Virtanen Lotta, Kaihlanen Anu-Marja, Kainiemi Emma, Saukkonen Petra, Heponiemi Tarja
Welfare State Research and Reform Unit, Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
Digit Health. 2023 May 25;9:20552076231178422. doi: 10.1177/20552076231178422. eCollection 2023 Jan-Dec.
Utilising digital health services in the treatment of patients who frequently attend outpatient care could be beneficial for patients' health and the sustainability of health systems but carries the risk of digital exclusion. This study aimed to explore the patterns of acceptance and use of digital health services among frequent attenders (FAs), which may help in the assessment of patients' digital suitability.
Persistent FAs ( = 30) were recruited by random sampling from one Finnish municipality. The semistructured interviews were conducted in February-May 2021. We analysed the data with qualitative content analysis using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Additionally, we quantified the data for two-step cluster analyses to create separate cluster models that grouped FAs based on acceptance and use of (a) digital services for self-management of health and (b) telemedicine services.
Based on digital self-management, FAs were defined as , , and . Based on telemedicine use, they were grouped into , , and . The clusters described different opportunities, awareness, and interest in using digital health services. Referral from professionals seemed to promote digital service use. For some, digital services were not accessible.
Our findings emphasise the importance of assessing the suitability of FAs to digital health services, as their readiness to use may vary. Professionals should recommend digital services that support individual health to suitable patients. More accessible digital services could promote digital suitability despite functional limitations.
在频繁就诊的门诊患者治疗中使用数字健康服务可能有利于患者健康和卫生系统的可持续性，但存在数字排斥的风险。本研究旨在探索频繁就诊者（FAs）对数字健康服务的接受和使用模式，这可能有助于评估患者的数字适配性。
通过随机抽样从芬兰的一个市镇招募了30名持续性频繁就诊者。于2021年2月至5月进行了半结构化访谈。我们使用技术接受与使用统一理论（UTAUT）模型，通过定性内容分析法对数据进行了分析。此外，我们对数据进行了量化，以进行两步聚类分析，从而创建基于对（a）健康自我管理数字服务和（b）远程医疗服务的接受和使用情况对频繁就诊者进行分组的单独聚类模型。
基于数字自我管理，频繁就诊者被定义为[具体类别1]、[具体类别2]和[具体类别3]。基于远程医疗的使用情况，他们被分为[具体类别4]、[具体类别5]和[具体类别6]。这些聚类描述了在使用数字健康服务方面的不同机会、意识和兴趣。专业人员的推荐似乎促进了数字服务的使用。对一些人来说，无法使用数字服务。
我们的研究结果强调了评估频繁就诊者对数字健康服务适配性的重要性，因为他们使用数字服务的意愿可能各不相同。专业人员应向合适的患者推荐支持个人健康的数字服务。尽管存在功能限制，但更易获取的数字服务可以提高数字适配性。
