Vollmar Horst Christian, Kramer Ursula, Müller Hardy, Griemmert Maria, Noelle Guido, Schrappe Matthias
Institut für Allgemeinmedizin, Universitatsklinikum Jena, Jena.
Abteilung für Allgemeinmedizin, Ruhr-Universität Bochum.
Gesundheitswesen. 2017 Dec;79(12):1080-1092. doi: 10.1055/s-0043-122233. Epub 2017 Dec 29.
The term "digital health" is currently the most comprehensive term that includes all information and communication technologies in healthcare, including e-health, mobile health, telemedicine, big data, health apps and others. Digital health can be seen as a good example of the use of the concept and methodology of health services research in the interaction between complex interventions and complex contexts. The position paper deals with 1) digital health as the subject of health services research; 2) digital health as a methodological and ethical challenge for health services research. The often-postulated benefits of digital health interventions should be demonstrated with good studies. First systematic evaluations of apps for "treatment support" show that risks are higher than benefits. The need for a rigorous proof applies even more to big data-assisted interventions that support decision-making in the treatment process with the support of artificial intelligence. Of course, from the point of view of health services research, it is worth participating as much as possible in data access available through digital health and "big data". However, there is the risk that a noncritical application of digital health and big data will lead to a return to a linear understanding of biomedical research, which, at best, accepts complex conditions assuming multivariate models but does not take complex facts into account. It is not just a matter of scientific ethical requirements in health services care research, for instance, better research instead of unnecessary research ("reducing waste"), but it is primarily a matter of anticipating the social consequences (system level) of scientific analysis and evaluation. This is both a challenge and an attractive option for health services research to present itself as a mature and responsible scientific discipline.
“数字健康”一词目前是最具综合性的术语,涵盖了医疗保健领域中的所有信息和通信技术,包括电子健康、移动健康、远程医疗、大数据、健康应用程序等。数字健康可被视为在复杂干预措施与复杂环境之间的相互作用中运用健康服务研究的概念和方法的一个很好的例子。本立场文件探讨了:1)数字健康作为健康服务研究的主题;2)数字健康作为健康服务研究在方法和伦理方面的挑战。数字健康干预措施通常所宣称的益处应该通过高质量的研究来证明。对“治疗支持”类应用程序的首次系统评估表明,风险高于益处。对于借助人工智能支持治疗过程中决策的大数据辅助干预措施,更需要进行严格的论证。当然,从健康服务研究的角度来看,尽可能多地参与通过数字健康和“大数据”获取的数据是值得的。然而,存在这样一种风险,即对数字健康和大数据的非批判性应用将导致回归到对生物医学研究的线性理解,这种理解充其量只是在假设多变量模型的情况下接受复杂条件,但并未考虑复杂的实际情况。这不仅仅涉及健康服务护理研究中的科学伦理要求,例如,进行更好的研究而非不必要的研究(“减少浪费”),但主要涉及预测科学分析和评估的社会后果(系统层面)。这对于健康服务研究而言既是一项挑战,也是一个颇具吸引力的选择,使其能够展现为一门成熟且负责任的科学学科。