成为慢性病患者治疗的新基石。